From 56a722a1d01eb49bfbe5120065c615ecf1e16fe5 Mon Sep 17 00:00:00 2001 From: caoying03 Date: Mon, 10 Jul 2017 14:22:18 +0800 Subject: [PATCH 001/138] output all beam search results in layer group. --- .../RecurrentGradientMachine.cpp | 104 ++++++++++++------ .../RecurrentGradientMachine.h | 7 +- paddle/parameter/Argument.cpp | 36 +++--- paddle/parameter/Argument.h | 1 + .../paddle/trainer_config_helpers/networks.py | 13 +-- 5 files changed, 102 insertions(+), 59 deletions(-) diff --git a/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp b/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp index 41e0929959..4cb5b8ec2d 100644 --- a/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp +++ b/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp @@ -1012,11 +1012,6 @@ void RecurrentGradientMachine::generateSequence() { /* width */ resultNum, false, /* useGpu */ false); - Matrix::resizeOrCreate(generator_.outArg.value, - /* height */ maxGenWordCount, - /* width */ 1, - false, - /* useGpu */ false); } ICpuGpuVector::resizeOrCreate(generator_.outArg.sequenceStartPositions, numSequences + 1, @@ -1026,7 +1021,7 @@ void RecurrentGradientMachine::generateSequence() { } else { oneWaySearch(numSequences); } - if (dataArgsSize_) createDataOutlink(batchMachineIdVec_); + if (dataArgsSize_) createDataOutlink(); size_t size = generator_.ids.size(); generator_.outArg.ids->resize(size); @@ -1106,6 +1101,7 @@ void RecurrentGradientMachine::oneWaySearch(size_t batchSize) { } batchMachineIdVec_.clear(); + batchMachineStartPos_.clear(); int* starts = generator_.outArg.sequenceStartPositions->getMutableData(false); starts[0] = 0; generator_.ids.clear(); @@ -1312,13 +1308,20 @@ void RecurrentGradientMachine::fillGenOutputs() { finalPaths_[i].resize(minFinalPathsSize); } - batchMachineIdVec_.clear(); generator_.ids.clear(); int* starts = generator_.outArg.sequenceStartPositions->getMutableData(false); starts[0] = 0; if (numResults > 1) { - real* probs = generator_.outArg.in->getData(); + int idsProbSaveSize = 0; + for (auto inSeq : finalPaths_) { + for (auto path : inSeq) idsProbSaveSize += path.ids.size(); + idsProbSaveSize += inSeq.size(); + } + Matrix::resizeOrCreate( + generator_.outArg.value, idsProbSaveSize, 1, false, false); real* idsProb = generator_.outArg.value->getData(); + + real* probs = generator_.outArg.in->getData(); size_t curPos = 0; for (size_t i = 0; i < finalPaths_.size(); ++i) { for (size_t j = 0; j < finalPaths_[i].size(); ++j) { @@ -1333,24 +1336,16 @@ void RecurrentGradientMachine::fillGenOutputs() { curPos += genLen; idsProb[curPos++] = -1.0; probs[i * numResults + j] = path.logProb; - - if (!j && dataArgsSize_) { - // in beam search, here only reserved the top 1 generated result - // for out_links that are not the generated word indices. - batchMachineIdVec_.insert(batchMachineIdVec_.end(), - path.machineIdVec.begin(), - path.machineIdVec.end()); - } } starts[i + 1] = generator_.ids.size(); } } else { for (size_t i = 0; i < finalPaths_.size(); ++i) { CHECK(!finalPaths_[i].empty()); - generator_.ids.insert(generator_.ids.begin(), - finalPaths_[i][0].ids.begin(), - finalPaths_[i][0].ids.end()); - starts[i + 1] = starts[i] + finalPaths_[i][0].ids.size(); + Path& path = finalPaths_[i][0]; + generator_.ids.insert( + generator_.ids.begin(), path.ids.begin(), path.ids.end()); + starts[i + 1] = starts[i] + path.ids.size(); } } } @@ -1364,25 +1359,70 @@ void RecurrentGradientMachine::copyDataOutlinkFrame(size_t machineCur) { } } -void RecurrentGradientMachine::createDataOutlink( - std::vector& machineIdVec) { - size_t seqNum = - getBeamSize() > 1UL ? finalPaths_.size() : finalPaths_[0].size(); - std::vector starts(seqNum + 1, 0); - for (size_t i = 0; i < seqNum; ++i) { - size_t seqLen = getBeamSize() > 1UL ? finalPaths_[i][0].ids.size() - : finalPaths_[0][i].ids.size(); - starts[i + 1] = starts[i] + seqLen; +void RecurrentGradientMachine::createDataOutlinkSelRowsInfo( + bool isSeq, std::vector& outArgs) { + batchMachineIdVec_.clear(); + + size_t seqIdx = 0; + for (size_t i = 0; i < finalPaths_.size(); ++i) { + for (size_t j = 0; j < finalPaths_[i].size(); ++j) { + std::vector& machineIdVec = finalPaths_[i][j].machineIdVec; + if (isSeq) { + for (size_t i = 0; i < machineIdVec.size(); ++i) { + size_t rowId = machineIdVec[i]; + int* seqPos = + outArgs[i].sequenceStartPositions->getMutableData(false); + batchMachineIdVec_.push_back(seqPos[rowId]); + } + } else { + batchMachineIdVec_.insert( + batchMachineIdVec_.end(), machineIdVec.begin(), machineIdVec.end()); + } + seqIdx++; + } + } +} + +void RecurrentGradientMachine::createDataOutlinkCopySizeInfo( + bool isSeq, std::vector& outArgs, std::vector& copySize) { + size_t totalSeqNum = std::accumulate( + finalPaths_.begin(), + finalPaths_.end(), + 0UL, + [](size_t a, const std::vector& b) { return a + b.size(); }); + copySize.resize(totalSeqNum, 1); + + batchMachineStartPos_.resize(totalSeqNum + 1, 0); + if (isSeq) { + ICpuGpuVectorPtr inputSeqStartPos = outArgs[0].sequenceStartPositions; + CHECK_EQ(inputSeqStartPos->getSize() - 1, finalPaths_.size()); + int* starts = inputSeqStartPos->getMutableData(false); + int seqId = 0; + for (int i = 0; i < finalPaths_.size(); ++i) { + for (int j = 0; j < finalPaths_[i].size(); ++j) { + copySize[seqId] = starts[i + 1] - starts[i]; + batchMachineStartPos_[seqId + 1] = + batchMachineStartPos_[seqId] + finalPaths_[i][j].ids.size(); + seqId++; + } + } } +} +void RecurrentGradientMachine::createDataOutlink() { for (size_t i = 0; i < dataArgsSize_; i++) { + bool isSeq = dataArgsFrame_[i][0].hasSeq(); + std::vector copySize; + createDataOutlinkCopySizeInfo(isSeq, dataArgsFrame_[i], copySize); + createDataOutlinkSelRowsInfo(isSeq, dataArgsFrame_[i]); + dataArgs_[i].concat(dataArgsFrame_[i], - machineIdVec, - starts, + batchMachineIdVec_, + batchMachineStartPos_, + copySize, useGpu_, HPPL_STREAM_1, PASS_TEST); - auto dataAgent = dynamic_cast(outFrameLines_[i + 1].agentLayer.get()); CHECK_NOTNULL(dataAgent); diff --git a/paddle/gserver/gradientmachines/RecurrentGradientMachine.h b/paddle/gserver/gradientmachines/RecurrentGradientMachine.h index fb3fc5877a..bd096770b7 100644 --- a/paddle/gserver/gradientmachines/RecurrentGradientMachine.h +++ b/paddle/gserver/gradientmachines/RecurrentGradientMachine.h @@ -480,7 +480,11 @@ private: * @param machineIdVec : select a row of output matrix in each frame * that the generation process expanded. */ - void createDataOutlink(std::vector& machineIdVec); + void createDataOutlink(); + void createDataOutlinkCopySizeInfo(bool isSeq, + std::vector& outArgs, + std::vector& copySize); + void createDataOutlinkSelRowsInfo(bool isSeq, std::vector& outArgs); /* * @brief used in beam search, connect previous frame to form recurrent link @@ -543,6 +547,7 @@ private: std::vector topIds_; std::vector seqIds_; std::vector batchMachineIdVec_; + std::vector batchMachineStartPos_; std::vector> finalPaths_; std::vector minFinalPathLogProb_; BeamSearchControlCallbacks* beamSearchCtrlCallbacks_; diff --git a/paddle/parameter/Argument.cpp b/paddle/parameter/Argument.cpp index ef72b973c1..e7522def08 100644 --- a/paddle/parameter/Argument.cpp +++ b/paddle/parameter/Argument.cpp @@ -276,17 +276,21 @@ int32_t Argument::resizeAndCopyFrom(const Argument& src, void Argument::concat(const std::vector& args, const std::vector& selectRows, const std::vector& seqStartPos, + const std::vector& copySize, bool useGpu, hl_stream_t stream, PassType passType) { CHECK(!subSequenceStartPositions) << "undefined behavior for subsequence positions"; - size_t batchSize = selectRows.size(); + size_t batchSize = 0; + for (size_t i = 0; i < copySize.size(); ++i) + batchSize += copySize[i] * (seqStartPos[i + 1] - seqStartPos[i]); + auto copyArg = [batchSize, stream](MatrixPtr& dst, MatrixPtr src, - int startRow, - int pos, + int desStartRow, + int srcStartRow, int size, bool useGpu) { if (!src) { @@ -300,8 +304,8 @@ void Argument::concat(const std::vector& args, dst->resize(batchSize, width); } - MatrixPtr tmpMatrix = dst->subMatrix(startRow, size); - tmpMatrix->copyFrom(*src->subMatrix(pos, size), stream); + MatrixPtr tmpMatrix = dst->subMatrix(desStartRow, size); + tmpMatrix->copyFrom(*src->subMatrix(srcStartRow, size), stream); }; auto copyIds = [batchSize, stream](IVectorPtr& dst, @@ -339,24 +343,24 @@ void Argument::concat(const std::vector& args, dataId = args[0].dataId; CHECK_NE(seqStartPos.size(), 0UL); - size_t sampleNum = seqStartPos.size() - 1; - for (size_t i = 0; i < sampleNum; ++i) { + int desStartRow = 0; + for (size_t i = 0; i < copySize.size(); ++i) { int startPos = seqStartPos[i]; int endPos = seqStartPos[i + 1]; CHECK_GE(args.size(), static_cast(endPos - startPos)); for (int j = startPos; j < endPos; ++j) { const Argument& arg = args[j - startPos]; - CHECK_EQ(arg.dataId, dataId) << "Arguments in concat should have" - << " same dataId"; - const int copySize = 1; - const int rowIdx = selectRows[j]; - copyArg(in, arg.in, j, rowIdx, copySize, useGpu); - copyArg(value, arg.value, j, rowIdx, copySize, useGpu); + CHECK_EQ(arg.dataId, dataId) << "Arguments in concat should have the " + << "same dataId"; + const int srcStartRow = selectRows[j]; + copyArg(in, arg.in, desStartRow, srcStartRow, copySize[i], useGpu); + copyArg(value, arg.value, desStartRow, srcStartRow, copySize[i], useGpu); if (passType != PASS_TEST) { - copyArg(grad, arg.grad, j, rowIdx, copySize, useGpu); + copyArg(grad, arg.grad, desStartRow, srcStartRow, copySize[i], useGpu); } - copyIds(ids, arg.ids, j, rowIdx, copySize, useGpu); - copyStrs(strs, arg.strs, j, rowIdx, copySize, useGpu); + copyIds(ids, arg.ids, desStartRow, srcStartRow, copySize[i], useGpu); + copyStrs(strs, arg.strs, desStartRow, srcStartRow, copySize[i], useGpu); + desStartRow += copySize[i]; } } ICpuGpuVector::resizeOrCreate( diff --git a/paddle/parameter/Argument.h b/paddle/parameter/Argument.h index 0ccdef802e..be87175658 100644 --- a/paddle/parameter/Argument.h +++ b/paddle/parameter/Argument.h @@ -240,6 +240,7 @@ struct Argument { void concat(const std::vector& args, const std::vector& selectRows, const std::vector& seqStartPos, + const std::vector& copySize, bool useGpu, hl_stream_t stream, PassType passType); diff --git a/python/paddle/trainer_config_helpers/networks.py b/python/paddle/trainer_config_helpers/networks.py index b77932ce5f..c0b2ced234 100755 --- a/python/paddle/trainer_config_helpers/networks.py +++ b/python/paddle/trainer_config_helpers/networks.py @@ -1370,14 +1370,7 @@ def simple_attention(encoded_sequence, param_attr=softmax_param_attr, name="%s_softmax" % name, bias_attr=False) - - scaled = scaling_layer( - weight=attention_weight, - input=encoded_sequence, - name='%s_scaling' % name) - - return pooling_layer( - input=scaled, pooling_type=SumPooling(), name="%s_pooling" % name) + return attention_weight def inputs(layers, *args): @@ -1395,7 +1388,7 @@ def inputs(layers, *args): if len(args) != 0: layers.extend(args) - Inputs(* [l.name for l in layers]) + Inputs(*[l.name for l in layers]) def outputs(layers, *args): @@ -1438,7 +1431,7 @@ def outputs(layers, *args): assert len(layers) > 0 if HasInputsSet(): # input already set - Outputs(* [l.name for l in layers]) + Outputs(*[l.name for l in layers]) return # just return outputs. if len(layers) != 1: From 4c134c7c7d201a9f28449974d489111b51c6f6fb Mon Sep 17 00:00:00 2001 From: caoying03 Date: Fri, 14 Jul 2017 17:21:36 +0800 Subject: [PATCH 002/138] add comments. --- .../RecurrentGradientMachine.h | 38 ++++++++++++++++--- paddle/parameter/Argument.cpp | 4 +- .../paddle/trainer_config_helpers/networks.py | 4 +- 3 files changed, 36 insertions(+), 10 deletions(-) diff --git a/paddle/gserver/gradientmachines/RecurrentGradientMachine.h b/paddle/gserver/gradientmachines/RecurrentGradientMachine.h index a3d04b207c..cc0eda9f13 100644 --- a/paddle/gserver/gradientmachines/RecurrentGradientMachine.h +++ b/paddle/gserver/gradientmachines/RecurrentGradientMachine.h @@ -190,7 +190,7 @@ public: std::vector ids; /** - * @brief idsProb, log probability of each generated words. + * @brief idsProb, log probability of each generated word. */ std::vector idsProb; @@ -472,16 +472,42 @@ private: void copyDataOutlinkFrame(size_t machineCur); /* - * @brief In generation, if the layer group has more than 1 outlink, outlinks - * except the first one are data outlinks. This function creates the data - * outlinks. - * @note In beam search, only one generated sequence with the hightest log - * probabilites are retained. + * @brief In generation, if the layer group has more than 1 outlink, outlink + * except the first one is a data outlink. In RecurrentLayerGroup, each time + * step is a separate Network, outputs of a layer inside the + * RecurrentLayerGroup are stored in separate Arguments. If one layer is + * specified as an outlink of RecurrentLayerGroup. This function will + * collect outputs in each time step of each generated sequence which are + * dispersed in separate Arguments to form a new single Argument as output of + * RecurrentLayerGroup. */ void createDataOutlink(); + + /* + * @brief decide to select how many rows from the Matrix stored the forward + * pass results from a start position. + * + * @param isSeq: a flag indicating whetehr the layer to be output of the + * RecurrentGradientMachine is a sequence or not + * @param outArgs: all of the the returned Arguments of the forward pass + * during the generation process. + * @param copySize: the returned result, number of rows to select from the + * Matrix stored the forward pass results from a start position. + */ void createDataOutlinkCopySizeInfo(bool isSeq, std::vector& outArgs, std::vector& copySize); + + /* + * @brief decide index of the start row for each time step of a generated + * sequence in Matrix stored the entire beam search batch's forward pass + * results. + * + * @param isSeq: a flag indicating whetehr the layer to be output of the + * RecurrentGradientMachine is a sequence or not + * @param outArgs: all of the the returned Arguments of the forward pass + * during the generation process. + */ void createDataOutlinkSelRowsInfo(bool isSeq, std::vector& outArgs); /* diff --git a/paddle/parameter/Argument.cpp b/paddle/parameter/Argument.cpp index f45a51d7b1..9a9092af9b 100644 --- a/paddle/parameter/Argument.cpp +++ b/paddle/parameter/Argument.cpp @@ -352,8 +352,8 @@ void Argument::concat(const std::vector& args, CHECK_GE(args.size(), static_cast(endPos - startPos)); for (int j = startPos; j < endPos; ++j) { const Argument& arg = args[j - startPos]; - CHECK_EQ(arg.dataId, dataId) << "Arguments in concat should have the " - << "same dataId"; + CHECK_EQ(arg.dataId, dataId) << "Arguments to concatenate should have " + << "the same dataId."; const int srcStartRow = selectRows[j]; copyArg(in, arg.in, desStartRow, srcStartRow, copySize[i], useGpu); copyArg(value, arg.value, desStartRow, srcStartRow, copySize[i], useGpu); diff --git a/python/paddle/trainer_config_helpers/networks.py b/python/paddle/trainer_config_helpers/networks.py index 30c826ffc8..810bea913e 100755 --- a/python/paddle/trainer_config_helpers/networks.py +++ b/python/paddle/trainer_config_helpers/networks.py @@ -1375,9 +1375,9 @@ def simple_attention(encoded_sequence, weight=attention_weight, input=encoded_sequence, name='%s_scaling' % name) + return pooling_layer( - input=scaled, pooling_type=SumPooling(), - name="%s_pooling" % name), attention_weight + input=scaled, pooling_type=SumPooling(), name="%s_pooling" % name) def inputs(layers, *args): From 264b644718c14da348114bb9a44afddcd7166f11 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Wed, 2 Aug 2017 21:26:29 +0800 Subject: [PATCH 003/138] "add rowwise add backward op" --- paddle/operators/rowwise_add_op.cc | 15 +++++++++++++++ paddle/operators/rowwise_add_op.h | 19 +++++++++++++++++++ 2 files changed, 34 insertions(+) diff --git a/paddle/operators/rowwise_add_op.cc b/paddle/operators/rowwise_add_op.cc index 2ad2b66c8f..cc763a8cf4 100644 --- a/paddle/operators/rowwise_add_op.cc +++ b/paddle/operators/rowwise_add_op.cc @@ -46,6 +46,17 @@ for i in xrange(X.shape[0]): )DOC"); } }; +class RowWiseAddGradOp : public OperatorWithKernel { +protected: + void InferShape(const InferShapeContext &ctx) const override { + PADDLE_ENFORCE(ctx.InputSize() == 4UL, + "RowWiseAddGrad inputs is I, O, OG, size must be 4"); + PADDLE_ENFORCE(ctx.OutputSize() == 2, + "RowWiseAddGrad output is IG, size must be 2"); + ctx.Output(0)->Resize(ctx.Input(0)->dims()); + ctx.Output(1)->Resize(ctx.Input(1)->dims()); + } +}; } // namespace operators } // namespace paddle @@ -53,3 +64,7 @@ for i in xrange(X.shape[0]): REGISTER_OP(rowwise_add, ops::RowWiseAddOp, ops::RowWiseAddOpMaker); REGISTER_OP_CPU_KERNEL(rowwise_add, ops::RowWiseAddKernel); + +REGISTER_GRADIENT_OP(rowwise_add, rowwise_add_grad, ops::RowWiseAddGradOp); +REGISTER_OP_CPU_KERNEL(rowwise_add_grad, + ops::RowWiseAddGradKernel); diff --git a/paddle/operators/rowwise_add_op.h b/paddle/operators/rowwise_add_op.h index b86dd54634..940459e0f1 100644 --- a/paddle/operators/rowwise_add_op.h +++ b/paddle/operators/rowwise_add_op.h @@ -38,5 +38,24 @@ public: } }; +template +class RowWiseAddGradKernel : public OpKernel { +public: + void Compute(const ExecutionContext& context) const override { + auto XGrad = context.Output(0); + auto bGrad = context.Output(1); + XGrad->mutable_data(context.GetPlace()); + bGrad->mutable_data(context.GetPlace()); + + // I, O, OG => [X, b], [Out], [OutGrad] + auto OutGrad = EigenMatrix::From(*context.Input(3)); + EigenMatrix::From(*XGrad).device(*(context.GetEigenDevice())) = + OutGrad; + // const int dimension = bGrad.dimension(0); + // https://eigen.tuxfamily.org/dox/unsupported/TensorBase_8h_source.html + EigenVector::Flatten(*bGrad).device(*(context.GetEigenDevice())) = + OutGrad.cumsum(1); // colwise add + } +}; } // namespace operators } // namespace paddle From 8ff3590eda2a6488f4b06f5ce6ffe553ae42d0a6 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Fri, 4 Aug 2017 01:15:56 +0800 Subject: [PATCH 004/138] fix op name --- paddle/operators/rowwise_add_op.cc | 20 ++++++++++---------- paddle/operators/rowwise_add_op.cu | 2 +- paddle/operators/rowwise_add_op.h | 6 +++--- 3 files changed, 14 insertions(+), 14 deletions(-) diff --git a/paddle/operators/rowwise_add_op.cc b/paddle/operators/rowwise_add_op.cc index cc763a8cf4..178ea3c614 100644 --- a/paddle/operators/rowwise_add_op.cc +++ b/paddle/operators/rowwise_add_op.cc @@ -16,7 +16,7 @@ namespace paddle { namespace operators { -class RowWiseAddOp : public OperatorWithKernel { +class RowwiseAddOp : public OperatorWithKernel { protected: void InferShape(const InferShapeContext &ctx) const override { PADDLE_ENFORCE(ctx.InputSize() == 2UL, @@ -32,9 +32,9 @@ protected: } }; -class RowWiseAddOpMaker : public OpProtoAndCheckerMaker { +class RowwiseAddOpMaker : public OpProtoAndCheckerMaker { public: - RowWiseAddOpMaker(OpProto *proto, OpAttrChecker *op_checker) + RowwiseAddOpMaker(OpProto *proto, OpAttrChecker *op_checker) : OpProtoAndCheckerMaker(proto, op_checker) { AddInput("X", "The left input of row-wise add op, must be matrix"); AddInput("b", "The right input of row-wise add op, must be vector"); @@ -46,13 +46,13 @@ for i in xrange(X.shape[0]): )DOC"); } }; -class RowWiseAddGradOp : public OperatorWithKernel { +class RowwiseAddGradOp : public OperatorWithKernel { protected: void InferShape(const InferShapeContext &ctx) const override { PADDLE_ENFORCE(ctx.InputSize() == 4UL, - "RowWiseAddGrad inputs is I, O, OG, size must be 4"); + "RowwiseAddGrad inputs is I, O, OG, size must be 4"); PADDLE_ENFORCE(ctx.OutputSize() == 2, - "RowWiseAddGrad output is IG, size must be 2"); + "RowwiseAddGrad output is IG, size must be 2"); ctx.Output(0)->Resize(ctx.Input(0)->dims()); ctx.Output(1)->Resize(ctx.Input(1)->dims()); } @@ -61,10 +61,10 @@ protected: } // namespace operators } // namespace paddle -REGISTER_OP(rowwise_add, ops::RowWiseAddOp, ops::RowWiseAddOpMaker); +REGISTER_OP(rowwise_add, ops::RowwiseAddOp, ops::RowwiseAddOpMaker); REGISTER_OP_CPU_KERNEL(rowwise_add, - ops::RowWiseAddKernel); + ops::RowwiseAddKernel); -REGISTER_GRADIENT_OP(rowwise_add, rowwise_add_grad, ops::RowWiseAddGradOp); +REGISTER_GRADIENT_OP(rowwise_add, rowwise_add_grad, ops::RowwiseAddGradOp); REGISTER_OP_CPU_KERNEL(rowwise_add_grad, - ops::RowWiseAddGradKernel); + ops::RowwiseAddGradKernel); diff --git a/paddle/operators/rowwise_add_op.cu b/paddle/operators/rowwise_add_op.cu index 4b33e38eba..f48dfeb6f2 100644 --- a/paddle/operators/rowwise_add_op.cu +++ b/paddle/operators/rowwise_add_op.cu @@ -1,4 +1,4 @@ #include "paddle/operators/rowwise_add_op.h" REGISTER_OP_GPU_KERNEL(rowwise_add, - ops::RowWiseAddKernel); + ops::RowwiseAddKernel); diff --git a/paddle/operators/rowwise_add_op.h b/paddle/operators/rowwise_add_op.h index 940459e0f1..321f51e61d 100644 --- a/paddle/operators/rowwise_add_op.h +++ b/paddle/operators/rowwise_add_op.h @@ -19,7 +19,7 @@ namespace paddle { namespace operators { template -class RowWiseAddKernel : public OpKernel { +class RowwiseAddKernel : public OpKernel { public: void Compute(const ExecutionContext& context) const override { auto out = context.Output(0); @@ -39,7 +39,7 @@ public: }; template -class RowWiseAddGradKernel : public OpKernel { +class RowwiseAddGradKernel : public OpKernel { public: void Compute(const ExecutionContext& context) const override { auto XGrad = context.Output(0); @@ -51,7 +51,7 @@ public: auto OutGrad = EigenMatrix::From(*context.Input(3)); EigenMatrix::From(*XGrad).device(*(context.GetEigenDevice())) = OutGrad; - // const int dimension = bGrad.dimension(0); + // https://eigen.tuxfamily.org/dox/unsupported/TensorBase_8h_source.html EigenVector::Flatten(*bGrad).device(*(context.GetEigenDevice())) = OutGrad.cumsum(1); // colwise add From 84627bb934ed6b4c7213eeebc0fe59e5fbe7a84b Mon Sep 17 00:00:00 2001 From: caoying03 Date: Mon, 7 Aug 2017 14:03:13 +0800 Subject: [PATCH 005/138] add config helper for sequence slice layer. --- doc/api/v2/config/layer.rst | 5 ++ python/paddle/trainer/config_parser.py | 45 +++++++++++ .../paddle/trainer_config_helpers/layers.py | 68 ++++++++++++++++ .../tests/configs/file_list.sh | 3 +- .../protostr/test_seq_slice_layer.protostr | 79 +++++++++++++++++++ .../tests/configs/test_seq_slice_layer.py | 13 +++ 6 files changed, 212 insertions(+), 1 deletion(-) create mode 100644 python/paddle/trainer_config_helpers/tests/configs/protostr/test_seq_slice_layer.protostr create mode 100644 python/paddle/trainer_config_helpers/tests/configs/test_seq_slice_layer.py diff --git a/doc/api/v2/config/layer.rst b/doc/api/v2/config/layer.rst index 372272a53c..232ea6b49b 100644 --- a/doc/api/v2/config/layer.rst +++ b/doc/api/v2/config/layer.rst @@ -257,6 +257,11 @@ seq_concat .. autoclass:: paddle.v2.layer.seq_concat :noindex: +seq_slice +--------- +.. autoclass:: paddle.v2.layer.seq_slice + :noindex: + Reshaping Layers ================ diff --git a/python/paddle/trainer/config_parser.py b/python/paddle/trainer/config_parser.py index 9ea69fc5e5..11e54ba420 100644 --- a/python/paddle/trainer/config_parser.py +++ b/python/paddle/trainer/config_parser.py @@ -2657,6 +2657,51 @@ class SubSequenceLayer(LayerBase): self.create_bias_parameter(bias, size) +@config_layer('seq_slice') +class SeqSliceLayer(LayerBase): + def __init__(self, name, inputs, starts, ends, bias=False, **xargs): + if isinstance(inputs, list): + assert len(inputs) == 1, ('the first input of sequence slice layer ' + 'is a single sequence input.') + else: + inputs = [inputs] + + if starts is not None: + if isinstance(starts, list): + assert len(starts) == 1, ( + 'the start indices for sequence slice layer cannot ' + 'be a list having more than one element.') + starts = starts[0] + inputs.append(starts) + + if ends is not None: + if isinstance(ends, list): + assert len(ends) == 1, ( + 'the end indices for sequence slice layer cannot ' + 'be a list having more than one element.') + ends = ends[0] + inputs.append(ends) + assert len(inputs) >= 2, ( + 'the sequence slice layer has at least two inputs.') + + super(SeqSliceLayer, self).__init__( + name, 'seq_slice', 0, inputs=inputs, **xargs) + input_layer0 = self.get_input_layer(0) + size = input_layer0.size + self.set_layer_size(size) + + if len(inputs) == 3: + assert ( + self.get_input_layer(1).size == self.get_input_layer(2).size), ( + 'If start and end indices are both given to' + 'sequence slice layer, they should have the same width.') + elif len(inputs) == 2: + if starts is not None: + self.config.select_first = True + else: + self.config.select_first = False + + @config_layer('out_prod') class OuterProdLayer(LayerBase): def __init__(self, name, inputs, device=None): diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py index ea5fdcc50f..15636b1442 100755 --- a/python/paddle/trainer_config_helpers/layers.py +++ b/python/paddle/trainer_config_helpers/layers.py @@ -131,6 +131,7 @@ __all__ = [ 'crop_layer', 'clip_layer', 'slice_projection', + 'seq_slice_layer', ] @@ -225,6 +226,7 @@ class LayerType(object): PRELU = 'prelu' CROP_LAYER = 'crop' CLIP_LAYER = 'clip' + SEQ_SLICE = 'seq_slice' @staticmethod def is_layer_type(type_name): @@ -6119,3 +6121,69 @@ def clip_layer(input, min, max, name=None): max=max) return LayerOutput( name, LayerType.CLIP_LAYER, parents=[input], size=input.size) + + +@wrap_name_default() +def seq_slice_layer(input, starts, ends, name=None): + """ + seq_slice_layer will return one or several sub-sequences from the + input sequence layer given start and end indices. + + - If only start indices are given, and end indices are set to None, + this layer slices the input sequence from the given start indices + to its end. + - If only end indices are given, and start indices are set to None, + this layer slices the input sequence from its beginning to the + given end indices. + - If start and end indices are both given, they should have the same + number of elements. + + If start or end indices contains more than one elements, the input sequence + will be sliced for multiple times. + + + .. code-block:: python + + seq_silce = seq_slice_layer(input=input_seq, + starts=start_pos, ends=end_pos) + + :param name: name of this layer. + :type name: basestring + :param input: input for this layer, it should be a sequence. + :type input: LayerOutput + :param starts: start indices to slice the input sequence. + :type starts: LayerOutput|None + :param ends: end indices to slice the input sequence. + :type ends: LayerOutput|None + :return: LayerOutput object. + :rtype: LayerOutput + + """ + + assert isinstance(input, LayerOutput), ( + 'The first input of seq_slice layer must be a PaddlePaddle layer.') + + if starts is not None: + assert isinstance(starts, LayerOutput), ( + 'The start indices for seq_slice layer ' + 'must be a PaddlePaddle layer.') + if ends is not None: + assert isinstance(ends, LayerOutput), ( + 'The end indices for seq_slice layer must be a PaddlePaddle layer.') + assert starts is not None or ends is not None, ( + 'start and end indices ' + 'cannot be set to None at the same time, at least one of ' + 'them should be given.') + if starts is not None and ends is not None: + assert starts.size == ends.size, ( + 'If start and end indices are both given to seq_slice_layer, ' + 'they should have the same width.') + + Layer( + name=name, + type=LayerType.SEQ_SLICE, + inputs=input.name, + starts=starts.name if starts is not None else None, + ends=ends.name if ends is not None else None) + return LayerOutput( + name, LayerType.SEQ_SLICE, parents=[input], size=input.size) diff --git a/python/paddle/trainer_config_helpers/tests/configs/file_list.sh b/python/paddle/trainer_config_helpers/tests/configs/file_list.sh index 0ffa58bc1e..1ce865ceac 100755 --- a/python/paddle/trainer_config_helpers/tests/configs/file_list.sh +++ b/python/paddle/trainer_config_helpers/tests/configs/file_list.sh @@ -7,6 +7,7 @@ test_rnn_group shared_fc shared_lstm shared_gru test_cost_layers_with_weight test_spp_layer test_bilinear_interp test_maxout test_bi_grumemory math_ops test_seq_concat_reshape test_pad test_smooth_l1 test_multiplex_layer test_prelu_layer test_row_conv test_detection_output_layer test_multibox_loss_layer -test_recursive_topology test_gated_unit_layer test_clip_layer test_row_l2_norm_layer) +test_recursive_topology test_gated_unit_layer test_clip_layer test_row_l2_norm_layer +test_seq_slice_layer) export whole_configs=(test_split_datasource) diff --git a/python/paddle/trainer_config_helpers/tests/configs/protostr/test_seq_slice_layer.protostr b/python/paddle/trainer_config_helpers/tests/configs/protostr/test_seq_slice_layer.protostr new file mode 100644 index 0000000000..5b73d614fe --- /dev/null +++ b/python/paddle/trainer_config_helpers/tests/configs/protostr/test_seq_slice_layer.protostr @@ -0,0 +1,79 @@ +type: "nn" +layers { + name: "word" + type: "data" + size: 128 + active_type: "" +} +layers { + name: "starts" + type: "data" + size: 5 + active_type: "" +} +layers { + name: "ends" + type: "data" + size: 5 + active_type: "" +} +layers { + name: "__seq_slice_layer_0__" + type: "seq_slice" + size: 128 + active_type: "" + inputs { + input_layer_name: "word" + } + inputs { + input_layer_name: "starts" + } + inputs { + input_layer_name: "ends" + } +} +layers { + name: "__seq_slice_layer_1__" + type: "seq_slice" + size: 128 + active_type: "" + inputs { + input_layer_name: "word" + } + inputs { + input_layer_name: "starts" + } + select_first: true +} +layers { + name: "__seq_slice_layer_2__" + type: "seq_slice" + size: 128 + active_type: "" + inputs { + input_layer_name: "word" + } + inputs { + input_layer_name: "ends" + } + select_first: false +} +input_layer_names: "word" +output_layer_names: "__seq_slice_layer_0__" +output_layer_names: "__seq_slice_layer_1__" +output_layer_names: "__seq_slice_layer_2__" +sub_models { + name: "root" + layer_names: "word" + layer_names: "starts" + layer_names: "ends" + layer_names: "__seq_slice_layer_0__" + layer_names: "__seq_slice_layer_1__" + layer_names: "__seq_slice_layer_2__" + input_layer_names: "word" + output_layer_names: "__seq_slice_layer_0__" + output_layer_names: "__seq_slice_layer_1__" + output_layer_names: "__seq_slice_layer_2__" + is_recurrent_layer_group: false +} + diff --git a/python/paddle/trainer_config_helpers/tests/configs/test_seq_slice_layer.py b/python/paddle/trainer_config_helpers/tests/configs/test_seq_slice_layer.py new file mode 100644 index 0000000000..510ad32208 --- /dev/null +++ b/python/paddle/trainer_config_helpers/tests/configs/test_seq_slice_layer.py @@ -0,0 +1,13 @@ +#!/usr/bin/env python +#coding=utf-8 +from paddle.trainer_config_helpers import * + +input_seq = data_layer("word", size=128) +starts = data_layer("starts", size=5) +ends = data_layer("ends", size=5) + +seq_slice1 = seq_slice_layer(input=input_seq, starts=starts, ends=ends) +seq_slice2 = seq_slice_layer(input=input_seq, starts=starts, ends=None) +seq_slice3 = seq_slice_layer(input=input_seq, starts=None, ends=ends) + +outputs(seq_slice1, seq_slice2, seq_slice3) From 2988a58ef01a56e84cff02463972e0150bc6ab13 Mon Sep 17 00:00:00 2001 From: caoying03 Date: Tue, 8 Aug 2017 08:52:05 +0800 Subject: [PATCH 006/138] add unittest. --- paddle/gserver/tests/CMakeLists.txt | 6 + .../gserver/tests/test_SeqSliceLayerGrad.cpp | 214 ++++++++++++++++++ 2 files changed, 220 insertions(+) create mode 100644 paddle/gserver/tests/test_SeqSliceLayerGrad.cpp diff --git a/paddle/gserver/tests/CMakeLists.txt b/paddle/gserver/tests/CMakeLists.txt index 4546d12a90..9fdb148864 100644 --- a/paddle/gserver/tests/CMakeLists.txt +++ b/paddle/gserver/tests/CMakeLists.txt @@ -30,6 +30,12 @@ add_unittest_without_exec(test_CRFLayerGrad add_test(NAME test_CRFLayerGrad COMMAND test_CRFLayerGrad) +################ test_SeqSliceLayerGrad #################### +add_unittest_without_exec(test_SeqSliceLayerGrad + test_SeqSliceLayerGrad.cpp + LayerGradUtil.cpp) +add_test(NAME test_SeqSliceLayerGrad + COMMAND test_SeqSliceLayerGrad) add_unittest_without_exec(test_ActivationGrad test_ActivationGrad.cpp diff --git a/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp b/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp new file mode 100644 index 0000000000..e456dd5db7 --- /dev/null +++ b/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp @@ -0,0 +1,214 @@ +/* Copyright (c) 2016 Baidu, Inc. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include +#include "ModelConfig.pb.h" +#include "paddle/gserver/layers/DataLayer.h" +#include "paddle/trainer/Trainer.h" + +#include "LayerGradUtil.h" +#include "paddle/testing/TestUtil.h" + +using namespace paddle; // NOLINT +using namespace std; // NOLINT + +DECLARE_int32(gpu_id); +DECLARE_bool(thread_local_rand_use_global_seed); + +const int MAX_SEQ_NUM = 5; +const int MAX_SEQ_LEN = 5; +const int MAX_BEAM_SIZE = 3; + +vector randSampling(real range, int n) { + CHECK_GE(range, n); + vector num(range); + iota(begin(num), end(num), 0.); + if (range == n) return num; + + random_shuffle(begin(num), end(num)); + num.resize(n); + sort(begin(num), end(num)); + return num; +} + +void genSeqInfo(vector& seqStartPos, vector& subSeqStartPos) { + seqStartPos.resize(1, 0); + subSeqStartPos.resize(1, 0); + + // srand((size_t)(time(NULL))); + srand(1); + int seqNum = 1 + (rand() % MAX_SEQ_NUM); + for (int i = 0; i < seqNum; ++i) { + int subSeqNum = 1 + (rand() % MAX_SEQ_NUM); + for (int j = 0; j < subSeqNum; ++j) + subSeqStartPos.push_back(subSeqStartPos.back() + + (1 + (rand() % MAX_SEQ_LEN))); + seqStartPos.push_back(subSeqStartPos.back()); + } +} + +/* + generate start indices according to sequence start positions. + */ +void genStarts(vector& seqStartPos, + vector>& starts, + size_t beamSize) { + starts.clear(); + starts.resize(seqStartPos.size() - 1, vector(beamSize, -1.)); + + for (size_t i = 0; i < seqStartPos.size() - 1; ++i) { + int seqLen = seqStartPos[i + 1] - seqStartPos[i]; + vector randStarts = + randSampling(seqLen, min(seqLen, static_cast(beamSize))); + copy(begin(randStarts), end(randStarts), begin(starts[i])); + } +} + +/* + generate end indices according to sequence start positions and start indices. + */ +void genEnds(vector& seqStartPos, + vector>& starts, + vector>& ends, + size_t beamSize) { + CHECK_EQ(seqStartPos.size() - 1, starts.size()); + ends.clear(); + ends.resize(seqStartPos.size() - 1, vector(beamSize, -1.)); + + for (size_t i = 0; i < starts.size(); ++i) { + for (size_t j = 0; j < starts[i].size(); ++j) { + int seqLen = seqStartPos[i + 1] - seqStartPos[i]; + CHECK_GE(seqLen - 1, starts[i][j]); + if (starts[i][j] == -1.) break; + if (starts[i][j] == (seqLen - 1)) { + ends[i][j] = starts[i][j]; + } else { + ends[i][j] = starts[i][j] + randSampling(seqLen - starts[i][j], 1)[0]; + } + } + } +} + +void genTestData(vector& seqStartPos, + vector& subSeqStartPos, + vector>& starts, + vector>& ends, + bool hasSubseq) { + size_t beamSize = MAX_BEAM_SIZE; + genSeqInfo(seqStartPos, subSeqStartPos); + + genStarts(hasSubseq ? subSeqStartPos : seqStartPos, starts, beamSize); + genEnds(hasSubseq ? subSeqStartPos : seqStartPos, starts, ends, beamSize); +} + +template +void flatten2dVector(vector>& inVec, vector& outVec) { + size_t totalSize{0}; + for (auto const& items : inVec) totalSize += items.size(); + outVec.reserve(totalSize); + + for (auto& items : inVec) + move(items.begin(), items.end(), back_inserter(outVec)); +} + +void testSeqSliceLayer(bool hasSubseq, + bool useGpu, + vector& seqStartPos, + vector& subSeqStartPos, + vector>& starts, + vector>& ends) { + // layer size is not crutial for this layer, + // so here use a small layer size in the unittest. + const size_t layerSize{4}; + TestConfig config; + config.layerConfig.set_type("seq_slice"); + config.layerConfig.set_size(layerSize); + + // add the first input + MatrixPtr seqInputPtr = + Matrix::create(hasSubseq ? subSeqStartPos.back() : seqStartPos.back(), + layerSize, + false, + false); + seqInputPtr->randomizeUniform(); + + if (hasSubseq) { + config.inputDefs.push_back({INPUT_SELF_DEFINE_DATA, + "seq_input", + seqInputPtr, + seqStartPos, + subSeqStartPos}); + } else { + config.inputDefs.push_back( + {INPUT_SELF_DEFINE_DATA, "seq_input", seqInputPtr, seqStartPos}); + } + config.layerConfig.add_inputs(); + + // add start indices + if (starts.size()) { + vector startsToVec; + flatten2dVector(starts, startsToVec); + + MatrixPtr startMatrixPtr = + Matrix::create(starts.size(), starts[0].size(), false, false); + startMatrixPtr->copyFrom(startsToVec.data(), startsToVec.size()); + + config.inputDefs.push_back( + {INPUT_SELF_DEFINE_DATA, "starts", startMatrixPtr}); + config.layerConfig.add_inputs(); + } + + // add end indices + if (ends.size()) { + vector endsToVec; + flatten2dVector(ends, endsToVec); + MatrixPtr endMatrixPtr = + Matrix::create(ends.size(), ends[0].size(), false, false); + config.inputDefs.push_back({INPUT_SELF_DEFINE_DATA, "ends", endMatrixPtr}); + config.layerConfig.add_inputs(); + } + + testLayerGrad(config, "seq_slice", /*batchSize*/ 100, false, useGpu, false); +} + +TEST(Layer, SeqSliceLayer) { + vector seqStartPos; + vector subSeqStartPos; + vector> starts; + vector> ends; + + genSeqInfo(seqStartPos, subSeqStartPos); + for (bool hasSubseq : {false, true}) { + genTestData(seqStartPos, subSeqStartPos, starts, ends, hasSubseq); + for (bool useGpu : {false, true}) { + vector> tmp; + testSeqSliceLayer( + hasSubseq, useGpu, seqStartPos, subSeqStartPos, tmp, ends); + testSeqSliceLayer( + hasSubseq, useGpu, seqStartPos, subSeqStartPos, starts, tmp); + testSeqSliceLayer( + hasSubseq, useGpu, seqStartPos, subSeqStartPos, starts, ends); + } + } +} + +int main(int argc, char** argv) { + initMain(argc, argv); + hl_start(); + hl_init(FLAGS_gpu_id); + FLAGS_thread_local_rand_use_global_seed = true; + srand(1); + testing::InitGoogleTest(&argc, argv); + return RUN_ALL_TESTS(); +} From b7ee1e7d9c7f01844b23c54a3c5a2584e0a6a410 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Wed, 9 Aug 2017 00:12:09 +0800 Subject: [PATCH 007/138] "backward check todo" --- paddle/operators/rowwise_add_op.h | 8 ++++---- python/paddle/v2/framework/tests/test_rowwise_add_op.py | 2 ++ 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/paddle/operators/rowwise_add_op.h b/paddle/operators/rowwise_add_op.h index 06af88a993..965c0df532 100644 --- a/paddle/operators/rowwise_add_op.h +++ b/paddle/operators/rowwise_add_op.h @@ -42,18 +42,18 @@ template class RowwiseAddGradKernel : public OpKernel { public: void Compute(const ExecutionContext& context) const override { - auto XGrad = context.Output(0); - auto bGrad = context.Output(1); + auto* XGrad = context.Output(0); + auto* bGrad = context.Output(1); XGrad->mutable_data(context.GetPlace()); bGrad->mutable_data(context.GetPlace()); // I, O, OG => [X, b], [Out], [OutGrad] auto OutGrad = EigenMatrix::From(*context.Input(3)); - EigenMatrix::From(*XGrad).device(*(context.GetEigenDevice())) = + EigenMatrix::From(*XGrad).device(context.GetEigenDevice()) = OutGrad; // https://eigen.tuxfamily.org/dox/unsupported/TensorBase_8h_source.html - EigenVector::Flatten(*bGrad).device(*(context.GetEigenDevice())) = + EigenVector::Flatten(*bGrad).device(context.GetEigenDevice()) = OutGrad.cumsum(1); // colwise add } }; diff --git a/python/paddle/v2/framework/tests/test_rowwise_add_op.py b/python/paddle/v2/framework/tests/test_rowwise_add_op.py index f8521eb517..e957dd6b3f 100644 --- a/python/paddle/v2/framework/tests/test_rowwise_add_op.py +++ b/python/paddle/v2/framework/tests/test_rowwise_add_op.py @@ -15,5 +15,7 @@ class TestRowwiseAddOp(unittest.TestCase): self.outputs = {'Out': np.add(self.inputs['X'], self.inputs['b'])} +#TODO(dzh): rowwise_grad check + if __name__ == '__main__': unittest.main() From 200e3e2c6b7b3c1be47204f0e76ab79696f46efb Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Wed, 9 Aug 2017 10:14:20 +0800 Subject: [PATCH 008/138] "change namespace prefix" --- paddle/operators/rowwise_add_op.cc | 6 +++--- paddle/operators/rowwise_add_op.h | 2 +- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/paddle/operators/rowwise_add_op.cc b/paddle/operators/rowwise_add_op.cc index c192da04da..a012ab0be0 100644 --- a/paddle/operators/rowwise_add_op.cc +++ b/paddle/operators/rowwise_add_op.cc @@ -35,7 +35,7 @@ class RowwiseAddOp : public framework::OperatorWithKernel { class RowwiseAddOpMaker : public framework::OpProtoAndCheckerMaker { public: - RowWiseAddOpMaker(framework::OpProto *proto, + RowwiseAddOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker) : OpProtoAndCheckerMaker(proto, op_checker) { AddInput("X", "The left input of row-wise add op, must be matrix"); @@ -48,9 +48,9 @@ for i in xrange(X.shape[0]): )DOC"); } }; -class RowwiseAddGradOp : public OperatorWithKernel { +class RowwiseAddGradOp : public framework::OperatorWithKernel { protected: - void InferShape(const InferShapeContext &ctx) const override { + void InferShape(const framework::InferShapeContext &ctx) const override { PADDLE_ENFORCE(ctx.InputSize() == 4UL, "RowwiseAddGrad inputs is I, O, OG, size must be 4"); PADDLE_ENFORCE(ctx.OutputSize() == 2, diff --git a/paddle/operators/rowwise_add_op.h b/paddle/operators/rowwise_add_op.h index ad43e753e4..27d7a33e8a 100644 --- a/paddle/operators/rowwise_add_op.h +++ b/paddle/operators/rowwise_add_op.h @@ -28,7 +28,7 @@ template ; template -class RowwiseAddKernel : public OpKernel { +class RowwiseAddKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { auto out = context.Output(0); From 68bfc3ff963474e12c8af1c3575128b0acac90ed Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Wed, 9 Aug 2017 21:02:51 +0800 Subject: [PATCH 009/138] "add python test" --- .../v2/framework/tests/test_rowwise_add_op.py | 13 ++++++++++++- 1 file changed, 12 insertions(+), 1 deletion(-) diff --git a/python/paddle/v2/framework/tests/test_rowwise_add_op.py b/python/paddle/v2/framework/tests/test_rowwise_add_op.py index e957dd6b3f..1b27f54f15 100644 --- a/python/paddle/v2/framework/tests/test_rowwise_add_op.py +++ b/python/paddle/v2/framework/tests/test_rowwise_add_op.py @@ -1,6 +1,7 @@ import unittest -from op_test_util import OpTestMeta import numpy as np +from op_test_util import OpTestMeta +from gradient_checker import GradientChecker, create_op class TestRowwiseAddOp(unittest.TestCase): @@ -15,6 +16,16 @@ class TestRowwiseAddOp(unittest.TestCase): self.outputs = {'Out': np.add(self.inputs['X'], self.inputs['b'])} +class RowwiseAddGradOpTest(GradientChecker): + def test_rowwise_add(self): + op = create_op("rowwise_add") + inputs = { + "X": np.random.uniform(0.1, 1, [10, 10]).astype("float32"), + "b": np.random.uniform(0.1, 1, [10, 1]).astype("float32") + } + self.check_grad(op, inputs, set("X", "b"), "Out") + + #TODO(dzh): rowwise_grad check if __name__ == '__main__': From 26bc5b12596c945956f7a6b003712805e579a36d Mon Sep 17 00:00:00 2001 From: caoying03 Date: Tue, 8 Aug 2017 18:48:11 +0800 Subject: [PATCH 010/138] add implementations. --- paddle/gserver/layers/KmaxSeqScoreLayer.cpp | 5 + paddle/gserver/layers/SequenceSliceLayer.cpp | 228 ++++++++++++++++++ .../gserver/layers/SubNestedSequenceLayer.cpp | 16 +- .../gserver/tests/test_SeqSliceLayerGrad.cpp | 25 +- paddle/parameter/Argument.cpp | 27 ++- 5 files changed, 278 insertions(+), 23 deletions(-) create mode 100644 paddle/gserver/layers/SequenceSliceLayer.cpp diff --git a/paddle/gserver/layers/KmaxSeqScoreLayer.cpp b/paddle/gserver/layers/KmaxSeqScoreLayer.cpp index 8ce591d476..e96fd61fc1 100644 --- a/paddle/gserver/layers/KmaxSeqScoreLayer.cpp +++ b/paddle/gserver/layers/KmaxSeqScoreLayer.cpp @@ -97,6 +97,11 @@ void KmaxSeqScoreLayer::forward(PassType passType) { scores_ = inputScore; } + // TODO(caoying) + // Here selSubSeqIdx is automatically converted from real to int + // This is very dangerous if user fill this matrix himself, invalid data may + // occur. The selected indices should be stored in + // CpuSparseMatrix with SparseValueType set to NO_VALUE. Matrix::resizeOrCreate( output_.value, input.hasSubseq() ? input.getNumSubSequences() : input.getNumSequences(), diff --git a/paddle/gserver/layers/SequenceSliceLayer.cpp b/paddle/gserver/layers/SequenceSliceLayer.cpp new file mode 100644 index 0000000000..410aba663e --- /dev/null +++ b/paddle/gserver/layers/SequenceSliceLayer.cpp @@ -0,0 +1,228 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "Layer.h" +#include "paddle/math/Matrix.h" +#include "paddle/math/Vector.h" +#include "paddle/utils/Logging.h" +#include "paddle/utils/Stat.h" + +namespace paddle { + +class SequenceSliceLayer : public Layer { +public: + explicit SequenceSliceLayer(const LayerConfig& config) : Layer(config) {} + + bool init(const LayerMap& layerMap, + const ParameterMap& parameterMap) override; + + void forward(PassType passType) override; + void backward(const UpdateCallback& callback = nullptr) override; + +private: + // TODO(caoying) + // Here selSubSeqIdx is automatically converted from real to int + // This is very dangerous if user fill this matrix himself, invalid data + // may occur. The selected indices should be stored in CpuSparseMatrix + // with SparseValueType set to NO_VALUE. + MatrixPtr startIdsOnCpu_; + MatrixPtr endIdsOnCpu_; + + std::vector selectedRows_; + IVectorPtr rowIndice_; + std::vector> inputSeqInfoVec_; + std::vector outSubSeqStartPos_; + std::vector outSeqStartPos_; + + void checkInputs(); + void copySliceIdsToCpu(); + void calSelectedRows(const MatrixPtr starts, const MatrixPtr ends); +}; + +REGISTER_LAYER(seq_slice, SequenceSliceLayer); + +bool SequenceSliceLayer::init(const LayerMap& layerMap, + const ParameterMap& parameterMap) { + /* Initialize the basic parent class */ + Layer::init(layerMap, parameterMap); + CHECK_GE(inputLayers_.size(), 2U); + CHECK_LE(inputLayers_.size(), 3U); + + setNeedSequenceInfo(false); + return true; +} + +void SequenceSliceLayer::checkInputs() { + const Argument& inputSeq = getInput(0); + CHECK(inputSeq.hasSeq()) << "The first input of sequence slic layer " + << "must be a sequence."; + // Check inputs + const MatrixPtr indices1 = getInputValue(1); + CHECK_EQ(indices1->getHeight(), + inputSeq.hasSubseq() ? inputSeq.getNumSubSequences() + : inputSeq.getNumSequences()) + << "Height of the second input should be equal to number of sequence " + << "in the first input."; + if (inputLayers_.size() == 3) { + const MatrixPtr indices2 = getInputValue(2); + CHECK_EQ(indices2->getHeight(), indices1->getHeight()) + << "start indices and end indices should have the same height."; + CHECK_EQ(indices2->getWidth(), indices1->getWidth()) + << "start indices and end indices should have the same Width."; + } +} + +void SequenceSliceLayer::copySliceIdsToCpu() { + if (!useGpu_) { + if (inputLayers_.size() == 2U) { + if (config_.select_first()) { + startIdsOnCpu_ = getInputValue(1); + endIdsOnCpu_ = nullptr; + } else { + startIdsOnCpu_ = nullptr; + endIdsOnCpu_ = getInputValue(1); + } + } else if (inputLayers_.size() == 3U) { + startIdsOnCpu_ = getInputValue(1); + endIdsOnCpu_ = getInputValue(2); + } + return; + } + + const MatrixPtr indices1 = getInputValue(1); + if (inputLayers_.size() == 2U) { + if (config_.select_first()) { + Matrix::resizeOrCreate(startIdsOnCpu_, + indices1->getHeight(), + indices1->getWidth(), + false /* trans */, + false /* useGpu */); + startIdsOnCpu_->copyFrom(*indices1); + endIdsOnCpu_ = nullptr; + } else { + Matrix::resizeOrCreate(endIdsOnCpu_, + indices1->getHeight(), + indices1->getWidth(), + false /* trans */, + false /* useGpu */); + endIdsOnCpu_->copyFrom(*indices1); + startIdsOnCpu_ = nullptr; + } + } else if (inputLayers_.size() == 3U) { + Matrix::resizeOrCreate(startIdsOnCpu_, + indices1->getHeight(), + indices1->getWidth(), + false /* trans */, + false /* useGpu */); + startIdsOnCpu_->copyFrom(*indices1); + + const MatrixPtr indices2 = getInputValue(2); + Matrix::resizeOrCreate(endIdsOnCpu_, + indices2->getHeight(), + indices2->getWidth(), + false /* trans */, + false /* useGpu */); + endIdsOnCpu_->copyFrom(*indices2); + } +} + +void SequenceSliceLayer::calSelectedRows(const MatrixPtr starts, + const MatrixPtr ends) { + outSeqStartPos_.resize(1, 0); + outSubSeqStartPos_.resize(1, 0); + selectedRows_.clear(); + + size_t beamSize = starts ? starts->getWidth() : ends->getWidth(); + // iterate over sequence + size_t rowIdx = 0; + for (size_t i = 0; i < inputSeqInfoVec_.size(); ++i) { + // iterate over sub-sequence in a sequence + for (size_t j = 0; j < inputSeqInfoVec_[i].size() - 1; ++j) { + // iterate over each index for slicing. + for (size_t k = 0; k < beamSize; ++k) { + if (starts) { + if (starts->getElement(rowIdx, k) == -1.) break; + } else if (ends->getElement(rowIdx, k) == -1.) + break; + + int begPos = inputSeqInfoVec_[i][j]; + if (starts) begPos += starts->getElement(rowIdx, k); + + int endPos = inputSeqInfoVec_[i][j + 1] - 1; + if (ends) endPos = inputSeqInfoVec_[i][j] + ends->getElement(rowIdx, k); + + int seqLen = endPos - begPos + 1; + CHECK(seqLen); + for (int m = begPos; m <= endPos; ++m) selectedRows_.push_back(m); + inputSeqInfoVec_.size() > 1 + ? outSubSeqStartPos_.push_back(outSubSeqStartPos_.back() + seqLen) + : outSeqStartPos_.push_back(outSeqStartPos_.back() + seqLen); + } + rowIdx++; + } + if (inputSeqInfoVec_.size() > 1) + outSeqStartPos_.push_back(outSubSeqStartPos_.back()); + } + + if (useGpu_) { + rowIndice_ = IVector::create(selectedRows_.size(), useGpu_); + rowIndice_->copyFrom(selectedRows_.data(), selectedRows_.size()); + } else { + rowIndice_ = + IVector::create(selectedRows_.data(), selectedRows_.size(), useGpu_); + } + + // create the sequence information for the output. + ICpuGpuVector::resizeOrCreate( + output_.sequenceStartPositions, outSeqStartPos_.size(), false); + output_.sequenceStartPositions->copyFrom( + outSeqStartPos_.data(), outSeqStartPos_.size(), false); + + if (inputSeqInfoVec_.size() > 1) { + ICpuGpuVector::resizeOrCreate( + output_.subSequenceStartPositions, outSubSeqStartPos_.size(), false); + output_.subSequenceStartPositions->copyFrom( + outSubSeqStartPos_.data(), outSubSeqStartPos_.size(), false); + } +} + +void SequenceSliceLayer::forward(PassType passType) { + Layer::forward(passType); + checkInputs(); + + const Argument& inputSeq = getInput(0); + inputSeqInfoVec_.clear(); + Argument::reorganizeSeqInfo(inputSeq.sequenceStartPositions, + inputSeq.subSequenceStartPositions, + inputSeqInfoVec_); + copySliceIdsToCpu(); + + // calculate the selected row indices in a batch, + // and build the output sequence information. + calSelectedRows(startIdsOnCpu_ ? startIdsOnCpu_ : nullptr, + endIdsOnCpu_ ? endIdsOnCpu_ : nullptr); + + resetOutput(selectedRows_.size(), getSize()); + + getOutputValue()->selectRows(*getInputValue(0), *rowIndice_); +} + +void SequenceSliceLayer::backward(const UpdateCallback& callback) { + MatrixPtr inputSeqGrad = getInputGrad(0); + MatrixPtr outputGrad = getOutputGrad(); + + outputGrad->addToRows(*inputSeqGrad, *rowIndice_); +} + +} // namespace paddle diff --git a/paddle/gserver/layers/SubNestedSequenceLayer.cpp b/paddle/gserver/layers/SubNestedSequenceLayer.cpp index 76f587fff7..0db0300270 100644 --- a/paddle/gserver/layers/SubNestedSequenceLayer.cpp +++ b/paddle/gserver/layers/SubNestedSequenceLayer.cpp @@ -52,11 +52,10 @@ private: * ] * * ths output is saved to private member rowIndice_; - * [0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15, - * 16,17,18,19,20,21,22,23,24,25,26,27] + * [0,1,2,3,4,5,6,7,8,9,15,16,17,18,19,20,21,23,24,25,26,27] */ - void calSelectedCols(const MatrixPtr selectedIndices, + void calSelectedRows(const MatrixPtr selectedIndices, const std::vector>& inputSeqInfo); // if the second input of this layer is on GPU memory, copy it to CPU memory. @@ -67,7 +66,7 @@ private: std::vector> inputSeqInfoVec_; // the final selected row indices in a batch, - // rowIdx_ and selectedRows_ actually share a same memory. + // rowIndice_ and selectedRows_ actually share a same memory. IVectorPtr rowIndice_; std::vector selectedRows_; }; @@ -83,7 +82,7 @@ bool SubNestedSequenceLayer::init(const LayerMap& layerMap, return true; } -void SubNestedSequenceLayer::calSelectedCols( +void SubNestedSequenceLayer::calSelectedRows( const MatrixPtr selectedIndices, const std::vector>& inputSeqInfo) { selectedRows_.clear(); @@ -96,6 +95,11 @@ void SubNestedSequenceLayer::calSelectedCols( for (size_t i = 0; i < seqNum; ++i) { for (size_t j = 0; j < beamSize; ++j) { if (selectedIndices->getElement(i, j) == -1.) break; + // TODO(caoying) + // Here selSubSeqIdx is automatically converted from real to int + // This is very dangerous if user fill this matrix himself, invalid data + // may occur. The selected indices should be stored in + // CpuSparseMatrix with SparseValueType set to NO_VALUE. int selSubSeqIdx = selectedIndices->getElement(i, j); CHECK_GT(inputSeqInfoVec_[i].size() - 1, selSubSeqIdx); @@ -160,7 +164,7 @@ void SubNestedSequenceLayer::forward(PassType passType) { Argument::reorganizeSeqInfo(inputSeq.sequenceStartPositions, inputSeq.subSequenceStartPositions, inputSeqInfoVec_); - calSelectedCols(selIdsCpu_, inputSeqInfoVec_); + calSelectedRows(selIdsCpu_, inputSeqInfoVec_); resetOutput(selectedRows_.size(), getSize()); getOutputValue()->selectRows(*getInputValue(0), *rowIndice_); diff --git a/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp b/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp index e456dd5db7..d560ca650b 100644 --- a/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp +++ b/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp @@ -26,9 +26,9 @@ using namespace std; // NOLINT DECLARE_int32(gpu_id); DECLARE_bool(thread_local_rand_use_global_seed); -const int MAX_SEQ_NUM = 5; -const int MAX_SEQ_LEN = 5; -const int MAX_BEAM_SIZE = 3; +const int MAX_SEQ_NUM = 17; +const int MAX_SEQ_LEN = 23; +const int MAX_BEAM_SIZE = 13; vector randSampling(real range, int n) { CHECK_GE(range, n); @@ -46,8 +46,7 @@ void genSeqInfo(vector& seqStartPos, vector& subSeqStartPos) { seqStartPos.resize(1, 0); subSeqStartPos.resize(1, 0); - // srand((size_t)(time(NULL))); - srand(1); + srand((size_t)(time(NULL))); int seqNum = 1 + (rand() % MAX_SEQ_NUM); for (int i = 0; i < seqNum; ++i) { int subSeqNum = 1 + (rand() % MAX_SEQ_NUM); @@ -105,7 +104,7 @@ void genTestData(vector& seqStartPos, vector>& starts, vector>& ends, bool hasSubseq) { - size_t beamSize = MAX_BEAM_SIZE; + size_t beamSize = 1 + (rand() % MAX_BEAM_SIZE); genSeqInfo(seqStartPos, subSeqStartPos); genStarts(hasSubseq ? subSeqStartPos : seqStartPos, starts, beamSize); @@ -167,16 +166,21 @@ void testSeqSliceLayer(bool hasSubseq, config.inputDefs.push_back( {INPUT_SELF_DEFINE_DATA, "starts", startMatrixPtr}); config.layerConfig.add_inputs(); + config.layerConfig.set_select_first(true); } // add end indices if (ends.size()) { vector endsToVec; flatten2dVector(ends, endsToVec); + MatrixPtr endMatrixPtr = Matrix::create(ends.size(), ends[0].size(), false, false); + endMatrixPtr->copyFrom(endsToVec.data(), endsToVec.size()); + config.inputDefs.push_back({INPUT_SELF_DEFINE_DATA, "ends", endMatrixPtr}); config.layerConfig.add_inputs(); + config.layerConfig.set_select_first(false); } testLayerGrad(config, "seq_slice", /*batchSize*/ 100, false, useGpu, false); @@ -188,10 +192,15 @@ TEST(Layer, SeqSliceLayer) { vector> starts; vector> ends; + std::vector mode = {false}; +#ifndef PADDLE_ONLY_CPU + mode.push_back(true); +#endif genSeqInfo(seqStartPos, subSeqStartPos); - for (bool hasSubseq : {false, true}) { + for (bool hasSubseq : {true, false}) { + LOG(INFO) << "hasSubSeq : " << hasSubseq; genTestData(seqStartPos, subSeqStartPos, starts, ends, hasSubseq); - for (bool useGpu : {false, true}) { + for (bool useGpu : mode) { vector> tmp; testSeqSliceLayer( hasSubseq, useGpu, seqStartPos, subSeqStartPos, tmp, ends); diff --git a/paddle/parameter/Argument.cpp b/paddle/parameter/Argument.cpp index 0547ac93cd..06f7e5245f 100644 --- a/paddle/parameter/Argument.cpp +++ b/paddle/parameter/Argument.cpp @@ -670,19 +670,28 @@ void Argument::reorganizeSeqInfo( const ICpuGpuVectorPtr seqStartPos, const ICpuGpuVectorPtr subSeqStartPos, std::vector>& reorganizedSeqInfo) { - int* seqStarts = seqStartPos->getMutableData(false); - int* subSeqStarts = subSeqStartPos->getMutableData(false); + CHECK(seqStartPos); int seqNum = seqStartPos->getSize() - 1; - reorganizedSeqInfo.resize(seqNum, std::vector()); - int seqIdx = 0; - for (size_t i = 0; i < subSeqStartPos->getSize(); ++i) { - reorganizedSeqInfo[seqIdx].push_back(subSeqStarts[i]); - if (subSeqStarts[i] == seqStarts[seqIdx + 1]) { - seqIdx++; - if (seqIdx == seqNum) return; + int* seqStarts = seqStartPos->getMutableData(false); + + if (subSeqStartPos) { + int* subSeqStarts = subSeqStartPos->getMutableData(false); + reorganizedSeqInfo.resize(seqNum, std::vector()); + int seqIdx = 0; + for (size_t i = 0; i < subSeqStartPos->getSize(); ++i) { reorganizedSeqInfo[seqIdx].push_back(subSeqStarts[i]); + if (subSeqStarts[i] == seqStarts[seqIdx + 1]) { + seqIdx++; + if (seqIdx == seqNum) return; + reorganizedSeqInfo[seqIdx].push_back(subSeqStarts[i]); + } } + } else { + reorganizedSeqInfo.resize(1, std::vector(seqNum + 1, 0)); + memcpy(reorganizedSeqInfo[0].data(), + seqStarts, + sizeof(int) * seqStartPos->getSize()); } } From 7c0cb0c7901093e7b2aa57100f086f737ab39739 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Wed, 9 Aug 2017 23:51:46 +0800 Subject: [PATCH 011/138] "fix ci launch" --- python/paddle/v2/framework/tests/test_rowwise_add_op.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/python/paddle/v2/framework/tests/test_rowwise_add_op.py b/python/paddle/v2/framework/tests/test_rowwise_add_op.py index 1b27f54f15..8118d2d741 100644 --- a/python/paddle/v2/framework/tests/test_rowwise_add_op.py +++ b/python/paddle/v2/framework/tests/test_rowwise_add_op.py @@ -23,7 +23,7 @@ class RowwiseAddGradOpTest(GradientChecker): "X": np.random.uniform(0.1, 1, [10, 10]).astype("float32"), "b": np.random.uniform(0.1, 1, [10, 1]).astype("float32") } - self.check_grad(op, inputs, set("X", "b"), "Out") + self.check_grad(op, inputs, set(["X", "b"]), "Out") #TODO(dzh): rowwise_grad check From 2ddb11222adef0545a2691d73281516026b9de10 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Thu, 10 Aug 2017 11:31:08 +0800 Subject: [PATCH 012/138] "on hold" --- paddle/operators/mul_op.cc | 27 +++++++++++++++--- paddle/operators/mul_op.cu | 3 +- paddle/operators/mul_op.h | 28 +++++++++++++++++++ .../paddle/v2/framework/tests/test_mul_op.py | 2 ++ 4 files changed, 55 insertions(+), 5 deletions(-) diff --git a/paddle/operators/mul_op.cc b/paddle/operators/mul_op.cc index db81fd555d..fb79796f36 100644 --- a/paddle/operators/mul_op.cc +++ b/paddle/operators/mul_op.cc @@ -54,10 +54,27 @@ The equation is: Out = X * Y class MulOpGrad : public framework::OperatorWithKernel { protected: - void InferShape(const framework::InferShapeContext &ctx) const override {} - std::string DebugString() const override { - LOG(INFO) << "MulGrad"; - return ""; + void InferShape(const framework::InferShapeContext &ctx) const override { + PADDLE_ENFORCE_EQ(ctx.InputSize(), 3UL, + "Input of MulOpGrad should be 3, X, Y, Out@GRAD"); + PADDLE_ENFORCE_EQ(ctx.OutputSize(), 2UL, + "Output of MulOpGrad should be 2, X@GRAD, Y@GRAD"); + PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) should not be null"); + PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"), "Input(Y) should not be null"); + PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Out")), + "Input(Out@GRAD) should not be null"); + auto *x_grad = ctx.Output(framework::GradVarName("X")); + auto *y_grad = ctx.Output(framework::GradVarName("Y")); + auto dim0 = ctx.Input(0)->dims(); + auto dim1 = ctx.Input(1)->dims(); + auto out_dims = ctx.Input(2)->dims(); + PADDLE_ENFORCE(dim0[0] * dim1[0] == out_dims[0], + "Out@GRAD[0] must equal to X[0] * Y[0]"); + PADDLE_ENFORCE(dim0[1] * dim1[1] == out_dims[1], + "Out@GRAD shape must equal to X[1] * Y[1]"); + + x_grad->Resize(dim1); + y_grad->Resize(dim0); } }; @@ -69,3 +86,5 @@ REGISTER_OP(mul, ops::MulOp, ops::MulOpMaker); REGISTER_GRADIENT_OP(mul, mul_grad, ops::MulOpGrad); REGISTER_OP_CPU_KERNEL(mul, ops::MulKernel); +REGISTER_OP_CPU_KERNEL(mul_grad, + ops::MulGradKernel); diff --git a/paddle/operators/mul_op.cu b/paddle/operators/mul_op.cu index 43debbc21a..a81444dbe6 100644 --- a/paddle/operators/mul_op.cu +++ b/paddle/operators/mul_op.cu @@ -16,5 +16,6 @@ #include "paddle/operators/mul_op.h" namespace ops = paddle::operators; - REGISTER_OP_GPU_KERNEL(mul, ops::MulKernel); +REGISTER_OP_GPU_KERNEL(mul_grad, + ops::MulGradKernel); diff --git a/paddle/operators/mul_op.h b/paddle/operators/mul_op.h index ab12631c03..2032a2addd 100644 --- a/paddle/operators/mul_op.h +++ b/paddle/operators/mul_op.h @@ -46,5 +46,33 @@ class MulKernel : public framework::OpKernel { } }; +template +class MulGradKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& ctx) const override { + auto* input0 = ctx.Input("X"); + auto* input1 = ctx.Input("Y"); + auto* input2 = ctx.Input(framework::GradVarName("Out")); + + auto* output0 = ctx.Output(0); + auto* output1 = ctx.Output(1); + output0->mutable_data(ctx.GetPlace()); + output1->mutable_data(ctx.GetPlace()); + + auto X = EigenMatrix::From(*input0); + auto Y = EigenMatrix::From(*input1); + auto dOut = EigenMatrix::From(*input2); + auto dX = EigenMatrix::From(*output0); + auto dY = EigenMatrix::From(*output1); + + // dX = Out@G * Y' + // dY = X' * Out@G + auto place = ctx.GetEigenDevice(); + // TODO(dzh,qijun) : need transpose feature of blas library + // Eigen Tensor does not support it very well + // dX.device(place) = dOut.contract(dOut, transpose) + } +}; + } // namespace operators } // namespace paddle diff --git a/python/paddle/v2/framework/tests/test_mul_op.py b/python/paddle/v2/framework/tests/test_mul_op.py index ec0ac99156..126a7f3985 100644 --- a/python/paddle/v2/framework/tests/test_mul_op.py +++ b/python/paddle/v2/framework/tests/test_mul_op.py @@ -15,5 +15,7 @@ class TestMulOp(unittest.TestCase): self.outputs = {'Out': np.dot(self.inputs['X'], self.inputs['Y'])} +# TODO(dzh,qijun) : mulgrad test case need transpose feature of blas library + if __name__ == '__main__': unittest.main() From b97f020f9c34da04e093deb4691f6286f4017e62 Mon Sep 17 00:00:00 2001 From: caoying03 Date: Thu, 10 Aug 2017 10:37:07 +0800 Subject: [PATCH 013/138] fix unittest error. --- paddle/gserver/layers/SequenceSliceLayer.cpp | 3 +-- python/paddle/trainer_config_helpers/layers.py | 1 + .../protostr/test_kmax_seq_socre_layer.protostr | 17 +++++------------ .../tests/configs/test_kmax_seq_socre_layer.py | 4 +--- 4 files changed, 8 insertions(+), 17 deletions(-) diff --git a/paddle/gserver/layers/SequenceSliceLayer.cpp b/paddle/gserver/layers/SequenceSliceLayer.cpp index 424f898553..165ee6311a 100644 --- a/paddle/gserver/layers/SequenceSliceLayer.cpp +++ b/paddle/gserver/layers/SequenceSliceLayer.cpp @@ -70,9 +70,8 @@ void SequenceSliceLayer::checkInputs() { const Argument& inputSeq = getInput(0); CHECK(inputSeq.hasSeq()) << "The first input of sequence slic layer " << "must be a sequence."; - // Check inputs const MatrixPtr indices1 = getInputValue(1); - CHECK_EQ(indices1->getHeight(), + CHECK_EQ(static_cast(indices1->getHeight()), inputSeq.hasSubseq() ? inputSeq.getNumSubSequences() : inputSeq.getNumSequences()) << "Height of the second input should be equal to number of sequence " diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py index e51332da0d..79d24cfe5b 100755 --- a/python/paddle/trainer_config_helpers/layers.py +++ b/python/paddle/trainer_config_helpers/layers.py @@ -6242,6 +6242,7 @@ def seq_slice_layer(input, starts, ends, name=None): name, LayerType.SEQ_SLICE, parents=[input], size=input.size) +@wrap_name_default() @layer_support() def kmax_sequence_score_layer(input, name=None, beam_size=1): """ diff --git a/python/paddle/trainer_config_helpers/tests/configs/protostr/test_kmax_seq_socre_layer.protostr b/python/paddle/trainer_config_helpers/tests/configs/protostr/test_kmax_seq_socre_layer.protostr index 81bd71f68e..3d32220bfb 100644 --- a/python/paddle/trainer_config_helpers/tests/configs/protostr/test_kmax_seq_socre_layer.protostr +++ b/python/paddle/trainer_config_helpers/tests/configs/protostr/test_kmax_seq_socre_layer.protostr @@ -1,12 +1,6 @@ type: "nn" layers { - name: "input" - type: "data" - size: 300 - active_type: "" -} -layers { - name: "data" + name: "input_seq" type: "data" size: 128 active_type: "" @@ -17,7 +11,7 @@ layers { size: 1 active_type: "exponential" inputs { - input_layer_name: "data" + input_layer_name: "input_seq" input_parameter_name: "___fc_layer_0__.w0" } bias_parameter_name: "___fc_layer_0__.wbias" @@ -51,15 +45,14 @@ parameters { initial_strategy: 0 initial_smart: false } -input_layer_names: "data" +input_layer_names: "input_seq" output_layer_names: "__kmax_sequence_score_layer_0__" sub_models { name: "root" - layer_names: "input" - layer_names: "data" + layer_names: "input_seq" layer_names: "__fc_layer_0__" layer_names: "__kmax_sequence_score_layer_0__" - input_layer_names: "data" + input_layer_names: "input_seq" output_layer_names: "__kmax_sequence_score_layer_0__" is_recurrent_layer_group: false } diff --git a/python/paddle/trainer_config_helpers/tests/configs/test_kmax_seq_socre_layer.py b/python/paddle/trainer_config_helpers/tests/configs/test_kmax_seq_socre_layer.py index d245c5a41c..48d0cd55da 100644 --- a/python/paddle/trainer_config_helpers/tests/configs/test_kmax_seq_socre_layer.py +++ b/python/paddle/trainer_config_helpers/tests/configs/test_kmax_seq_socre_layer.py @@ -2,9 +2,7 @@ #coding=utf-8 from paddle.trainer_config_helpers import * -data = data_layer(name='input', size=300) - -data = data_layer(name="data", size=128) +data = data_layer(name="input_seq", size=128) scores = fc_layer(input=data, size=1, act=ExpActivation()) kmax_seq_id = kmax_sequence_score_layer(input=scores, beam_size=5) From 632b320e9dc11c6991d95187631c311cae7f7162 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Mon, 14 Aug 2017 17:19:15 +0800 Subject: [PATCH 014/138] "refine argument with new style " --- paddle/operators/math/math_function.h | 9 +++ paddle/operators/mul_op.cc | 20 ++++--- paddle/operators/mul_op.h | 60 +++++++++++-------- .../paddle/v2/framework/tests/test_mul_op.py | 13 +++- 4 files changed, 66 insertions(+), 36 deletions(-) diff --git a/paddle/operators/math/math_function.h b/paddle/operators/math/math_function.h index 155589fadb..c7c603929b 100644 --- a/paddle/operators/math/math_function.h +++ b/paddle/operators/math/math_function.h @@ -77,6 +77,15 @@ void matmul(const framework::Tensor& matrix_a, bool trans_a, framework::Tensor* matrix_out, T beta, platform::DeviceContext* context); +// // matrix multiply with continuous memory +// template +// void matmul(const framework::Tensor& matrix_a, bool trans_a, +// const framework::Tensor& matrix_b, bool trans_b, +// framework::Tensor* matrix_out, +// platform::DeviceContext* context) { +// matmul(matrix_a, matrix_b, trans_a, trans_b, 1, matrix_out, 0, context); +// } + } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/mul_op.cc b/paddle/operators/mul_op.cc index a1ca66a24d..d77c0607a0 100644 --- a/paddle/operators/mul_op.cc +++ b/paddle/operators/mul_op.cc @@ -18,6 +18,8 @@ namespace paddle { namespace operators { +using framework::Tensor; + class MulOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; @@ -60,19 +62,19 @@ class MulOpGrad : public framework::OperatorWithKernel { protected: void InferShape(const framework::InferShapeContext &ctx) const override { - PADDLE_ENFORCE_EQ(ctx.InputSize(), 3UL, - "Input of MulOpGrad should be 3, X, Y, Out@GRAD"); - PADDLE_ENFORCE_EQ(ctx.OutputSize(), 2UL, - "Output of MulOpGrad should be 2, X@GRAD, Y@GRAD"); + // PADDLE_ENFORCE_EQ(ctx.InputSize(), 3UL, + // "Input of MulOpGrad should be 3, X, Y, Out@GRAD"); + // PADDLE_ENFORCE_EQ(ctx.OutputSize(), 2UL, + // "Output of MulOpGrad should be 2, X@GRAD, Y@GRAD"); PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) should not be null"); PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"), "Input(Y) should not be null"); PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Out")), "Input(Out@GRAD) should not be null"); - auto *x_grad = ctx.Output(framework::GradVarName("X")); - auto *y_grad = ctx.Output(framework::GradVarName("Y")); - auto dim0 = ctx.Input(0)->dims(); - auto dim1 = ctx.Input(1)->dims(); - auto out_dims = ctx.Input(2)->dims(); + auto *x_grad = ctx.Output(framework::GradVarName("X")); + auto *y_grad = ctx.Output(framework::GradVarName("Y")); + auto dim0 = ctx.Input(framework::GradVarName("X"))->dims(); + auto dim1 = ctx.Input(framework::GradVarName("Y"))->dims(); + auto out_dims = ctx.Input(framework::GradVarName("Out"))->dims(); PADDLE_ENFORCE(dim0[0] * dim1[0] == out_dims[0], "Out@GRAD[0] must equal to X[0] * Y[0]"); PADDLE_ENFORCE(dim0[1] * dim1[1] == out_dims[1], diff --git a/paddle/operators/mul_op.h b/paddle/operators/mul_op.h index ad40e3cf11..279454c7f3 100644 --- a/paddle/operators/mul_op.h +++ b/paddle/operators/mul_op.h @@ -31,18 +31,22 @@ template class MulKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { - Eigen::array, 1> dim_pair = { - {Eigen::IndexPair(1, 0)}}; - auto* input0 = context.Input("X"); - auto* input1 = context.Input("Y"); - auto* output = context.Output("Out"); - output->mutable_data(context.GetPlace()); - auto X = EigenMatrix::From(*input0); - auto Y = EigenMatrix::From(*input1); - auto Z = EigenMatrix::From(*output); - auto& place = context.GetEigenDevice(); - - Z.device(place) = X.contract(Y, dim_pair); + // Eigen::array, 1> dim_pair = { + // {Eigen::IndexPair(1, 0)}}; + auto* X = context.Input("X"); + auto* Y = context.Input("Y"); + auto* Z = context.Output("Out"); + Z->mutable_data(context.GetPlace()); + auto* device_context = + const_cast(context.device_context_); + math::matmul(*X, false, *Y, false, 1, Z, 0, device_context); + + // auto X = EigenMatrix::From(*input0); + // auto Y = EigenMatrix::From(*input1); + // auto Z = EigenMatrix::From(*output); + // auto& place = context.GetEigenDevice(); + + // Z.device(place) = X.contract(Y, dim_pair); } }; @@ -50,27 +54,31 @@ template class MulGradKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { - auto* input0 = ctx.Input("X"); - auto* input1 = ctx.Input("Y"); - auto* input2 = ctx.Input(framework::GradVarName("Out")); + auto* X = ctx.Input("X"); + auto* Y = ctx.Input("Y"); + auto* dOut = ctx.Input(framework::GradVarName("Out")); - auto* output0 = ctx.Output(0); - auto* output1 = ctx.Output(1); - output0->mutable_data(ctx.GetPlace()); - output1->mutable_data(ctx.GetPlace()); + auto* dX = ctx.Output(framework::GradVarName("X")); + auto* dY = ctx.Output(framework::GradVarName("Y")); + // auto* dXdata = dX->template mutable_data(ctx.GetPlace()); + // auto* dYdata = dY->template mutable_data(ctx.GetPlace()); + auto* device_context = + const_cast(ctx.device_context_); + math::matmul(*dOut, false, *Y, true, 1, dX, 0, device_context); + math::matmul(*X, true, *dOut, false, 1, dY, 0, device_context); - auto X = EigenMatrix::From(*input0); - auto Y = EigenMatrix::From(*input1); - auto dOut = EigenMatrix::From(*input2); - auto dX = EigenMatrix::From(*output0); - auto dY = EigenMatrix::From(*output1); + // auto X = EigenMatrix::From(*input0); + // auto Y = EigenMatrix::From(*input1); + // auto dOut = EigenMatrix::From(*input2); + // auto dX = EigenMatrix::From(*output0); + // auto dY = EigenMatrix::From(*output1); // dX = Out@G * Y' // dY = X' * Out@G - auto place = ctx.GetEigenDevice(); + // auto place = ctx.GetEigenDevice(); // TODO(dzh,qijun) : need transpose feature of blas library // Eigen Tensor does not support it very well - // dX.device(place) = dOut.contract(dOut, transpose) + // dX.device(place) = matmul(input2, ) } }; diff --git a/python/paddle/v2/framework/tests/test_mul_op.py b/python/paddle/v2/framework/tests/test_mul_op.py index 126a7f3985..eef5a4f961 100644 --- a/python/paddle/v2/framework/tests/test_mul_op.py +++ b/python/paddle/v2/framework/tests/test_mul_op.py @@ -1,6 +1,7 @@ import unittest -from op_test_util import OpTestMeta import numpy as np +from gradient_checker import GradientChecker, create_op +from op_test_util import OpTestMeta class TestMulOp(unittest.TestCase): @@ -15,6 +16,16 @@ class TestMulOp(unittest.TestCase): self.outputs = {'Out': np.dot(self.inputs['X'], self.inputs['Y'])} +class MulGradOpTest(GradientChecker): + def test_mul(self): + op = create_op("mul") + inputs = { + 'X': np.random.random((32, 84)).astype("float32"), + 'Y': np.random.random((84, 100)).astype("float32") + } + self.check_grad(op, inputs, set(["X", "Y"]), "Out") + + # TODO(dzh,qijun) : mulgrad test case need transpose feature of blas library if __name__ == '__main__': From e0395a53e93ff1631dff39582ec4754e4f5acdf0 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Mon, 14 Aug 2017 17:57:22 +0800 Subject: [PATCH 015/138] "remove unused commented code" --- paddle/operators/mul_op.cc | 4 ---- paddle/operators/mul_op.h | 24 ------------------------ 2 files changed, 28 deletions(-) diff --git a/paddle/operators/mul_op.cc b/paddle/operators/mul_op.cc index d77c0607a0..95b495b87a 100644 --- a/paddle/operators/mul_op.cc +++ b/paddle/operators/mul_op.cc @@ -62,10 +62,6 @@ class MulOpGrad : public framework::OperatorWithKernel { protected: void InferShape(const framework::InferShapeContext &ctx) const override { - // PADDLE_ENFORCE_EQ(ctx.InputSize(), 3UL, - // "Input of MulOpGrad should be 3, X, Y, Out@GRAD"); - // PADDLE_ENFORCE_EQ(ctx.OutputSize(), 2UL, - // "Output of MulOpGrad should be 2, X@GRAD, Y@GRAD"); PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) should not be null"); PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"), "Input(Y) should not be null"); PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Out")), diff --git a/paddle/operators/mul_op.h b/paddle/operators/mul_op.h index 279454c7f3..2afed81842 100644 --- a/paddle/operators/mul_op.h +++ b/paddle/operators/mul_op.h @@ -31,8 +31,6 @@ template class MulKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { - // Eigen::array, 1> dim_pair = { - // {Eigen::IndexPair(1, 0)}}; auto* X = context.Input("X"); auto* Y = context.Input("Y"); auto* Z = context.Output("Out"); @@ -40,13 +38,6 @@ class MulKernel : public framework::OpKernel { auto* device_context = const_cast(context.device_context_); math::matmul(*X, false, *Y, false, 1, Z, 0, device_context); - - // auto X = EigenMatrix::From(*input0); - // auto Y = EigenMatrix::From(*input1); - // auto Z = EigenMatrix::From(*output); - // auto& place = context.GetEigenDevice(); - - // Z.device(place) = X.contract(Y, dim_pair); } }; @@ -60,25 +51,10 @@ class MulGradKernel : public framework::OpKernel { auto* dX = ctx.Output(framework::GradVarName("X")); auto* dY = ctx.Output(framework::GradVarName("Y")); - // auto* dXdata = dX->template mutable_data(ctx.GetPlace()); - // auto* dYdata = dY->template mutable_data(ctx.GetPlace()); auto* device_context = const_cast(ctx.device_context_); math::matmul(*dOut, false, *Y, true, 1, dX, 0, device_context); math::matmul(*X, true, *dOut, false, 1, dY, 0, device_context); - - // auto X = EigenMatrix::From(*input0); - // auto Y = EigenMatrix::From(*input1); - // auto dOut = EigenMatrix::From(*input2); - // auto dX = EigenMatrix::From(*output0); - // auto dY = EigenMatrix::From(*output1); - - // dX = Out@G * Y' - // dY = X' * Out@G - // auto place = ctx.GetEigenDevice(); - // TODO(dzh,qijun) : need transpose feature of blas library - // Eigen Tensor does not support it very well - // dX.device(place) = matmul(input2, ) } }; From 12ee5014857e751fb429e0d3ebcfd41dcd5da29d Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Mon, 14 Aug 2017 20:57:46 +0800 Subject: [PATCH 016/138] "fix operator grad config" --- paddle/operators/rowwise_add_op.cc | 23 +++++++++++++++++------ paddle/operators/rowwise_add_op.h | 21 +++++++++++---------- 2 files changed, 28 insertions(+), 16 deletions(-) diff --git a/paddle/operators/rowwise_add_op.cc b/paddle/operators/rowwise_add_op.cc index 0c6ae64d0c..60e5d7749c 100644 --- a/paddle/operators/rowwise_add_op.cc +++ b/paddle/operators/rowwise_add_op.cc @@ -17,6 +17,8 @@ namespace paddle { namespace operators { +using framework::Tensor; + class RowwiseAddOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; @@ -50,14 +52,23 @@ for i in xrange(X.shape[0]): } }; class RowwiseAddGradOp : public framework::OperatorWithKernel { + public: + using framework::OperatorWithKernel::OperatorWithKernel; + protected: void InferShape(const framework::InferShapeContext &ctx) const override { - PADDLE_ENFORCE(ctx.InputSize() == 4UL, - "RowwiseAddGrad inputs is I, O, OG, size must be 4"); - PADDLE_ENFORCE(ctx.OutputSize() == 2, - "RowwiseAddGrad output is IG, size must be 2"); - ctx.Output(0)->Resize(ctx.Input(0)->dims()); - ctx.Output(1)->Resize(ctx.Input(1)->dims()); + // PADDLE_ENFORCE(ctx.InputSize() == 4UL, + // "RowwiseAddGrad inputs is I, O, OG, size must be 4"); + // PADDLE_ENFORCE(ctx.OutputSize() == 2, + // "RowwiseAddGrad output is IG, size must be 2"); + PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "X should not be null"); + PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("b"), "b should not be null"); + PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Out")), + "Input(Out@GRAD) should not be null"); + auto dims0 = ctx.Input("X")->dims(); + auto dims1 = ctx.Input("b")->dims(); + ctx.Output(framework::GradVarName("X"))->Resize(dims0); + ctx.Output(framework::GradVarName("b"))->Resize(dims1); } }; diff --git a/paddle/operators/rowwise_add_op.h b/paddle/operators/rowwise_add_op.h index 3ad60172c1..6593d811e4 100644 --- a/paddle/operators/rowwise_add_op.h +++ b/paddle/operators/rowwise_add_op.h @@ -51,19 +51,20 @@ template class RowwiseAddGradKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { - auto* XGrad = context.Output(0); - auto* bGrad = context.Output(1); - XGrad->mutable_data(context.GetPlace()); - bGrad->mutable_data(context.GetPlace()); + auto* dX = context.Output(framework::GradVarName("X")); + auto* db = context.Output(framework::GradVarName("b")); + auto* dOut = context.Output(framework::GradVarName("Out")); + dX->mutable_data(context.GetPlace()); + db->mutable_data(context.GetPlace()); - // I, O, OG => [X, b], [Out], [OutGrad] - auto OutGrad = EigenMatrix::From(*context.Input(3)); - EigenMatrix::From(*XGrad).device(context.GetEigenDevice()) = - OutGrad; + auto OutGrad = EigenMatrix::From(*dOut); + auto place = context.GetEigenDevice(); + EigenMatrix::From(*dX).device(place) = OutGrad; // https://eigen.tuxfamily.org/dox/unsupported/TensorBase_8h_source.html - EigenVector::Flatten(*bGrad).device(context.GetEigenDevice()) = - OutGrad.cumsum(1); // colwise add + // colwise add + Eigen::array dims{{1}}; /* dimension to reduce */ + EigenVector::Flatten(*db).device(place) = OutGrad.sum(dims); } }; } // namespace operators From af1eb31afc92ae3ac59869a6a5b0e890e009c44b Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Fri, 11 Aug 2017 11:55:56 -0700 Subject: [PATCH 017/138] add as an operator --- paddle/operators/CMakeLists.txt | 2 ++ paddle/operators/gather_op.cc | 64 +++++++++++++++++++++++++++++++++ paddle/operators/gather_op.h | 52 +++++++++++++++++++++++++++ 3 files changed, 118 insertions(+) create mode 100644 paddle/operators/gather_op.cc create mode 100644 paddle/operators/gather_op.h diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index a7c89787e4..5ac898a8d3 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -43,6 +43,8 @@ endfunction() add_subdirectory(math) cc_test(gather_test SRCS gather_test.cc DEPS tensor) +cc_library(gather_op SRCS gather_op.cc DEPS op_registry) +# cc_test(gather_op_test SRCS gather_op_test.cc DEPS gather_op) cc_test(scatter_test SRCS scatter_test.cc DEPS tensor) diff --git a/paddle/operators/gather_op.cc b/paddle/operators/gather_op.cc new file mode 100644 index 0000000000..1008a57a87 --- /dev/null +++ b/paddle/operators/gather_op.cc @@ -0,0 +1,64 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "paddle/operators/gather_op.h" +#include "paddle/framework/ddim.h" + +namespace paddle { +namespace operators { + +class GatherOp : public framework::OperatorWithKernel { + protected: + void InferShape(const framework::InferShapeContext &ctx) const override { + PADDLE_ENFORCE(ctx.InputSize() == 2, ""); + PADDLE_ENFORCE(ctx.OutputSize() == 1, ""); + int batch_size = ctx.Input(1)->dims()[0]; + PADDLE_ENFORCE(batch_size > 0); + } +}; + +class GatherOpMaker : public framework::OpProtoAndCheckerMaker { + public: + GatherOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker) + : OpProtoAndCheckerMaker(proto, op_checker) { + AddInput("X", "The source input of gather op"); + AddInput("Index", "The index input of gather op"); + AddOutput("Y", "The output of add op"); + AddComment(R"DOC( +Gather Operator by selecting from the first axis, + +Y = X[Index] +)DOC"); + } +}; + +class GatherGradOp : public framework::OperatorWithKernel { + protected: + void InferShape(const framework::InferShapeContext &ctx) const override { + // ctx.Output("X" + framework::kGradVarSuffix) + // ->Resize(ctx.Input("X")->dims()); + } +}; + +} // namespace operators +} // namespace paddle + +namespace ops = paddle::operators; +REGISTER_OP(gather, ops::GatherOp, ops::GatherOpMaker); +REGISTER_OP_CPU_KERNEL(gather, + ops::GatherOpKernel); +REGISTER_GRADIENT_OP(gather, gather_grad, ops::GatherGradOp); +REGISTER_OP_CPU_KERNEL( + gather_grad, + ops::GatherGradientOpKernel); diff --git a/paddle/operators/gather_op.h b/paddle/operators/gather_op.h new file mode 100644 index 0000000000..13e4c9b058 --- /dev/null +++ b/paddle/operators/gather_op.h @@ -0,0 +1,52 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#pragma once +#include "gather.h" +#include "paddle/framework/eigen.h" +#include "paddle/framework/op_registry.h" +#include "scatter.h" + +namespace paddle { +namespace operators { + +using Tensor = framework::Tensor; + +template +class GatherOpKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& ctx) const override { + auto X = ctx.Input("X"); + auto Index = ctx.Input("Index"); + auto Y = ctx.Output("Y"); + + Y->mutable_data(ctx.GetPlace()); + Gather(ctx.GetPlace(), X, Index, Y); + } +}; + +template +class GatherGradientOpKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& ctx) const override { + auto Index = ctx.Input("Index"); + auto dX = ctx.Output(framework::GradVarName("X")); + auto dY = ctx.Input(framework::GradVarName("Y")); + + ScatterUpdate(ctx.GetPlace(), dY, Index, dX); + } +}; + +} // namespace operators +} // namespace paddle From caaa5f86b91beda67daf8ae295cf99fa4dce12ba Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Fri, 11 Aug 2017 15:09:04 -0700 Subject: [PATCH 018/138] gather op added --- paddle/framework/CMakeLists.txt | 2 ++ paddle/framework/empty_test.cc | 56 +++++++++++++++++++++++++++++++++ paddle/operators/gather_op.cc | 2 ++ 3 files changed, 60 insertions(+) create mode 100644 paddle/framework/empty_test.cc diff --git a/paddle/framework/CMakeLists.txt b/paddle/framework/CMakeLists.txt index 0398526024..9e306c8650 100644 --- a/paddle/framework/CMakeLists.txt +++ b/paddle/framework/CMakeLists.txt @@ -10,6 +10,8 @@ cc_test(eigen_test SRCS eigen_test.cc DEPS tensor) cc_library(lod_tensor SRCS lod_tensor.cc DEPS ddim place tensor) cc_test(lod_tensor_test SRCS lod_tensor_test.cc DEPS lod_tensor) +cc_test(empty_test SRCS empty_test.cc DEPS tensor) + cc_test(variable_test SRCS variable_test.cc) cc_library(scope SRCS scope.cc) diff --git a/paddle/framework/empty_test.cc b/paddle/framework/empty_test.cc new file mode 100644 index 0000000000..2237f8ce0e --- /dev/null +++ b/paddle/framework/empty_test.cc @@ -0,0 +1,56 @@ +/* + Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + http://www.apache.org/licenses/LICENSE-2.0 + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. +*/ + +#include +#include +#include "paddle/framework/tensor.h" + +TEST(Empty, Dims) { + using namespace paddle::framework; + using namespace paddle::platform; + Tensor tt; + tt.Resize(make_ddim({0, 3, 4})); + DDim dims = tt.dims(); + ASSERT_EQ(arity(dims), 3); + EXPECT_EQ(0, dims[0]); + EXPECT_EQ(3, dims[1]); + EXPECT_EQ(4, dims[2]); +} + +TEST(Empty, MutableData) { + using namespace paddle::framework; + using namespace paddle::platform; + { + Tensor src_tensor; + float* p1 = nullptr; + // initialization + p1 = src_tensor.mutable_data(make_ddim({0, 2, 3}), CPUPlace()); + EXPECT_NE(p1, nullptr); + } + +#ifndef PADDLE_ONLY_CPU + { + Tensor src_tensor; + float* p1 = nullptr; + float* p2 = nullptr; + // initialization + p1 = src_tensor.mutable_data(make_ddim({0, 2, 3}), GPUPlace()); + EXPECT_NE(p1, nullptr); + // set src_tensor a new dim with large size + // momery is supposed to be re-allocated + p2 = src_tensor.mutable_data(make_ddim({0, 4}), GPUPlace()); + EXPECT_NE(p2, nullptr); + // EXPECT_NE(p1, p2); + } +#endif +} diff --git a/paddle/operators/gather_op.cc b/paddle/operators/gather_op.cc index 1008a57a87..3414a3c263 100644 --- a/paddle/operators/gather_op.cc +++ b/paddle/operators/gather_op.cc @@ -23,6 +23,8 @@ class GatherOp : public framework::OperatorWithKernel { void InferShape(const framework::InferShapeContext &ctx) const override { PADDLE_ENFORCE(ctx.InputSize() == 2, ""); PADDLE_ENFORCE(ctx.OutputSize() == 1, ""); + PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(0), + "Inputs of GatherOp must all be set"); int batch_size = ctx.Input(1)->dims()[0]; PADDLE_ENFORCE(batch_size > 0); } From 2a42a73db1ff32f7d1b9dfc772070fc7827aa4e7 Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Fri, 11 Aug 2017 15:10:59 -0700 Subject: [PATCH 019/138] modify gather_op with test --- paddle/operators/gather_op.cc | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/paddle/operators/gather_op.cc b/paddle/operators/gather_op.cc index 3414a3c263..5a4f889f3d 100644 --- a/paddle/operators/gather_op.cc +++ b/paddle/operators/gather_op.cc @@ -27,6 +27,9 @@ class GatherOp : public framework::OperatorWithKernel { "Inputs of GatherOp must all be set"); int batch_size = ctx.Input(1)->dims()[0]; PADDLE_ENFORCE(batch_size > 0); + paddle::framework::DDim output_dims(ctx.Input(0)->dims()); + output_dims[0] = batch_size; + ctx.Output(0)->Resize(output_dims); } }; @@ -48,8 +51,8 @@ Y = X[Index] class GatherGradOp : public framework::OperatorWithKernel { protected: void InferShape(const framework::InferShapeContext &ctx) const override { - // ctx.Output("X" + framework::kGradVarSuffix) - // ->Resize(ctx.Input("X")->dims()); + ctx.Output("X" + framework::kGradVarSuffix) + ->Resize(ctx.Input("X")->dims()); } }; From f6bffd4e1ff506319fa1a3338038d61d3f653181 Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Fri, 11 Aug 2017 15:40:23 -0700 Subject: [PATCH 020/138] gather_op modified --- paddle/operators/gather_op.cc | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/paddle/operators/gather_op.cc b/paddle/operators/gather_op.cc index 5a4f889f3d..05ba52ce06 100644 --- a/paddle/operators/gather_op.cc +++ b/paddle/operators/gather_op.cc @@ -51,8 +51,10 @@ Y = X[Index] class GatherGradOp : public framework::OperatorWithKernel { protected: void InferShape(const framework::InferShapeContext &ctx) const override { - ctx.Output("X" + framework::kGradVarSuffix) - ->Resize(ctx.Input("X")->dims()); + auto X_grad = ctx.Output(framework::GradVarName("X")); + auto X = ctx.Input("X"); + + X_grad->Resize(X->dims()); } }; From 4ab36a71c4cdc2319d0566ddef355ad11dcddd7b Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Tue, 15 Aug 2017 13:42:19 +0800 Subject: [PATCH 021/138] "fix error" --- paddle/operators/mul_op.cc | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/paddle/operators/mul_op.cc b/paddle/operators/mul_op.cc index 903ca7b184..9a57e6b68f 100644 --- a/paddle/operators/mul_op.cc +++ b/paddle/operators/mul_op.cc @@ -68,8 +68,8 @@ class MulOpGrad : public framework::OperatorWithKernel { "Input(Out@GRAD) should not be null"); auto *x_grad = ctx.Output(framework::GradVarName("X")); auto *y_grad = ctx.Output(framework::GradVarName("Y")); - auto dim0 = ctx.Input(framework::GradVarName("X"))->dims(); - auto dim1 = ctx.Input(framework::GradVarName("Y"))->dims(); + auto dim0 = ctx.Output(framework::GradVarName("X"))->dims(); + auto dim1 = ctx.Output(framework::GradVarName("Y"))->dims(); auto out_dims = ctx.Input(framework::GradVarName("Out"))->dims(); PADDLE_ENFORCE(dim0[0] * dim1[0] == out_dims[0], "Out@GRAD[0] must equal to X[0] * Y[0]"); From e256bfaf28a0984a15d594110ad1e868380a3e25 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Tue, 15 Aug 2017 17:12:35 +0800 Subject: [PATCH 022/138] "update paddle enforce" --- paddle/operators/mul_op.cc | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/paddle/operators/mul_op.cc b/paddle/operators/mul_op.cc index 9a57e6b68f..5645df6677 100644 --- a/paddle/operators/mul_op.cc +++ b/paddle/operators/mul_op.cc @@ -68,16 +68,16 @@ class MulOpGrad : public framework::OperatorWithKernel { "Input(Out@GRAD) should not be null"); auto *x_grad = ctx.Output(framework::GradVarName("X")); auto *y_grad = ctx.Output(framework::GradVarName("Y")); - auto dim0 = ctx.Output(framework::GradVarName("X"))->dims(); - auto dim1 = ctx.Output(framework::GradVarName("Y"))->dims(); + auto x_dims = ctx.Output(framework::GradVarName("X"))->dims(); + auto y_dims = ctx.Output(framework::GradVarName("Y"))->dims(); auto out_dims = ctx.Input(framework::GradVarName("Out"))->dims(); - PADDLE_ENFORCE(dim0[0] * dim1[0] == out_dims[0], - "Out@GRAD[0] must equal to X[0] * Y[0]"); - PADDLE_ENFORCE(dim0[1] * dim1[1] == out_dims[1], - "Out@GRAD shape must equal to X[1] * Y[1]"); + PADDLE_ENFORCE(x_dims[0] == out_dims[0], + "Out@GRAD M X N must equal to X dims 0, M "); + PADDLE_ENFORCE(y_dims[1] == out_dims[1], + "Out@GRAD M X N must equal to Y dims 1, N "); - x_grad->Resize(dim1); - y_grad->Resize(dim0); + x_grad->Resize(x_dims); + y_grad->Resize(y_dims); } }; From 49aa2c042cbae87ada74e7e63590f7b43239c596 Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Tue, 15 Aug 2017 17:40:26 +0800 Subject: [PATCH 023/138] Implement GPU kernel for cross entropy operator. --- paddle/framework/pybind.cc | 2 +- paddle/operators/cross_entropy_op.cc | 15 +-- paddle/operators/cross_entropy_op.cu | 108 +++++++++++++++++- paddle/operators/cross_entropy_op.h | 11 +- .../framework/tests/test_cross_entropy_op.py | 2 +- 5 files changed, 120 insertions(+), 18 deletions(-) diff --git a/paddle/framework/pybind.cc b/paddle/framework/pybind.cc index fe0c87bc57..2b3e7fba41 100644 --- a/paddle/framework/pybind.cc +++ b/paddle/framework/pybind.cc @@ -31,7 +31,7 @@ limitations under the License. */ namespace py = pybind11; USE_OP(add_two); -USE_CPU_ONLY_OP(onehot_cross_entropy); +USE_OP(onehot_cross_entropy); USE_OP(sgd); USE_OP(mul); USE_OP(mean); diff --git a/paddle/operators/cross_entropy_op.cc b/paddle/operators/cross_entropy_op.cc index a623c551e1..ab1e1c101a 100644 --- a/paddle/operators/cross_entropy_op.cc +++ b/paddle/operators/cross_entropy_op.cc @@ -39,11 +39,10 @@ class OnehotCrossEntropyGradientOp : public framework::OperatorWithKernel { protected: void InferShape(const framework::InferShapeContext &ctx) const override { - auto X_grad = ctx.Output(framework::GradVarName("X")); + auto dX = ctx.Output(framework::GradVarName("X")); auto X = ctx.Input("X"); - // TODO(superjom) add enforce here after helper functions ready - X_grad->Resize(X->dims()); + dX->Resize(X->dims()); } }; @@ -70,9 +69,7 @@ namespace ops = paddle::operators; REGISTER_OP(onehot_cross_entropy, ops::OnehotCrossEntropyOp, ops::OnehotCrossEntropyOpMaker, onehot_cross_entropy_grad, ops::OnehotCrossEntropyGradientOp); -REGISTER_OP_CPU_KERNEL( - onehot_cross_entropy, - ops::OnehotCrossEntropyOpKernel); -REGISTER_OP_CPU_KERNEL( - onehot_cross_entropy_grad, - ops::OnehotCrossEntropyGradientOpKernel); +REGISTER_OP_CPU_KERNEL(onehot_cross_entropy, + ops::OnehotCrossEntropyOpKernel); +REGISTER_OP_CPU_KERNEL(onehot_cross_entropy_grad, + ops::OnehotCrossEntropyGradientOpKernel); diff --git a/paddle/operators/cross_entropy_op.cu b/paddle/operators/cross_entropy_op.cu index 4bbc8f093a..2392c3d5ed 100644 --- a/paddle/operators/cross_entropy_op.cu +++ b/paddle/operators/cross_entropy_op.cu @@ -12,10 +12,108 @@ See the License for the specific language governing permissions and limitations under the License. */ -#define EIGEN_USE_GPU -#include "paddle/operators/cross_entropy_op.h" +#include "paddle/framework/op_registry.h" +#include "paddle/platform/assert.h" + +namespace paddle { +namespace operators { + +using Tensor = framework::Tensor; + +template +__global__ void CrossEntropyKernel(T* Y, const T* X, const int* label, + const int N, const int D) { + // TOOD(qingqing) define CUDA_1D_KERNEL_LOOP macro in a common file. + // CUDA_1D_KERNEL_LOOP(i, N) { + for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < N; + i += blockDim.x * gridDim.x) { + PADDLE_ASSERT(label[i] >= 0 && label[i] < D); + Y[i] = -log(X[i * D + label[i]]); + } +} + +template +__global__ void zero(T* X, const int N) { + for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < N; + i += blockDim.x * gridDim.x) { + X[i] = 0.0; + } +} + +template +__global__ void CrossEntropyGradientKernel(T* dX, const T* dY, const T* X, + const int* label, const int N, + const int D) { + // TOOD(qingqing) define CUDA_1D_KERNEL_LOOP macro in a common file. + // CUDA_1D_KERNEL_LOOP(i, N) { + for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < N; + i += blockDim.x * gridDim.x) { + int idx = i * D + label[i]; + dX[idx] = -dY[i] / X[idx]; + } +} + +template +class OnehotCrossEntropyOpCUDAKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& ctx) const override { + PADDLE_ENFORCE(platform::is_gpu_place(ctx.GetPlace()), + "It must use GPUPlace."); + + auto X = ctx.Input("X"); + const T* Xdata = X->data(); + const int* label_data = ctx.Input("label")->data(); + auto Y = ctx.Output("Y"); + Y->mutable_data(ctx.GetPlace()); + T* Ydata = Y->data(); + + int N = X->dims()[0]; + int D = X->dims()[1]; + int block = 512; + int grid = (N + block - 1) / block; + // TODO(qingqing) launch kernel on specified stream + // base on ExecutionContext. + CrossEntropyKernel<<>>(Ydata, Xdata, label_data, N, D); + } +}; + +template +class OnehotCrossEntropyGradientOpCUDAKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& ctx) const override { + PADDLE_ENFORCE(platform::is_gpu_place(ctx.GetPlace()), + "It must use GPUPlace."); + + auto X = ctx.Input("X"); + auto dX = ctx.Output(framework::GradVarName("X")); + auto dY = ctx.Input(framework::GradVarName("Y")); + auto label = ctx.Input("label"); + + auto* dXdata = dX->template mutable_data(ctx.GetPlace()); + auto* dYdata = dY->template data(); + auto* Xdata = X->template data(); + auto* label_data = label->data(); + + int N = X->dims()[0]; + int D = X->dims()[1]; + int block = 512; + int grid = (N * D + block - 1) / block; + // TODO(qingqing): make zero an common function. + zero<<>>(dXdata, N * D); + + grid = (N + block - 1) / block; + // TODO(qingqing): launch kernel on specified stream + // base on ExecutionContext. + CrossEntropyGradientKernel<<>>(dXdata, dYdata, Xdata, + label_data, N, D); + } +}; + +} // namespace operators +} // namespace paddle namespace ops = paddle::operators; -REGISTER_OP_GPU_KERNEL( - onehot_cross_entropy, - ops::OnehotCrossEntropyOpKernel); +REGISTER_OP_GPU_KERNEL(onehot_cross_entropy, + ops::OnehotCrossEntropyOpCUDAKernel); +REGISTER_OP_GPU_KERNEL(onehot_cross_entropy_grad, + ops::OnehotCrossEntropyGradientOpCUDAKernel); diff --git a/paddle/operators/cross_entropy_op.h b/paddle/operators/cross_entropy_op.h index b7df92c9a9..261cbe2d42 100644 --- a/paddle/operators/cross_entropy_op.h +++ b/paddle/operators/cross_entropy_op.h @@ -39,10 +39,13 @@ T tolerable_value(T x) { return x; } -template +template class OnehotCrossEntropyOpKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { + PADDLE_ENFORCE(platform::is_cpu_place(ctx.GetPlace()), + "It must use CPUPlace."); + auto X = ctx.Input("X"); const T* Xdata = X->data(); const int* label_data = ctx.Input("label")->data(); @@ -62,10 +65,13 @@ class OnehotCrossEntropyOpKernel : public framework::OpKernel { } }; -template +template class OnehotCrossEntropyGradientOpKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { + PADDLE_ENFORCE(platform::is_cpu_place(ctx.GetPlace()), + "It must use CPUPlace."); + auto X = ctx.Input("X"); auto dX = ctx.Output(framework::GradVarName("X")); auto dY = ctx.Input(framework::GradVarName("Y")); @@ -79,6 +85,7 @@ class OnehotCrossEntropyGradientOpKernel : public framework::OpKernel { const int batch_size = X->dims()[0]; const int class_num = X->dims()[1]; + memset(dXdata, 0, sizeof(T) * batch_size * class_num); for (int i = 0; i < batch_size; ++i) { int index = i * class_num + label_data[i]; dXdata[index] = -tolerable_value(dYdata[i] / Xdata[index]); diff --git a/python/paddle/v2/framework/tests/test_cross_entropy_op.py b/python/paddle/v2/framework/tests/test_cross_entropy_op.py index 4815192e25..5557e0d358 100644 --- a/python/paddle/v2/framework/tests/test_cross_entropy_op.py +++ b/python/paddle/v2/framework/tests/test_cross_entropy_op.py @@ -22,7 +22,7 @@ class TestCrossEntropy(unittest.TestCase): class CrossEntropyGradOpTest(GradientChecker): - def test_softmax_grad(self): + def test_check_grad(self): op = create_op("onehot_cross_entropy") batch_size = 100 class_num = 10 From 26475cd9ba4539a74cd2d36e8697fba4fbc52ddb Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Tue, 15 Aug 2017 19:25:16 +0800 Subject: [PATCH 024/138] Use clipping log in cuda kernel, making it same with CPU. --- paddle/operators/cross_entropy_op.cu | 19 +++++++++++++++++-- paddle/operators/cross_entropy_op.h | 3 ++- .../paddle/v2/framework/tests/op_test_util.py | 3 ++- .../framework/tests/test_cross_entropy_op.py | 5 ++--- 4 files changed, 23 insertions(+), 7 deletions(-) diff --git a/paddle/operators/cross_entropy_op.cu b/paddle/operators/cross_entropy_op.cu index 2392c3d5ed..5f5d269267 100644 --- a/paddle/operators/cross_entropy_op.cu +++ b/paddle/operators/cross_entropy_op.cu @@ -20,6 +20,21 @@ namespace operators { using Tensor = framework::Tensor; +template +struct clipping_log { + __host__ __device__ T operator()(const T x) { + PADDLE_ASSERT(std::is_floating_point::value); + const T kApproInf = 1e20; + if (x == INFINITY) { + return kApproInf; + } + if (x == -INFINITY) { + return -kApproInf; + } + return x; + } +}; + template __global__ void CrossEntropyKernel(T* Y, const T* X, const int* label, const int N, const int D) { @@ -28,10 +43,11 @@ __global__ void CrossEntropyKernel(T* Y, const T* X, const int* label, for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < N; i += blockDim.x * gridDim.x) { PADDLE_ASSERT(label[i] >= 0 && label[i] < D); - Y[i] = -log(X[i * D + label[i]]); + Y[i] = -clipping_log()(X[i * D + label[i]]); } } +// TODO(qingqing): make zero setting an common function. template __global__ void zero(T* X, const int N) { for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < N; @@ -98,7 +114,6 @@ class OnehotCrossEntropyGradientOpCUDAKernel : public framework::OpKernel { int D = X->dims()[1]; int block = 512; int grid = (N * D + block - 1) / block; - // TODO(qingqing): make zero an common function. zero<<>>(dXdata, N * D); grid = (N + block - 1) / block; diff --git a/paddle/operators/cross_entropy_op.h b/paddle/operators/cross_entropy_op.h index 261cbe2d42..e95f5e1167 100644 --- a/paddle/operators/cross_entropy_op.h +++ b/paddle/operators/cross_entropy_op.h @@ -21,7 +21,7 @@ namespace operators { using Tensor = framework::Tensor; template -T tolerable_value(T x) { +T tolerable_value(const T x) { static_assert(std::is_floating_point::value, "tolerable_value works only on float, " "double and double double."); @@ -85,6 +85,7 @@ class OnehotCrossEntropyGradientOpKernel : public framework::OpKernel { const int batch_size = X->dims()[0]; const int class_num = X->dims()[1]; + // TODO(qingqing): make zero setting an common function. memset(dXdata, 0, sizeof(T) * batch_size * class_num); for (int i = 0; i < batch_size; ++i) { int index = i * class_num + label_data[i]; diff --git a/python/paddle/v2/framework/tests/op_test_util.py b/python/paddle/v2/framework/tests/op_test_util.py index dd65e0f2dc..ae23108dfa 100644 --- a/python/paddle/v2/framework/tests/op_test_util.py +++ b/python/paddle/v2/framework/tests/op_test_util.py @@ -64,7 +64,8 @@ class OpTestMeta(type): actual = numpy.array(scope.find_var(out_name).get_tensor()) expect = self.outputs[out_name] self.assertTrue( - numpy.allclose(actual, expect), + numpy.allclose( + actual, expect, atol=1e-04), "output name: " + out_name + "has diff") obj.test_all = test_all diff --git a/python/paddle/v2/framework/tests/test_cross_entropy_op.py b/python/paddle/v2/framework/tests/test_cross_entropy_op.py index 5557e0d358..d4277f2a42 100644 --- a/python/paddle/v2/framework/tests/test_cross_entropy_op.py +++ b/python/paddle/v2/framework/tests/test_cross_entropy_op.py @@ -8,9 +8,8 @@ class TestCrossEntropy(unittest.TestCase): __metaclass__ = OpTestMeta def setUp(self): - # TODO this unit test is not passed self.type = "onehot_cross_entropy" - batch_size = 100 + batch_size = 30 class_num = 10 X = numpy.random.random((batch_size, class_num)).astype("float32") label = 5 * numpy.ones(batch_size).astype("int32") @@ -24,7 +23,7 @@ class TestCrossEntropy(unittest.TestCase): class CrossEntropyGradOpTest(GradientChecker): def test_check_grad(self): op = create_op("onehot_cross_entropy") - batch_size = 100 + batch_size = 30 class_num = 10 inputs = { "X": numpy.random.uniform( From 323d4233f3cb0f72ddac36977941e84880a7eedc Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Tue, 15 Aug 2017 23:50:56 +0000 Subject: [PATCH 025/138] gather op added with python unittest --- paddle/operators/gather_op.cu | 20 ++++++++++++++++ .../v2/framework/tests/test_gather_op.py | 23 +++++++++++++++++++ 2 files changed, 43 insertions(+) create mode 100644 paddle/operators/gather_op.cu create mode 100644 python/paddle/v2/framework/tests/test_gather_op.py diff --git a/paddle/operators/gather_op.cu b/paddle/operators/gather_op.cu new file mode 100644 index 0000000000..3f04a7b3f8 --- /dev/null +++ b/paddle/operators/gather_op.cu @@ -0,0 +1,20 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#define EIGEN_USE_GPU +#include "paddle/operators/gather_op.h" + +namespace ops = paddle::operators; +REGISTER_OP_GPU_KERNEL(gather, + ops::GatherOpKernel); diff --git a/python/paddle/v2/framework/tests/test_gather_op.py b/python/paddle/v2/framework/tests/test_gather_op.py new file mode 100644 index 0000000000..2ffbf17236 --- /dev/null +++ b/python/paddle/v2/framework/tests/test_gather_op.py @@ -0,0 +1,23 @@ +import unittest + +import numpy +import paddle.v2.framework.core as core +from paddle.v2.framework.op import Operator + +from op_test_util import OpTestMeta + + +class TestGatherOp(unittest.TestCase): + __metaclass__ = OpTestMeta + + def setUp(self): + self.type = "gather" + self.inputs = { + 'X': numpy.random.random((10, 20)).astype("float32"), + 'Index': numpy.array([1, 3, 5]).astype("int") + } + self.outputs = {'Y': self.input['X'][self.input['Index']]} + + +if __name__ == "__main__": + unittest.main() From 4d2adab772e3c0789e9696533da61ee3583363d1 Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Tue, 15 Aug 2017 23:54:16 +0000 Subject: [PATCH 026/138] gather op added with python unittest --- paddle/framework/CMakeLists.txt | 1 + paddle/framework/pybind.cc | 1 + paddle/operators/CMakeLists.txt | 3 +- paddle/operators/gather_op.cc | 43 +++++++++++-------- .../paddle/v2/framework/tests/CMakeLists.txt | 1 + 5 files changed, 29 insertions(+), 20 deletions(-) diff --git a/paddle/framework/CMakeLists.txt b/paddle/framework/CMakeLists.txt index 9e306c8650..30313780a3 100644 --- a/paddle/framework/CMakeLists.txt +++ b/paddle/framework/CMakeLists.txt @@ -47,6 +47,7 @@ cc_library(paddle_pybind SHARED SRCS pybind.cc DEPS pybind python backward sgd_op + gather_op add_op mul_op rowwise_add_op diff --git a/paddle/framework/pybind.cc b/paddle/framework/pybind.cc index fe0c87bc57..90311e0dc3 100644 --- a/paddle/framework/pybind.cc +++ b/paddle/framework/pybind.cc @@ -42,6 +42,7 @@ USE_OP(fill_zeros_like); USE_OP_ITSELF(recurrent_op); USE_OP(gaussian_random); USE_OP(uniform_random); +USE_CPU_ONLY_OP(gather); namespace paddle { namespace framework { diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index 5ac898a8d3..6849e39cb7 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -43,7 +43,8 @@ endfunction() add_subdirectory(math) cc_test(gather_test SRCS gather_test.cc DEPS tensor) -cc_library(gather_op SRCS gather_op.cc DEPS op_registry) +op_library(gather_op SRCS gather_op.cc gather_op.cu) +# DEPS op_registry) # cc_test(gather_op_test SRCS gather_op_test.cc DEPS gather_op) cc_test(scatter_test SRCS scatter_test.cc DEPS tensor) diff --git a/paddle/operators/gather_op.cc b/paddle/operators/gather_op.cc index 05ba52ce06..2e08ba8dcc 100644 --- a/paddle/operators/gather_op.cc +++ b/paddle/operators/gather_op.cc @@ -19,17 +19,33 @@ namespace paddle { namespace operators { class GatherOp : public framework::OperatorWithKernel { + public: + using framework::OperatorWithKernel::OperatorWithKernel; + protected: void InferShape(const framework::InferShapeContext &ctx) const override { - PADDLE_ENFORCE(ctx.InputSize() == 2, ""); - PADDLE_ENFORCE(ctx.OutputSize() == 1, ""); - PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(0), - "Inputs of GatherOp must all be set"); - int batch_size = ctx.Input(1)->dims()[0]; + // PADDLE_ENFORCE(ctx.InputSize() == 2, ""); + // PADDLE_ENFORCE(ctx.OutputSize() == 1, ""); + // PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(0), + // "Inputs of GatherOp must all be set"); + int batch_size = ctx.Input("Index")->dims()[0]; PADDLE_ENFORCE(batch_size > 0); paddle::framework::DDim output_dims(ctx.Input(0)->dims()); output_dims[0] = batch_size; - ctx.Output(0)->Resize(output_dims); + ctx.Output("Y")->Resize(output_dims); + } +}; + +class GatherGradOp : public framework::OperatorWithKernel { + public: + using framework::OperatorWithKernel::OperatorWithKernel; + + protected: + void InferShape(const framework::InferShapeContext &ctx) const override { + auto X_grad = ctx.Output(framework::GradVarName("X")); + auto X = ctx.Input("X"); + + X_grad->Resize(X->dims()); } }; @@ -47,25 +63,14 @@ Y = X[Index] )DOC"); } }; - -class GatherGradOp : public framework::OperatorWithKernel { - protected: - void InferShape(const framework::InferShapeContext &ctx) const override { - auto X_grad = ctx.Output(framework::GradVarName("X")); - auto X = ctx.Input("X"); - - X_grad->Resize(X->dims()); - } -}; - } // namespace operators } // namespace paddle namespace ops = paddle::operators; -REGISTER_OP(gather, ops::GatherOp, ops::GatherOpMaker); +REGISTER_OP(gather, ops::GatherOp, ops::GatherOpMaker, gather_grad, + ops::GatherGradOp); REGISTER_OP_CPU_KERNEL(gather, ops::GatherOpKernel); -REGISTER_GRADIENT_OP(gather, gather_grad, ops::GatherGradOp); REGISTER_OP_CPU_KERNEL( gather_grad, ops::GatherGradientOpKernel); diff --git a/python/paddle/v2/framework/tests/CMakeLists.txt b/python/paddle/v2/framework/tests/CMakeLists.txt index 96fad9b42e..1032743a13 100644 --- a/python/paddle/v2/framework/tests/CMakeLists.txt +++ b/python/paddle/v2/framework/tests/CMakeLists.txt @@ -13,6 +13,7 @@ py_test(test_add_two_op SRCS test_add_two_op.py) py_test(test_sigmoid_op SRCS test_sigmoid_op.py) py_test(test_softmax_op SRCS test_softmax_op.py) py_test(test_cross_entropy_op SRCS test_cross_entropy_op.py) +py_test(test_gather_op SRCS test_gather_op.py) py_test(test_fill_zeros_like_op SRCS test_fill_zeros_like_op.py) py_test(gradient_checker SRCS gradient_checker.py) From 6075928d5531b5eecff0d3183c1d47ab3b0962d4 Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Wed, 16 Aug 2017 19:02:29 +0000 Subject: [PATCH 027/138] gather op added --- paddle/operators/gather.h | 2 ++ paddle/operators/gather_op.cc | 8 ++------ python/paddle/v2/framework/tests/test_gather_op.py | 7 ++++--- 3 files changed, 8 insertions(+), 9 deletions(-) diff --git a/paddle/operators/gather.h b/paddle/operators/gather.h index d6e6990394..3f299ea1a6 100644 --- a/paddle/operators/gather.h +++ b/paddle/operators/gather.h @@ -17,6 +17,8 @@ limitations under the License. */ #include #include "paddle/framework/ddim.h" +#include "paddle/framework/eigen.h" +#include "paddle/framework/op_registry.h" #include "paddle/framework/tensor.h" #include "paddle/platform/place.h" diff --git a/paddle/operators/gather_op.cc b/paddle/operators/gather_op.cc index 2e08ba8dcc..499def05a7 100644 --- a/paddle/operators/gather_op.cc +++ b/paddle/operators/gather_op.cc @@ -24,13 +24,9 @@ class GatherOp : public framework::OperatorWithKernel { protected: void InferShape(const framework::InferShapeContext &ctx) const override { - // PADDLE_ENFORCE(ctx.InputSize() == 2, ""); - // PADDLE_ENFORCE(ctx.OutputSize() == 1, ""); - // PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(0), - // "Inputs of GatherOp must all be set"); int batch_size = ctx.Input("Index")->dims()[0]; - PADDLE_ENFORCE(batch_size > 0); - paddle::framework::DDim output_dims(ctx.Input(0)->dims()); + PADDLE_ENFORCE_GE(batch_size, 0, "Batch size must be >0"); + paddle::framework::DDim output_dims(ctx.Input("X")->dims()); output_dims[0] = batch_size; ctx.Output("Y")->Resize(output_dims); } diff --git a/python/paddle/v2/framework/tests/test_gather_op.py b/python/paddle/v2/framework/tests/test_gather_op.py index 2ffbf17236..049054d07b 100644 --- a/python/paddle/v2/framework/tests/test_gather_op.py +++ b/python/paddle/v2/framework/tests/test_gather_op.py @@ -12,11 +12,12 @@ class TestGatherOp(unittest.TestCase): def setUp(self): self.type = "gather" + xnp = numpy.random.random((10, 20)).astype("float32") self.inputs = { - 'X': numpy.random.random((10, 20)).astype("float32"), - 'Index': numpy.array([1, 3, 5]).astype("int") + 'X': xnp, + 'Index': numpy.array([1, 3, 5]).astype("int32") } - self.outputs = {'Y': self.input['X'][self.input['Index']]} + self.outputs = {'Y': self.inputs['X'][self.inputs['Index']]} if __name__ == "__main__": From 02299813685a7172d9e9182631b71473b492c904 Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Wed, 16 Aug 2017 23:54:38 +0000 Subject: [PATCH 028/138] remove empty test --- paddle/framework/CMakeLists.txt | 2 -- paddle/framework/empty_test.cc | 56 --------------------------------- 2 files changed, 58 deletions(-) delete mode 100644 paddle/framework/empty_test.cc diff --git a/paddle/framework/CMakeLists.txt b/paddle/framework/CMakeLists.txt index 68b5cec2c5..2cdf323c53 100644 --- a/paddle/framework/CMakeLists.txt +++ b/paddle/framework/CMakeLists.txt @@ -10,8 +10,6 @@ cc_test(eigen_test SRCS eigen_test.cc DEPS tensor) cc_library(lod_tensor SRCS lod_tensor.cc DEPS ddim place tensor) cc_test(lod_tensor_test SRCS lod_tensor_test.cc DEPS lod_tensor) -cc_test(empty_test SRCS empty_test.cc DEPS tensor) - cc_test(variable_test SRCS variable_test.cc) cc_library(scope SRCS scope.cc) diff --git a/paddle/framework/empty_test.cc b/paddle/framework/empty_test.cc deleted file mode 100644 index 2237f8ce0e..0000000000 --- a/paddle/framework/empty_test.cc +++ /dev/null @@ -1,56 +0,0 @@ -/* - Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - Licensed under the Apache License, Version 2.0 (the "License"); - you may not use this file except in compliance with the License. - You may obtain a copy of the License at - http://www.apache.org/licenses/LICENSE-2.0 - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the License for the specific language governing permissions and - limitations under the License. -*/ - -#include -#include -#include "paddle/framework/tensor.h" - -TEST(Empty, Dims) { - using namespace paddle::framework; - using namespace paddle::platform; - Tensor tt; - tt.Resize(make_ddim({0, 3, 4})); - DDim dims = tt.dims(); - ASSERT_EQ(arity(dims), 3); - EXPECT_EQ(0, dims[0]); - EXPECT_EQ(3, dims[1]); - EXPECT_EQ(4, dims[2]); -} - -TEST(Empty, MutableData) { - using namespace paddle::framework; - using namespace paddle::platform; - { - Tensor src_tensor; - float* p1 = nullptr; - // initialization - p1 = src_tensor.mutable_data(make_ddim({0, 2, 3}), CPUPlace()); - EXPECT_NE(p1, nullptr); - } - -#ifndef PADDLE_ONLY_CPU - { - Tensor src_tensor; - float* p1 = nullptr; - float* p2 = nullptr; - // initialization - p1 = src_tensor.mutable_data(make_ddim({0, 2, 3}), GPUPlace()); - EXPECT_NE(p1, nullptr); - // set src_tensor a new dim with large size - // momery is supposed to be re-allocated - p2 = src_tensor.mutable_data(make_ddim({0, 4}), GPUPlace()); - EXPECT_NE(p2, nullptr); - // EXPECT_NE(p1, p2); - } -#endif -} From 53b0e427092219b402f0ed6fab4235c3b70fdc7c Mon Sep 17 00:00:00 2001 From: hedaoyuan Date: Thu, 17 Aug 2017 16:19:59 +0800 Subject: [PATCH 029/138] Add EigenGemm. --- paddle/function/EigenGemm.cpp | 92 ++++++++++++++++++++++++++++++ paddle/function/GemmFunctor.cpp | 85 ++++++++++++++++++++++++++++ paddle/function/GemmFunctor.h | 99 +++++++++++---------------------- 3 files changed, 211 insertions(+), 65 deletions(-) create mode 100644 paddle/function/EigenGemm.cpp create mode 100644 paddle/function/GemmFunctor.cpp diff --git a/paddle/function/EigenGemm.cpp b/paddle/function/EigenGemm.cpp new file mode 100644 index 0000000000..0b4220fcbe --- /dev/null +++ b/paddle/function/EigenGemm.cpp @@ -0,0 +1,92 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include +#include "unsupported/Eigen/CXX11/Tensor" + +namespace paddle { + +template +struct EigenBlasGemm { + typedef Eigen::TensorMap, + Eigen::Aligned> + Matrix; + + static void compute(const bool transA, + const bool transB, + const int M, + const int N, + const int K, + const T alpha, + const T* A, + const int lda, + const T* B, + const int ldb, + const T beta, + T* C, + const int ldc) { + Eigen::array sizeA; + if (transA) { + sizeA[0] = K; + sizeA[1] = M; + CHECK_EQ(M, lda); + } else { + sizeA[0] = M; + sizeA[1] = K; + CHECK_EQ(K, lda); + } + Eigen::array sizeB; + if (transB) { + sizeB[0] = N; + sizeB[1] = K; + CHECK_EQ(K, ldb); + } else { + sizeB[0] = K; + sizeB[1] = N; + CHECK_EQ(N, ldb); + } + Eigen::array sizeC; + sizeC[0] = M; + sizeC[1] = N; + CHECK_EQ(N, ldc); + + const Matrix a(const_cast(A), sizeA); + const Matrix b(const_cast(B), sizeB); + Matrix c(C, sizeC); + + typedef typename Eigen::Tensor::DimensionPair DimPair; + Eigen::array dims; + dims[0] = DimPair(1, 0); + dims[0].first = transA ? 0 : 1; + dims[0].second = transB ? 1 : 0; + + Eigen::DefaultDevice device; + if (alpha == T(1) && beta == T(0)) { + c.device(device) = a.contract(b, dims); + } else if (alpha == T(1) && beta == T(1)) { + c.device(device) += a.contract(b, dims); + } else { + c.device(device) = + c.constant(alpha) * a.contract(b, dims) + c.constant(beta) * c; + } + } +}; + +#ifdef PADDLE_TYPE_DOUBLE +template class EigenBlasGemm; +#else +template class EigenBlasGemm; +#endif + +} // namespace paddle diff --git a/paddle/function/GemmFunctor.cpp b/paddle/function/GemmFunctor.cpp new file mode 100644 index 0000000000..8df9b884fe --- /dev/null +++ b/paddle/function/GemmFunctor.cpp @@ -0,0 +1,85 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "GemmFunctor.h" +#include "paddle/math/MathFunctions.h" + +namespace paddle { + +template +struct BlasGemm { + static void compute(const bool transA, + const bool transB, + const int M, + const int N, + const int K, + const T alpha, + const T* A, + const int lda, + const T* B, + const int ldb, + const T beta, + T* C, + const int ldc) { + gemm(transA == false ? CblasNoTrans : CblasTrans, + transB == false ? CblasNoTrans : CblasTrans, + M, + N, + K, + alpha, + A, + lda, + B, + ldb, + beta, + C, + ldc); + } +}; + +template +struct BlasGemm { + static void compute(const bool transA, + const bool transB, + const int M, + const int N, + const int K, + const T alpha, + const T* A, + const int lda, + const T* B, + const int ldb, + const T beta, + T* C, + const int ldc) { + hl_matrix_mul((T*)A, + transA == false ? HPPL_OP_N : HPPL_OP_T, + (T*)B, + transB == false ? HPPL_OP_N : HPPL_OP_T, + C, + M, + N, + K, + alpha, + beta, + lda, + ldb, + ldc); + } +}; + +template class BlasGemm; +template class BlasGemm; + +} // namespace paddle diff --git a/paddle/function/GemmFunctor.h b/paddle/function/GemmFunctor.h index d5db5cf5e7..0809953b4e 100644 --- a/paddle/function/GemmFunctor.h +++ b/paddle/function/GemmFunctor.h @@ -14,7 +14,7 @@ limitations under the License. */ #pragma once -#include "paddle/math/MathFunctions.h" +#include "TensorType.h" namespace paddle { @@ -24,73 +24,42 @@ namespace paddle { // of MatMulFunction, we need to consider the reconstruction of hl_matrix_mul // interface. template -class GemmFunctor { -public: - void operator()(const CBLAS_TRANSPOSE transA, - const CBLAS_TRANSPOSE TransB, - const int M, - const int N, - const int K, - const T alpha, - const T* A, - const int lda, - const T* B, - const int ldb, - const T beta, - T* C, - const int ldc); +struct BlasGemm { + static void compute(const bool transA, + const bool transB, + const int M, + const int N, + const int K, + const T alpha, + const T* A, + const int lda, + const T* B, + const int ldb, + const T beta, + T* C, + const int ldc); }; +// TODO(hedaoyuan): Since the definition of the real type in the Paddle +// conflicts with the Eigen library, so compile the Eigen code can not +// include the Paddle header file. And need an EigenBlasGemm template class +// that does not contain the DeviceType parameter. +// I will fix this problem and merge BlasGemm and EigenBlasGemm into one. template -class GemmFunctor { -public: - void operator()(const CBLAS_TRANSPOSE transA, - const CBLAS_TRANSPOSE TransB, - const int M, - const int N, - const int K, - const T alpha, - const T* A, - const int lda, - const T* B, - const int ldb, - const T beta, - T* C, - const int ldc) { - gemm(transA, TransB, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc); - } -}; - -template -class GemmFunctor { -public: - void operator()(const CBLAS_TRANSPOSE transA, - const CBLAS_TRANSPOSE TransB, - const int M, - const int N, - const int K, - const T alpha, - const T* A, - const int lda, - const T* B, - const int ldb, - const T beta, - T* C, - const int ldc) { - hl_matrix_mul((T*)A, - transA == CblasNoTrans ? HPPL_OP_N : HPPL_OP_T, - (T*)B, - TransB == CblasNoTrans ? HPPL_OP_N : HPPL_OP_T, - C, - M, - N, - K, - alpha, - beta, - lda, - ldb, - ldc); - } +struct EigenBlasGemm { + static void compute(const bool transA, + const bool transB, + const int M, + const int N, + const int K, + const T alpha, + const T* A, + const int lda, + const T* B, + const int ldb, + const T beta, + T* C, + const int ldc); }; } // namespace paddle From ec2ba242060fc10b2045533fdcb410cfbd473cec Mon Sep 17 00:00:00 2001 From: hedaoyuan Date: Thu, 17 Aug 2017 16:22:30 +0800 Subject: [PATCH 030/138] Fix GemmConvFunction. --- paddle/function/CMakeLists.txt | 2 + paddle/function/GemmConvOp.cpp | 82 ++++++++++++++++------------------ 2 files changed, 41 insertions(+), 43 deletions(-) diff --git a/paddle/function/CMakeLists.txt b/paddle/function/CMakeLists.txt index 7dfb6f61c5..9187294a49 100644 --- a/paddle/function/CMakeLists.txt +++ b/paddle/function/CMakeLists.txt @@ -4,6 +4,8 @@ file(GLOB cpp_files . *Op.cpp) list(APPEND h_files Function.h) list(APPEND cpp_files Function.cpp) list(APPEND cpp_files BufferArg.cpp) +list(APPEND cpp_files GemmFunctor.cpp) +list(APPEND cpp_files EigenGemm.cpp) if(WITH_GPU) file(GLOB cu_files . *OpGpu.cu) diff --git a/paddle/function/GemmConvOp.cpp b/paddle/function/GemmConvOp.cpp index 0ada4d70a0..f8cf4ebea8 100644 --- a/paddle/function/GemmConvOp.cpp +++ b/paddle/function/GemmConvOp.cpp @@ -85,7 +85,6 @@ public: } Im2ColFunctor im2col; - GemmFunctor gemm; size_t inputOffset = imShape.getElements(); size_t outputOffset = (outputChannels / groups_) * outputHeight * outputWidth; @@ -108,19 +107,19 @@ public: int M = outputChannels / groups_; int N = outputHeight * outputWidth; int K = inputChannels / groups_ * filterHeight * filterWidth; - gemm(CblasNoTrans, - CblasNoTrans, - M, - N, - K, - 1.0f, - filterData + g * filterOffset, - K, - colData, - N, - beta, - outputData + g * outputOffset, - N); + BlasGemm::compute(false, + false, + M, + N, + K, + 1.0f, + filterData + g * filterOffset, + K, + colData, + N, + beta, + outputData + g * outputOffset, + N); } inputData += inputChannels * inputHeight * inputWidth; outputData += outputChannels * outputHeight * outputWidth; @@ -188,8 +187,6 @@ public: } Col2ImFunctor col2im; - GemmFunctor gemm; - size_t inputOffset = imShape.getElements(); size_t outputOffset = (outputChannels / groups_) * outputHeight * outputWidth; @@ -205,19 +202,19 @@ public: colData = inputGrad + g * inputOffset; scale = 1.0f; } - gemm(CblasTrans, - CblasNoTrans, - M, - N, - K, - 1.0f, - filterData + g * filterOffset, - M, - outputGrad + g * outputOffset, - N, - scale, - colData, - N); + BlasGemm::compute(true, + false, + M, + N, + K, + 1.0f, + filterData + g * filterOffset, + M, + outputGrad + g * outputOffset, + N, + scale, + colData, + N); if (needIm2col) { col2im(inputGrad + g * inputOffset, imShape, @@ -299,7 +296,6 @@ public: } Im2ColFunctor im2col; - GemmFunctor gemm; size_t inputOffset = imShape.getElements(); size_t outputOffset = (outputChannels / groups_) * outputHeight * outputWidth; @@ -321,19 +317,19 @@ public: int M = outputChannels / groups_; int K = outputHeight * outputWidth; int N = inputChannels / groups_ * filterHeight * filterWidth; - gemm(CblasNoTrans, - CblasTrans, - M, - N, - K, - 1.0f, - outputGrad + g * outputOffset, - K, - colData, - K, - i == 0 ? beta : 1.0f, - filterGrad + g * filterOffset, - N); + BlasGemm::compute(false, + true, + M, + N, + K, + 1.0f, + outputGrad + g * outputOffset, + K, + colData, + K, + i == 0 ? beta : 1.0f, + filterGrad + g * filterOffset, + N); } inputData += inputChannels * inputHeight * inputWidth; outputGrad += outputChannels * outputHeight * outputWidth; From adcca2cc064182cd75809dd1e3d8c64329a0b0de Mon Sep 17 00:00:00 2001 From: hedaoyuan Date: Thu, 17 Aug 2017 16:40:38 +0800 Subject: [PATCH 031/138] Add PADDLE_USE_EIGEN_FOR_BLAS macro. --- CMakeLists.txt | 1 + cmake/configure.cmake | 4 ++++ paddle/function/GemmFunctor.cpp | 5 +++++ 3 files changed, 10 insertions(+) diff --git a/CMakeLists.txt b/CMakeLists.txt index dcd1218a5b..28bbfd7916 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -55,6 +55,7 @@ option(WITH_C_API "Compile PaddlePaddle with C-API(Prediction)" OFF) option(WITH_GOLANG "Compile PaddlePaddle with GOLANG" OFF) option(GLIDE_INSTALL "Download and install go dependencies " ON) option(USE_NNPACK "Compile PaddlePaddle with NNPACK library" OFF) +option(USE_EIGEN_FOR_BLAS "Use matrix multiplication in Eigen" OFF) # CMAKE_BUILD_TYPE if(NOT CMAKE_BUILD_TYPE) diff --git a/cmake/configure.cmake b/cmake/configure.cmake index 209f9078a6..51c3b918cc 100644 --- a/cmake/configure.cmake +++ b/cmake/configure.cmake @@ -28,6 +28,10 @@ if(NOT WITH_TIMER) add_definitions(-DPADDLE_DISABLE_TIMER) endif(NOT WITH_TIMER) +if(USE_EIGEN_FOR_BLAS) + add_definitions(-DPADDLE_USE_EIGEN_FOR_BLAS) +endif(USE_EIGEN_FOR_BLAS) + if(NOT WITH_PROFILER) add_definitions(-DPADDLE_DISABLE_PROFILER) endif(NOT WITH_PROFILER) diff --git a/paddle/function/GemmFunctor.cpp b/paddle/function/GemmFunctor.cpp index 8df9b884fe..dc83278d8e 100644 --- a/paddle/function/GemmFunctor.cpp +++ b/paddle/function/GemmFunctor.cpp @@ -32,6 +32,10 @@ struct BlasGemm { const T beta, T* C, const int ldc) { +#ifdef PADDLE_USE_EIGEN_FOR_BLAS + EigenBlasGemm::compute( + transA, transB, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc); +#else gemm(transA == false ? CblasNoTrans : CblasTrans, transB == false ? CblasNoTrans : CblasTrans, M, @@ -45,6 +49,7 @@ struct BlasGemm { beta, C, ldc); +#endif } }; From 6ba04dcd112e0caac46a7a829182ce00f301752f Mon Sep 17 00:00:00 2001 From: hedaoyuan Date: Thu, 17 Aug 2017 16:56:46 +0800 Subject: [PATCH 032/138] Remove the header files that do not need to be included. --- paddle/function/DepthwiseConvOp.cpp | 1 - paddle/function/DepthwiseConvOpGpu.cu | 1 - 2 files changed, 2 deletions(-) diff --git a/paddle/function/DepthwiseConvOp.cpp b/paddle/function/DepthwiseConvOp.cpp index 490e8d546c..2f3112fe65 100644 --- a/paddle/function/DepthwiseConvOp.cpp +++ b/paddle/function/DepthwiseConvOp.cpp @@ -14,7 +14,6 @@ limitations under the License. */ #include "DepthwiseConvOp.h" #include "ConvOp.h" -#include "GemmFunctor.h" namespace paddle { diff --git a/paddle/function/DepthwiseConvOpGpu.cu b/paddle/function/DepthwiseConvOpGpu.cu index 33463805cb..2d722dfcfc 100644 --- a/paddle/function/DepthwiseConvOpGpu.cu +++ b/paddle/function/DepthwiseConvOpGpu.cu @@ -13,7 +13,6 @@ See the License for the specific language governing permissions and limitations under the License. */ #include "DepthwiseConvOp.h" -#include "GemmFunctor.h" #include "paddle/math/BaseMatrix.h" namespace paddle { From e28e007373fca4faae6301f10b7c58e36153aec7 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Thu, 17 Aug 2017 18:41:23 +0800 Subject: [PATCH 033/138] Enable test_sgd_op --- python/paddle/v2/framework/tests/CMakeLists.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/python/paddle/v2/framework/tests/CMakeLists.txt b/python/paddle/v2/framework/tests/CMakeLists.txt index 96fad9b42e..faeac69513 100644 --- a/python/paddle/v2/framework/tests/CMakeLists.txt +++ b/python/paddle/v2/framework/tests/CMakeLists.txt @@ -25,3 +25,4 @@ py_test(test_operator SRCS test_operator.py) # py_test(test_gaussian_random_op SRCS test_gaussian_random_op.py) py_test(test_uniform_random_op SRCS test_uniform_random_op.py) py_test(test_recurrent_op SRCS test_recurrent_op.py) +py_test(test_sgd_op SRCS test_sgd_op.py) From 7d2ef02a993a378921a006d3575a802e5e9c5e9d Mon Sep 17 00:00:00 2001 From: guosheng Date: Thu, 17 Aug 2017 21:18:58 +0800 Subject: [PATCH 034/138] Add ScaleShiftLayer --- doc/api/v2/config/layer.rst | 5 + paddle/gserver/layers/ScaleShiftLayer.cpp | 106 ++++++++++++++++++ paddle/gserver/tests/test_LayerGrad.cpp | 15 +++ python/paddle/trainer/config_parser.py | 14 +++ .../paddle/trainer_config_helpers/layers.py | 37 ++++++ .../tests/configs/file_list.sh | 2 +- .../protostr/test_scale_shift_layer.protostr | 72 ++++++++++++ .../tests/configs/test_scale_shift_layer.py | 11 ++ 8 files changed, 261 insertions(+), 1 deletion(-) create mode 100644 paddle/gserver/layers/ScaleShiftLayer.cpp create mode 100644 python/paddle/trainer_config_helpers/tests/configs/protostr/test_scale_shift_layer.protostr create mode 100644 python/paddle/trainer_config_helpers/tests/configs/test_scale_shift_layer.py diff --git a/doc/api/v2/config/layer.rst b/doc/api/v2/config/layer.rst index cb330ea5e1..a4a843c610 100644 --- a/doc/api/v2/config/layer.rst +++ b/doc/api/v2/config/layer.rst @@ -362,6 +362,11 @@ trans .. autoclass:: paddle.v2.layer.trans :noindex: +scale_shift +----------- +.. autoclass:: paddle.v2.layer.scale_shift + :noindex: + Sampling Layers =============== diff --git a/paddle/gserver/layers/ScaleShiftLayer.cpp b/paddle/gserver/layers/ScaleShiftLayer.cpp new file mode 100644 index 0000000000..4f5b1c6225 --- /dev/null +++ b/paddle/gserver/layers/ScaleShiftLayer.cpp @@ -0,0 +1,106 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "Layer.h" + +namespace paddle { + +/** + * A layer does scaling and shifting to the input by appling a slope and + * an intercept which are trainable to the input element-wise. + * + * \f[ + * y = wx + b + * \f] + * + * Here, w is scale and b is offset, which are scalars and trainable. + * + */ + +class ScaleShiftLayer : public Layer { +protected: + std::unique_ptr scale_; + std::unique_ptr offset_; + +public: + explicit ScaleShiftLayer(const LayerConfig& config) : Layer(config) {} + + bool init(const LayerMap& layerMap, + const ParameterMap& parameterMap) override; + + void forward(PassType passType) override; + void backward(const UpdateCallback& callback = nullptr) override; +}; + +REGISTER_LAYER(scale_shift, ScaleShiftLayer); + +bool ScaleShiftLayer::init(const LayerMap& layerMap, + const ParameterMap& parameterMap) { + Layer::init(layerMap, parameterMap); + CHECK_EQ(inputLayers_.size(), 1U); + scale_.reset(new Weight(1, 1, parameters_[0])); + if (biasParameter_.get() != NULL) { + offset_ = std::unique_ptr(new Weight(1, 1, biasParameter_)); + } + return true; +} + +void ScaleShiftLayer::forward(PassType passType) { + Layer::forward(passType); + + MatrixPtr inV = getInputValue(0); + resetOutput(inV->getHeight(), inV->getWidth()); + MatrixPtr outV = getOutputValue(); + real scaleValue = scale_->getW()->getElement(0, 0); + outV->mulScalar(*inV, scaleValue); + if (offset_) { + real offsetValue = offset_->getW()->getElement(0, 0); + outV->add(offsetValue); + } +} + +void ScaleShiftLayer::backward(const UpdateCallback& callback) { + MatrixPtr inV = getInputValue(0); + MatrixPtr inG = getInputGrad(0); + MatrixPtr outV = getOutputValue(); + MatrixPtr outG = getOutputGrad(); + + /* Calculate the parameter gradient for the current layer */ + if (scale_->getWGrad()) { + MatrixPtr rowSumMtx; + Matrix::resizeOrCreate(rowSumMtx, outG->getHeight(), 1, false, useGpu_); + // this_i = scaleDest * this_i + scaleSum * \sum_j b_{ij} * c_{ij} + rowSumMtx->sumOfProducts( + /* b= */ *inV, /* c= */ *outG, /* scaleSum= */ 1, /* scaleDest= */ 0.); + // this_i = scaleDest * this_i + scaleSum * \sum_j b_{ji} + scale_->getWGrad()->sumCols( + /* b= */ *rowSumMtx, /* scaleSum= */ 1., /* scaleDest= */ 1.); + scale_->getParameterPtr()->incUpdate(callback); + } + if (offset_ && offset_->getWGrad()) { + MatrixPtr rowSumMtx; + Matrix::resizeOrCreate(rowSumMtx, outG->getHeight(), 1, false, useGpu_); + rowSumMtx->sumRows(*outG, 1., 0.); + offset_->getWGrad()->sumCols(*rowSumMtx, 1., 1.); + offset_->getParameterPtr()->incUpdate(callback); + } + + /* Calculate the input layers error */ + if (inG) { + real scaleValue = scale_->getW()->getElement(0, 0); + inG->add(*outG, scaleValue); + } +} + +} // namespace paddle diff --git a/paddle/gserver/tests/test_LayerGrad.cpp b/paddle/gserver/tests/test_LayerGrad.cpp index 0f312b6ca5..65429ebada 100644 --- a/paddle/gserver/tests/test_LayerGrad.cpp +++ b/paddle/gserver/tests/test_LayerGrad.cpp @@ -2007,6 +2007,21 @@ TEST(Layer, RowL2NormLayer) { } } +TEST(Layer, ScaleShiftLayer) { + const size_t batchSize = 128; + const size_t size = 512; + TestConfig config; + config.layerConfig.set_type("scale_shift"); + config.layerConfig.set_size(size); + config.biasSize = 1; + config.inputDefs.push_back( + {INPUT_DATA, "input", /* dim= */ size, /* paraSize= */ 1}); + config.layerConfig.add_inputs(); + for (auto useGpu : {false, true}) { + testLayerGrad(config, "scale_shift", batchSize, false, useGpu, false); + } +} + int main(int argc, char** argv) { testing::InitGoogleTest(&argc, argv); initMain(argc, argv); diff --git a/python/paddle/trainer/config_parser.py b/python/paddle/trainer/config_parser.py index da99e5bd53..8d71629faa 100644 --- a/python/paddle/trainer/config_parser.py +++ b/python/paddle/trainer/config_parser.py @@ -2232,6 +2232,20 @@ class ClipLayer(LayerBase): self.config.inputs[0].clip_conf.max = max +@config_layer('scale_shift') +class ScaleShiftLayer(LayerBase): + def __init__(self, name, inputs, bias=True, **xargs): + super(ScaleShiftLayer, self).__init__( + name, 'scale_shift', 0, inputs=inputs, **xargs) + config_assert( + len(self.inputs) == 1, + 'ScaleShiftLayer must have one and only one input.') + input_layer = self.get_input_layer(0) + self.set_layer_size(input_layer.size) + self.create_input_parameter(0, 1, [1, 1]) + self.create_bias_parameter(bias, 1) + + # key: cost type # value: cost class g_cost_map = {} diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py index 1bc55c8696..4c7217024a 100755 --- a/python/paddle/trainer_config_helpers/layers.py +++ b/python/paddle/trainer_config_helpers/layers.py @@ -133,6 +133,7 @@ __all__ = [ 'clip_layer', 'slice_projection', 'kmax_sequence_score_layer', + 'scale_shift_layer', ] @@ -230,6 +231,7 @@ class LayerType(object): CLIP_LAYER = 'clip' KMAX_SEQ_SCORE = 'kmax_seq_score' + SCALE_SHIFT_LAYER = 'scale_shift' @staticmethod def is_layer_type(type_name): @@ -6210,3 +6212,38 @@ def kmax_sequence_score_layer(input, name=None, beam_size=1): return LayerOutput( name, LayerType.KMAX_SEQ_SCORE, parents=[input], size=input.size) + + +@wrap_name_default("scale_shift") +@wrap_param_attr_default() +@wrap_bias_attr_default() +def scale_shift_layer(input, name=None, param_attr=None, bias_attr=None): + """ + A layer does scaling and shifting to the input by appling a slope and + an intercept which are trainable to the input element-wise. + .. math:: + + y = w * x + b + + .. code-block:: python + + scale_shift = scale_shift_layer(input=input_layer, bias_attr=False) + + :param name: The Layer Name. + :type name: basestring + :param input: The input layer. + :type input: LayerOutput. + :param param_attr: The parameter attribute of scaling. + :type param_attr: ParameterAttribute + :param bias_attr: The parameter attribute of shifting. + :type bias_attr: ParameterAttribute + :return: LayerOutput object. + :rtype: LayerOutput + """ + Layer( + name=name, + type=LayerType.SCALE_SHIFT_LAYER, + inputs=Input(input.name, **param_attr.attr), + bias=ParamAttr.to_bias(bias_attr)) + return LayerOutput( + name, LayerType.SCALE_SHIFT_LAYER, parents=[input], size=input.size) diff --git a/python/paddle/trainer_config_helpers/tests/configs/file_list.sh b/python/paddle/trainer_config_helpers/tests/configs/file_list.sh index a61beb871a..3860699f6f 100755 --- a/python/paddle/trainer_config_helpers/tests/configs/file_list.sh +++ b/python/paddle/trainer_config_helpers/tests/configs/file_list.sh @@ -8,6 +8,6 @@ test_spp_layer test_bilinear_interp test_maxout test_bi_grumemory math_ops test_seq_concat_reshape test_pad test_smooth_l1 test_multiplex_layer test_prelu_layer test_row_conv test_detection_output_layer test_multibox_loss_layer test_recursive_topology test_gated_unit_layer test_clip_layer test_row_l2_norm_layer -test_kmax_seq_socre_layer test_seq_select_layers) +test_kmax_seq_socre_layer test_seq_select_layers test_scale_shift_layer) export whole_configs=(test_split_datasource) diff --git a/python/paddle/trainer_config_helpers/tests/configs/protostr/test_scale_shift_layer.protostr b/python/paddle/trainer_config_helpers/tests/configs/protostr/test_scale_shift_layer.protostr new file mode 100644 index 0000000000..efaf20f8a7 --- /dev/null +++ b/python/paddle/trainer_config_helpers/tests/configs/protostr/test_scale_shift_layer.protostr @@ -0,0 +1,72 @@ +type: "nn" +layers { + name: "data" + type: "data" + size: 100 + active_type: "" +} +layers { + name: "__scale_shift_0__" + type: "scale_shift" + size: 100 + active_type: "" + inputs { + input_layer_name: "data" + input_parameter_name: "___scale_shift_0__.w0" + } + bias_parameter_name: "___scale_shift_0__.wbias" +} +layers { + name: "__scale_shift_1__" + type: "scale_shift" + size: 100 + active_type: "" + inputs { + input_layer_name: "data" + input_parameter_name: "___scale_shift_1__.w0" + } +} +parameters { + name: "___scale_shift_0__.w0" + size: 1 + initial_mean: 0.0 + initial_std: 1.0 + dims: 1 + dims: 1 + initial_strategy: 0 + initial_smart: true +} +parameters { + name: "___scale_shift_0__.wbias" + size: 1 + initial_mean: 0.0 + initial_std: 0.0 + dims: 1 + dims: 1 + initial_strategy: 0 + initial_smart: false +} +parameters { + name: "___scale_shift_1__.w0" + size: 1 + initial_mean: 0.0 + initial_std: 1.0 + dims: 1 + dims: 1 + initial_strategy: 0 + initial_smart: true +} +input_layer_names: "data" +output_layer_names: "__scale_shift_0__" +output_layer_names: "__scale_shift_1__" +sub_models { + name: "root" + layer_names: "data" + layer_names: "__scale_shift_0__" + layer_names: "__scale_shift_1__" + input_layer_names: "data" + output_layer_names: "__scale_shift_0__" + output_layer_names: "__scale_shift_1__" + is_recurrent_layer_group: false +} + diff --git a/python/paddle/trainer_config_helpers/tests/configs/test_scale_shift_layer.py b/python/paddle/trainer_config_helpers/tests/configs/test_scale_shift_layer.py new file mode 100644 index 0000000000..818d71f15d --- /dev/null +++ b/python/paddle/trainer_config_helpers/tests/configs/test_scale_shift_layer.py @@ -0,0 +1,11 @@ +from paddle.trainer_config_helpers import * + +settings(batch_size=1000, learning_rate=1e-5) + +data = data_layer(name='data', size=100) + +scale = scale_shift_layer(input=data) + +scale_shift = scale_shift_layer(input=data, bias_attr=False) + +outputs(scale, scale_shift) From a107181beae437705c561a245a102d7909d45d0d Mon Sep 17 00:00:00 2001 From: haonanyu Date: Thu, 17 Aug 2017 13:19:16 -0700 Subject: [PATCH 035/138] fix EXTERNAL_LIBS in CMakeLists.txt --- CMakeLists.txt | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/CMakeLists.txt b/CMakeLists.txt index dcd1218a5b..06dd5a1332 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -137,9 +137,9 @@ set(EXTERNAL_LIBS ) if(WITH_GPU) - list(APPEND EXTERNAL_LIB ${CUDA_LIBRARIES} ${CUDA_rt_LIBRARY}) + list(APPEND EXTERNAL_LIBS ${CUDA_LIBRARIES} ${CUDA_rt_LIBRARY}) if(NOT WITH_DSO) - list(APPEND EXTERNAL_LIB ${CUDNN_LIBRARY} ${CUDA_CUBLAS_LIBRARIES} ${CUDA_curand_LIBRARY}) + list(APPEND EXTERNAL_LIBS ${CUDNN_LIBRARY} ${CUDA_CUBLAS_LIBRARIES} ${CUDA_curand_LIBRARY}) endif(NOT WITH_DSO) endif(WITH_GPU) From 7b4b9d3e093de159bf7a9bfd91ef0e48a4756da0 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Thu, 17 Aug 2017 15:46:26 -0700 Subject: [PATCH 036/138] "format style" --- paddle/operators/mul_op.cc | 4 ++-- paddle/operators/mul_op.h | 2 ++ 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/paddle/operators/mul_op.cc b/paddle/operators/mul_op.cc index 5645df6677..329ab95327 100644 --- a/paddle/operators/mul_op.cc +++ b/paddle/operators/mul_op.cc @@ -66,10 +66,10 @@ class MulOpGrad : public framework::OperatorWithKernel { PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"), "Input(Y) should not be null"); PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Out")), "Input(Out@GRAD) should not be null"); + auto x_dims = ctx.Output("X")->dims(); + auto y_dims = ctx.Output("Y")->dims(); auto *x_grad = ctx.Output(framework::GradVarName("X")); auto *y_grad = ctx.Output(framework::GradVarName("Y")); - auto x_dims = ctx.Output(framework::GradVarName("X"))->dims(); - auto y_dims = ctx.Output(framework::GradVarName("Y"))->dims(); auto out_dims = ctx.Input(framework::GradVarName("Out"))->dims(); PADDLE_ENFORCE(x_dims[0] == out_dims[0], "Out@GRAD M X N must equal to X dims 0, M "); diff --git a/paddle/operators/mul_op.h b/paddle/operators/mul_op.h index 2afed81842..9bbd027526 100644 --- a/paddle/operators/mul_op.h +++ b/paddle/operators/mul_op.h @@ -53,7 +53,9 @@ class MulGradKernel : public framework::OpKernel { auto* dY = ctx.Output(framework::GradVarName("Y")); auto* device_context = const_cast(ctx.device_context_); + // dX = dOut' * Y. dX: M x K, dOut : M x N, Y : K x N math::matmul(*dOut, false, *Y, true, 1, dX, 0, device_context); + // dY = X' * dOut. dY: K x N, dOut : M x N, X : M x K math::matmul(*X, true, *dOut, false, 1, dY, 0, device_context); } }; From c332e4ee25ca28f307c1d3ccbcec9458fd25f5b3 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Thu, 17 Aug 2017 16:12:27 -0700 Subject: [PATCH 037/138] "relauch the ci" --- paddle/operators/rowwise_add_op.cc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/operators/rowwise_add_op.cc b/paddle/operators/rowwise_add_op.cc index 15192d90be..82e5df591d 100644 --- a/paddle/operators/rowwise_add_op.cc +++ b/paddle/operators/rowwise_add_op.cc @@ -73,7 +73,7 @@ class RowwiseAddGradOp : public framework::OperatorWithKernel { namespace ops = paddle::operators; REGISTER_OP(rowwise_add, ops::RowwiseAddOp, ops::RowwiseAddOpMaker, - rowwise_add_grad); + rowwise_add_grad, ops::RowwiseAddGradOp); REGISTER_OP_CPU_KERNEL( rowwise_add, ops::RowwiseAddKernel); REGISTER_OP_CPU_KERNEL( From 50cf127eea23e8771c17844cf09becec61004e96 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Thu, 17 Aug 2017 17:12:23 -0700 Subject: [PATCH 038/138] "change Output to Input" --- paddle/operators/mul_op.cc | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/paddle/operators/mul_op.cc b/paddle/operators/mul_op.cc index 329ab95327..460e458ca4 100644 --- a/paddle/operators/mul_op.cc +++ b/paddle/operators/mul_op.cc @@ -66,11 +66,11 @@ class MulOpGrad : public framework::OperatorWithKernel { PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"), "Input(Y) should not be null"); PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Out")), "Input(Out@GRAD) should not be null"); - auto x_dims = ctx.Output("X")->dims(); - auto y_dims = ctx.Output("Y")->dims(); + auto x_dims = ctx.Input("X")->dims(); + auto y_dims = ctx.Input("Y")->dims(); + auto out_dims = ctx.Input(framework::GradVarName("Out"))->dims(); auto *x_grad = ctx.Output(framework::GradVarName("X")); auto *y_grad = ctx.Output(framework::GradVarName("Y")); - auto out_dims = ctx.Input(framework::GradVarName("Out"))->dims(); PADDLE_ENFORCE(x_dims[0] == out_dims[0], "Out@GRAD M X N must equal to X dims 0, M "); PADDLE_ENFORCE(y_dims[1] == out_dims[1], From cef27dab47b430ce4034cfcfedf0c6bc95266f51 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Thu, 17 Aug 2017 19:14:27 -0700 Subject: [PATCH 039/138] "add fixl" --- paddle/operators/rowwise_add_op.cc | 1 + python/paddle/v2/framework/tests/test_rowwise_add_op.py | 4 +--- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/paddle/operators/rowwise_add_op.cc b/paddle/operators/rowwise_add_op.cc index 82e5df591d..f07dd8f602 100644 --- a/paddle/operators/rowwise_add_op.cc +++ b/paddle/operators/rowwise_add_op.cc @@ -63,6 +63,7 @@ class RowwiseAddGradOp : public framework::OperatorWithKernel { "Input(Out@GRAD) should not be null"); auto dims0 = ctx.Input("X")->dims(); auto dims1 = ctx.Input("b")->dims(); + PADDLE_ENFORCE_EQ(1, framework::product(dims1), "b dims should be 1") ctx.Output(framework::GradVarName("X"))->Resize(dims0); ctx.Output(framework::GradVarName("b"))->Resize(dims1); } diff --git a/python/paddle/v2/framework/tests/test_rowwise_add_op.py b/python/paddle/v2/framework/tests/test_rowwise_add_op.py index 8118d2d741..29d72e8500 100644 --- a/python/paddle/v2/framework/tests/test_rowwise_add_op.py +++ b/python/paddle/v2/framework/tests/test_rowwise_add_op.py @@ -21,12 +21,10 @@ class RowwiseAddGradOpTest(GradientChecker): op = create_op("rowwise_add") inputs = { "X": np.random.uniform(0.1, 1, [10, 10]).astype("float32"), - "b": np.random.uniform(0.1, 1, [10, 1]).astype("float32") + "b": np.random.uniform(0.1, 1, [10]).astype("float32") } self.check_grad(op, inputs, set(["X", "b"]), "Out") -#TODO(dzh): rowwise_grad check - if __name__ == '__main__': unittest.main() From 8b3d33a055b2a1556adedeb41a16b794249a3848 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Thu, 17 Aug 2017 20:10:44 -0700 Subject: [PATCH 040/138] fix-sgd --- paddle/operators/sgd_op.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/operators/sgd_op.h b/paddle/operators/sgd_op.h index bfb449d0b0..a0b5000ffb 100644 --- a/paddle/operators/sgd_op.h +++ b/paddle/operators/sgd_op.h @@ -30,7 +30,7 @@ class SGDOpKernel : public framework::OpKernel { void Compute(const framework::ExecutionContext& ctx) const override { auto param = ctx.Input("param"); auto grad = ctx.Input("grad"); - auto param_out = ctx.Output(0); + auto param_out = ctx.Output("param_out"); float lr = ctx.op_.GetAttr("learning_rate"); param_out->mutable_data(ctx.GetPlace()); From 46d30ec680f494e4cc30a73330074497da064fbd Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Thu, 17 Aug 2017 20:34:02 -0700 Subject: [PATCH 041/138] init minst.py --- python/paddle/v2/framework/tests/mnist.py | 140 ++++++++++++++++++++++ 1 file changed, 140 insertions(+) create mode 100644 python/paddle/v2/framework/tests/mnist.py diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py new file mode 100644 index 0000000000..32a088ac28 --- /dev/null +++ b/python/paddle/v2/framework/tests/mnist.py @@ -0,0 +1,140 @@ +import paddle.v2.framework.core as core +from paddle.v2.framework.op import Operator +import numpy + +BATCH_SIZE = 100 + +scope = core.Scope() +place = core.CPUPlace() +dev_ctx = core.DeviceContext.create(place) + +# init_net = core.Net.create() +forward_network = core.Net.create() + +# should be init after forward_op is constructed +# backward_net = core.Operator.backward(forward_net, set()) +backward_net = None +optimize_net = core.Net.create() + + +def atom_id(): + id = 0 + while True: + yield id + id += 1 + + +uniq_id = atom_id().next + + +def data_layer(name, dims): + var = scope.new_var(name) + tensor = var.get_tensor() + tensor.set_dims(dims) # 1 is batch size holder. + return name + + +def feed_data(name, data): + assert isinstance(data, numpy.array) + tensor = scope.find_var(name).get_tensor() + tensor.set_dims(data.shape) + tensor.alloc_float(place) + tensor.set(data, place) + + +def grad_var_name(var_name): + return var_name + "@GRAD" + + +def sgd_optimizer(net, param_name, learning_rate=0.01): + grad_name = grad_var_name(param_name) + optimize_op = Operator( + "sgd", param=param_name, grad=grad_name, learning_rate=learning_rate) + net.add_op(optimize_op) + + +# should use operator and add these to the init_network +def init_param(param_name, dims): + print param_name + var = scope.new_var(param_name) + tensor = var.get_tensor() + tensor.set_dims(dims) + data = numpy.random.uniform( + low=0.0, high=1.0, size=tensor.shape()).astype("float32") + tensor.set(data, place) + + +# fc_layer +def fc_layer(net, input, size, act="sigmoid", bias=True, param=None, name=None): + """ + Add a fc layer to net + + :param input: input variable name. + :type input: str + :param size: fully connected layer size. + :param act: activation name + :param param: parameter attribute, used for initialize parameters. + :param bias: bias attribute. False will not have a bias. + :param name: the name of fc layer. If not set, model will generate a + readable name + :return: output variable name. + """ + if name is None: + name = 'fc_%d' % uniq_id() + if not isinstance(name, str): + raise ValueError("name should be string") + + input_dims = scope.find_var(input).get_tensor().get_dims() + + w_name = param or name + ".w" + init_param(param_name=w_name, dims=[input_dims[1], size]) + sgd_optimizer(net=optimize_net, param_name=w_name, learning_rate=0.01) + + pre_activation = name + ".mul.out" + scope.new_var(pre_activation) + mul_op = Operator("mul", X=input, Y=w_name, Out=pre_activation) + net.add_op(mul_op) + + # create bias variable if needed + if bias: + bias_name = name + ".b" + init_param(param_name=bias_name, dims=[size]) + sgd_optimizer( + net=optimize_net, param_name=bias_name, learning_rate=0.01) + bias_out = name + ".rowwise_add.out" + scope.new_var(bias_out) + rowwise_add_op = Operator( + "rowwise_add", X=pre_activation, b=bias_name, Out=bias_out) + net.add_op(rowwise_add_op) + pre_activation = bias_out + + activation_op = Operator(act, X=pre_activation, Y=name) + net.add_op(activation_op) + scope.new_var(name) + net.infer_shape(scope) + return name + + +def cross_entropy_layer(net, input, label): + cost_name = 'cross_entropy_%d' % uniq_id() + cross_entropy_op = Operator( + "onehot_cross_entropy", X=input, label=label, Y=cost_name) + net.add_op(cross_entropy_op) + scope.new_var(cost_name) + net.infer_shape(scope) + return cost_name + + +images = data_layer(name='pixel', dims=[BATCH_SIZE, 784]) +label = data_layer(name='label', dims=[BATCH_SIZE]) +fc = fc_layer(net=forward_network, input=images, size=10, act="softmax") +cost = cross_entropy_layer(net=forward_network, input=fc, label=label) +forward_network.complete_add_op(True) +print(forward_network) +backward_net = core.Operator.backward(forward_network, set()) + +print(backward_net) + +PASS_NUM = 10 +for pass_id in range(PASS_NUM): + print pass_id From 55437b58b9b91d543f3498c3913a75bfb1122d6f Mon Sep 17 00:00:00 2001 From: liaogang Date: Fri, 18 Aug 2017 14:36:17 +0800 Subject: [PATCH 042/138] Add ENVIRONMENT interface interface --- paddle/memory/memory.cc | 10 +++++ paddle/memory/memory.h | 1 - paddle/platform/CMakeLists.txt | 3 +- paddle/platform/environment.h | 59 +++++++++++++++++++++++++++++ paddle/platform/environment_test.cc | 54 ++++++++++++++++++++++++++ paddle/platform/gpu_info.cc | 10 +++++ paddle/platform/gpu_info.h | 4 ++ 7 files changed, 139 insertions(+), 2 deletions(-) create mode 100644 paddle/platform/environment.h create mode 100644 paddle/platform/environment_test.cc diff --git a/paddle/memory/memory.cc b/paddle/memory/memory.cc index c99cc54156..0f46e1b8ea 100644 --- a/paddle/memory/memory.cc +++ b/paddle/memory/memory.cc @@ -18,8 +18,13 @@ limitations under the License. */ #include // for memcpy #include // for call_once +#include "glog/logging.h" + #include "paddle/memory/detail/buddy_allocator.h" #include "paddle/memory/detail/system_allocator.h" +#include "paddle/platform/gpu_info.h" + +DECLARE_double(fraction_of_gpu_memory_to_use); namespace paddle { namespace memory { @@ -79,6 +84,11 @@ BuddyAllocator* GetGPUBuddyAllocator(int gpu_id) { platform::GpuMinChunkSize(), platform::GpuMaxChunkSize())); } + VLOG(3) << "\n\nNOTE: each GPU device use " + << FLAGS_fraction_of_gpu_memory_to_use * 100 << "% of GPU memory.\n" + << "You can set environment variable '" + << platform::kEnvFractionGpuMemoryToUse + << "' to change the fraction of GPU usage.\n\n"; }); platform::SetDeviceId(gpu_id); diff --git a/paddle/memory/memory.h b/paddle/memory/memory.h index 72351b9dfa..11bbb88187 100644 --- a/paddle/memory/memory.h +++ b/paddle/memory/memory.h @@ -14,7 +14,6 @@ limitations under the License. */ #pragma once -#include "paddle/platform/gpu_info.h" #include "paddle/platform/place.h" namespace paddle { diff --git a/paddle/platform/CMakeLists.txt b/paddle/platform/CMakeLists.txt index acfc063973..120eb1e4af 100644 --- a/paddle/platform/CMakeLists.txt +++ b/paddle/platform/CMakeLists.txt @@ -1,7 +1,7 @@ cc_library(cpu_info SRCS cpu_info.cc DEPS gflags glog) cc_test(cpu_info_test SRCS cpu_info_test.cc DEPS cpu_info) -nv_library(gpu_info SRCS gpu_info.cc DEPS gflags) +nv_library(gpu_info SRCS gpu_info.cc DEPS gflags glog) cc_library(place SRCS place.cc) cc_test(place_test SRCS place_test.cc DEPS place glog gflags) @@ -9,6 +9,7 @@ cc_test(place_test SRCS place_test.cc DEPS place glog gflags) add_subdirectory(dynload) cc_test(enforce_test SRCS enforce_test.cc DEPS stringpiece) +cc_test(environment_test SRCS environment_test.cc DEPS stringpiece) IF(WITH_GPU) set(GPU_CTX_DEPS dynload_cuda dynamic_loader) diff --git a/paddle/platform/environment.h b/paddle/platform/environment.h new file mode 100644 index 0000000000..b868de4892 --- /dev/null +++ b/paddle/platform/environment.h @@ -0,0 +1,59 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#pragma once + +#include +#include + +#include "paddle/platform/enforce.h" +#include "paddle/string/piece.h" + +extern char** environ; + +namespace paddle { +namespace platform { + +inline void SetEnvVariable(const std::string& name, const std::string& value) { + PADDLE_ENFORCE_NE(setenv(name.c_str(), value.c_str(), 1), -1, + "Failed to set environment variable %s=%s", name, value); +} + +inline void UnsetEnvVariable(const std::string& name) { + PADDLE_ENFORCE_NE(unsetenv(name.c_str()), -1, + "Failed to unset environment variable %s", name); +} + +inline bool IsEnvVarDefined(const std::string& name) { + return std::getenv(name.c_str()) != nullptr; +} + +inline std::string GetEnvValue(const std::string& name) { + PADDLE_ENFORCE(IsEnvVarDefined(name), + "Tried to access undefined environment variable %s", name); + return std::getenv(name.c_str()); +} + +inline std::vector GetAllEnvVariables() { + std::vector vars; + for (auto var = environ; *var != nullptr; ++var) { + auto tail = string::Index(*var, "="); + auto name = string::SubStr(*var, 0, tail).ToString(); + vars.push_back(name); + } + return vars; +} + +} // namespace platform +} // namespace paddle diff --git a/paddle/platform/environment_test.cc b/paddle/platform/environment_test.cc new file mode 100644 index 0000000000..5f13652721 --- /dev/null +++ b/paddle/platform/environment_test.cc @@ -0,0 +1,54 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + http://www.apache.org/licenses/LICENSE-2.0 +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "paddle/platform/environment.h" + +#include "glog/logging.h" +#include "gtest/gtest.h" + +TEST(ENVIRONMENT, ACCESS) { + namespace platform = paddle::platform; + namespace string = paddle::string; + + platform::SetEnvVariable("PADDLE_USE_ENV", "TRUE"); + + EXPECT_TRUE(platform::IsEnvVarDefined("PADDLE_USE_ENV")); + EXPECT_EQ(platform::GetEnvValue("PADDLE_USE_ENV"), "TRUE"); + + platform::UnsetEnvVariable("PADDLE_USE_ENV"); + EXPECT_FALSE(platform::IsEnvVarDefined("PADDLE_USE_ENV")); + + platform::SetEnvVariable("PADDLE_USE_ENV1", "Hello "); + platform::SetEnvVariable("PADDLE_USE_ENV2", "World, "); + platform::SetEnvVariable("PADDLE_USE_ENV3", "PaddlePaddle!"); + + std::string env_info; + auto vars = platform::GetAllEnvVariables(); + for_each(vars.begin(), vars.end(), [&](const std::string& var) { + env_info += platform::GetEnvValue(var); + }); + + EXPECT_TRUE(string::Contains(env_info, "Hello World, PaddlePaddle!")); + platform::UnsetEnvVariable("PADDLE_USE_ENV1"); + platform::UnsetEnvVariable("PADDLE_USE_ENV2"); + platform::UnsetEnvVariable("PADDLE_USE_ENV3"); + + env_info.clear(); + vars = platform::GetAllEnvVariables(); + for_each(vars.begin(), vars.end(), [&](const std::string& var) { + env_info += platform::GetEnvValue(var); + }); + + EXPECT_FALSE(string::Contains(env_info, "Hello World, PaddlePaddle!")); + EXPECT_FALSE(platform::IsEnvVarDefined("PADDLE_USE_ENV1")); + EXPECT_FALSE(platform::IsEnvVarDefined("PADDLE_USE_ENV2")); + EXPECT_FALSE(platform::IsEnvVarDefined("PADDLE_USE_ENV3")); +} diff --git a/paddle/platform/gpu_info.cc b/paddle/platform/gpu_info.cc index edeb3ecd7b..be381a4e26 100644 --- a/paddle/platform/gpu_info.cc +++ b/paddle/platform/gpu_info.cc @@ -13,8 +13,11 @@ See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/platform/gpu_info.h" + #include "gflags/gflags.h" + #include "paddle/platform/enforce.h" +#include "paddle/platform/environment.h" DEFINE_double(fraction_of_gpu_memory_to_use, 0.95, "Default use 95% of GPU memory for PaddlePaddle," @@ -70,6 +73,13 @@ size_t GpuMaxChunkSize() { GpuMemoryUsage(available, total); + if (IsEnvVarDefined(kEnvFractionGpuMemoryToUse)) { + auto val = std::stod(GetEnvValue(kEnvFractionGpuMemoryToUse)); + PADDLE_ENFORCE_GT(val, 0.0); + PADDLE_ENFORCE_LE(val, 1.0); + FLAGS_fraction_of_gpu_memory_to_use = val; + } + // Reserving the rest memory for page tables, etc. size_t reserving = (1 - FLAGS_fraction_of_gpu_memory_to_use) * total; diff --git a/paddle/platform/gpu_info.h b/paddle/platform/gpu_info.h index d3a5f5f13f..6a99838241 100644 --- a/paddle/platform/gpu_info.h +++ b/paddle/platform/gpu_info.h @@ -18,10 +18,14 @@ limitations under the License. */ #include #include +#include namespace paddle { namespace platform { +//! Environment variable: fraction of GPU memory to use on each device. +const std::string kEnvFractionGpuMemoryToUse = "FRACTION_GPU_MEMORY_TO_USE"; + //! Get the total number of GPU devices in system. int GetDeviceCount(); From 3ec9ecb162d67b25adb7563381c9e693e3c6f306 Mon Sep 17 00:00:00 2001 From: liaogang Date: Fri, 18 Aug 2017 15:36:57 +0800 Subject: [PATCH 043/138] Fix conflicts with new declaration with 'C' linkage --- paddle/platform/environment.h | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/paddle/platform/environment.h b/paddle/platform/environment.h index b868de4892..9ed7653525 100644 --- a/paddle/platform/environment.h +++ b/paddle/platform/environment.h @@ -15,13 +15,12 @@ limitations under the License. */ #pragma once #include +#include #include #include "paddle/platform/enforce.h" #include "paddle/string/piece.h" -extern char** environ; - namespace paddle { namespace platform { @@ -46,6 +45,7 @@ inline std::string GetEnvValue(const std::string& name) { } inline std::vector GetAllEnvVariables() { + extern char** environ; std::vector vars; for (auto var = environ; *var != nullptr; ++var) { auto tail = string::Index(*var, "="); From 83d0016f54a79faa6cc8626283fd96eb3f704183 Mon Sep 17 00:00:00 2001 From: liaogang Date: Fri, 18 Aug 2017 15:49:10 +0800 Subject: [PATCH 044/138] Fix undefined reference --- paddle/platform/environment.h | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/paddle/platform/environment.h b/paddle/platform/environment.h index 9ed7653525..4edcce932e 100644 --- a/paddle/platform/environment.h +++ b/paddle/platform/environment.h @@ -21,6 +21,8 @@ limitations under the License. */ #include "paddle/platform/enforce.h" #include "paddle/string/piece.h" +extern char** environ; // for environment variables + namespace paddle { namespace platform { @@ -45,7 +47,6 @@ inline std::string GetEnvValue(const std::string& name) { } inline std::vector GetAllEnvVariables() { - extern char** environ; std::vector vars; for (auto var = environ; *var != nullptr; ++var) { auto tail = string::Index(*var, "="); From b3ab15a7abed52a7b70d74fd7b9642b2ca0ca7b1 Mon Sep 17 00:00:00 2001 From: liaogang Date: Fri, 18 Aug 2017 17:39:10 +0800 Subject: [PATCH 045/138] follow comments --- paddle/platform/gpu_info.h | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/paddle/platform/gpu_info.h b/paddle/platform/gpu_info.h index 6a99838241..ed2420b874 100644 --- a/paddle/platform/gpu_info.h +++ b/paddle/platform/gpu_info.h @@ -24,7 +24,8 @@ namespace paddle { namespace platform { //! Environment variable: fraction of GPU memory to use on each device. -const std::string kEnvFractionGpuMemoryToUse = "FRACTION_GPU_MEMORY_TO_USE"; +const std::string kEnvFractionGpuMemoryToUse = + "PADDLE_FRACTION_GPU_MEMORY_TO_USE"; //! Get the total number of GPU devices in system. int GetDeviceCount(); From 82b820e97b90f21d7b46629bba72436a69e888e1 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Fri, 18 Aug 2017 08:21:56 -0700 Subject: [PATCH 046/138] fix rowwise_add_grad_op --- paddle/operators/rowwise_add_op.cc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/operators/rowwise_add_op.cc b/paddle/operators/rowwise_add_op.cc index f07dd8f602..6825dce332 100644 --- a/paddle/operators/rowwise_add_op.cc +++ b/paddle/operators/rowwise_add_op.cc @@ -63,7 +63,7 @@ class RowwiseAddGradOp : public framework::OperatorWithKernel { "Input(Out@GRAD) should not be null"); auto dims0 = ctx.Input("X")->dims(); auto dims1 = ctx.Input("b")->dims(); - PADDLE_ENFORCE_EQ(1, framework::product(dims1), "b dims should be 1") + PADDLE_ENFORCE_EQ(1, dims1.size(), "b dims should be 1") ctx.Output(framework::GradVarName("X"))->Resize(dims0); ctx.Output(framework::GradVarName("b"))->Resize(dims1); } From 0cf5bdec563c4360f36c90ced8a73c7493874bf4 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Fri, 18 Aug 2017 14:24:24 -0700 Subject: [PATCH 047/138] "tensor mutable data" --- paddle/operators/mul_op.h | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/paddle/operators/mul_op.h b/paddle/operators/mul_op.h index 9bbd027526..8facc02814 100644 --- a/paddle/operators/mul_op.h +++ b/paddle/operators/mul_op.h @@ -51,9 +51,11 @@ class MulGradKernel : public framework::OpKernel { auto* dX = ctx.Output(framework::GradVarName("X")); auto* dY = ctx.Output(framework::GradVarName("Y")); + dX->mutable_data(ctx.GetPlace()); + dY->mutable_data(ctx.GetPlace()); auto* device_context = const_cast(ctx.device_context_); - // dX = dOut' * Y. dX: M x K, dOut : M x N, Y : K x N + // dX = dOut * Y'. dX: M x K, dOut : M x N, Y : K x N math::matmul(*dOut, false, *Y, true, 1, dX, 0, device_context); // dY = X' * dOut. dY: K x N, dOut : M x N, X : M x K math::matmul(*X, true, *dOut, false, 1, dY, 0, device_context); From 514398c0b17cb3b340ca05a885e1ed66c2405ea9 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Fri, 18 Aug 2017 15:04:04 -0700 Subject: [PATCH 048/138] "delete unused comment" --- paddle/operators/math/math_function.h | 9 --------- 1 file changed, 9 deletions(-) diff --git a/paddle/operators/math/math_function.h b/paddle/operators/math/math_function.h index c7c603929b..155589fadb 100644 --- a/paddle/operators/math/math_function.h +++ b/paddle/operators/math/math_function.h @@ -77,15 +77,6 @@ void matmul(const framework::Tensor& matrix_a, bool trans_a, framework::Tensor* matrix_out, T beta, platform::DeviceContext* context); -// // matrix multiply with continuous memory -// template -// void matmul(const framework::Tensor& matrix_a, bool trans_a, -// const framework::Tensor& matrix_b, bool trans_b, -// framework::Tensor* matrix_out, -// platform::DeviceContext* context) { -// matmul(matrix_a, matrix_b, trans_a, trans_b, 1, matrix_out, 0, context); -// } - } // namespace math } // namespace operators } // namespace paddle From b59002daef841d752bda2a46eeac446008f93a03 Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Fri, 18 Aug 2017 15:41:04 -0700 Subject: [PATCH 049/138] "fix math gemm lda order error" --- paddle/operators/math/math_function.cc | 8 ++++---- python/paddle/v2/framework/tests/test_mul_op.py | 4 +++- 2 files changed, 7 insertions(+), 5 deletions(-) diff --git a/paddle/operators/math/math_function.cc b/paddle/operators/math/math_function.cc index affdd1ac2c..1e86fc3d16 100644 --- a/paddle/operators/math/math_function.cc +++ b/paddle/operators/math/math_function.cc @@ -25,8 +25,8 @@ void gemm(const CBLAS_TRANSPOSE transA, const float alpha, const float* A, const float* B, const float beta, float* C, platform::DeviceContext* context) { - int lda = K; - int ldb = N; + int lda = (transA == CblasNoTrans) ? K : M; + int ldb = (transB == CblasNoTrans) ? N : K; int ldc = N; cblas_sgemm(CblasRowMajor, transA, transB, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc); @@ -40,8 +40,8 @@ void gemm(const CBLAS_TRANSPOSE transA, const double* B, const double beta, double* C, platform::DeviceContext* context) { - int lda = K; - int ldb = N; + int lda = (transA == CblasNoTrans) ? K : M; + int ldb = (transB == CblasNoTrans) ? N : K; int ldc = N; cblas_dgemm(CblasRowMajor, transA, transB, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc); diff --git a/python/paddle/v2/framework/tests/test_mul_op.py b/python/paddle/v2/framework/tests/test_mul_op.py index eef5a4f961..ee0d81a64e 100644 --- a/python/paddle/v2/framework/tests/test_mul_op.py +++ b/python/paddle/v2/framework/tests/test_mul_op.py @@ -23,7 +23,9 @@ class MulGradOpTest(GradientChecker): 'X': np.random.random((32, 84)).astype("float32"), 'Y': np.random.random((84, 100)).astype("float32") } - self.check_grad(op, inputs, set(["X", "Y"]), "Out") + # mul op will enlarge the relative error + self.check_grad( + op, inputs, set(["X", "Y"]), "Out", max_relative_error=0.5) # TODO(dzh,qijun) : mulgrad test case need transpose feature of blas library From 1eb98e2fef8f9264ed9110569748a7b42ca45eb4 Mon Sep 17 00:00:00 2001 From: Yi Wang Date: Fri, 18 Aug 2017 17:19:14 -0700 Subject: [PATCH 050/138] Set the default cuDNN installation path --- cmake/cudnn.cmake | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cmake/cudnn.cmake b/cmake/cudnn.cmake index 69f40df516..2c84061ff5 100644 --- a/cmake/cudnn.cmake +++ b/cmake/cudnn.cmake @@ -2,7 +2,7 @@ if(NOT WITH_GPU) return() endif() -set(CUDNN_ROOT "" CACHE PATH "CUDNN ROOT") +set(CUDNN_ROOT "/usr" CACHE PATH "CUDNN ROOT") find_path(CUDNN_INCLUDE_DIR cudnn.h PATHS ${CUDNN_ROOT} ${CUDNN_ROOT}/include $ENV{CUDNN_ROOT} $ENV{CUDNN_ROOT}/include ${CUDA_TOOLKIT_INCLUDE} From 8f6c8780a52b3e0a6df85f6d9e3e98366a381692 Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Sat, 19 Aug 2017 17:08:04 +0800 Subject: [PATCH 051/138] Replace functor by function. --- paddle/operators/cross_entropy_op.cu | 25 +++++++++---------- paddle/operators/cross_entropy_op.h | 2 +- .../paddle/v2/framework/tests/op_test_util.py | 2 +- 3 files changed, 14 insertions(+), 15 deletions(-) diff --git a/paddle/operators/cross_entropy_op.cu b/paddle/operators/cross_entropy_op.cu index 5f5d269267..d999bfce58 100644 --- a/paddle/operators/cross_entropy_op.cu +++ b/paddle/operators/cross_entropy_op.cu @@ -21,19 +21,18 @@ namespace operators { using Tensor = framework::Tensor; template -struct clipping_log { - __host__ __device__ T operator()(const T x) { - PADDLE_ASSERT(std::is_floating_point::value); - const T kApproInf = 1e20; - if (x == INFINITY) { - return kApproInf; - } - if (x == -INFINITY) { - return -kApproInf; - } - return x; +__host__ __device__ T clipping_log(const T x) { + PADDLE_ASSERT(std::is_floating_point::value); + const T kApproInf = 1e20; + T v = log(x); + if (v == INFINITY) { + return kApproInf; } -}; + if (v == -INFINITY) { + return -kApproInf; + } + return v; +} template __global__ void CrossEntropyKernel(T* Y, const T* X, const int* label, @@ -43,7 +42,7 @@ __global__ void CrossEntropyKernel(T* Y, const T* X, const int* label, for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < N; i += blockDim.x * gridDim.x) { PADDLE_ASSERT(label[i] >= 0 && label[i] < D); - Y[i] = -clipping_log()(X[i * D + label[i]]); + Y[i] = -clipping_log(X[i * D + label[i]]); } } diff --git a/paddle/operators/cross_entropy_op.h b/paddle/operators/cross_entropy_op.h index e95f5e1167..eb4d1348de 100644 --- a/paddle/operators/cross_entropy_op.h +++ b/paddle/operators/cross_entropy_op.h @@ -21,7 +21,7 @@ namespace operators { using Tensor = framework::Tensor; template -T tolerable_value(const T x) { +inline T tolerable_value(const T x) { static_assert(std::is_floating_point::value, "tolerable_value works only on float, " "double and double double."); diff --git a/python/paddle/v2/framework/tests/op_test_util.py b/python/paddle/v2/framework/tests/op_test_util.py index ae23108dfa..3bc05a0fec 100644 --- a/python/paddle/v2/framework/tests/op_test_util.py +++ b/python/paddle/v2/framework/tests/op_test_util.py @@ -65,7 +65,7 @@ class OpTestMeta(type): expect = self.outputs[out_name] self.assertTrue( numpy.allclose( - actual, expect, atol=1e-04), + actual, expect, atol=1e-05), "output name: " + out_name + "has diff") obj.test_all = test_all From f1e553354186c44508565ad89d4b526bdb3a705a Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Sun, 20 Aug 2017 13:57:26 +0800 Subject: [PATCH 052/138] Rename `Net::AddOp` to `Net::AppendOp` Fix #3582 --- paddle/framework/backward.cc | 9 +++--- paddle/framework/backward_test.cc | 30 +++++++++---------- paddle/framework/pybind.cc | 4 +-- paddle/operators/net_op.h | 7 +++-- paddle/operators/net_op_test.cc | 10 +++---- python/paddle/v2/framework/tests/test_net.py | 10 +++---- .../v2/framework/tests/test_recurrent_op.py | 2 +- 7 files changed, 37 insertions(+), 35 deletions(-) diff --git a/paddle/framework/backward.cc b/paddle/framework/backward.cc index 9d30887224..bfda18724c 100644 --- a/paddle/framework/backward.cc +++ b/paddle/framework/backward.cc @@ -110,7 +110,7 @@ static std::unique_ptr BackwardRecursive( dup_output_ops[out].emplace_back(local_op_id); return false; }); - net->AddOp(std::move(bwd)); + net->AppendOp(std::move(bwd)); } // Get unique ID for this method. auto uid = uniq_id++; @@ -163,8 +163,9 @@ static std::unique_ptr BackwardRecursive( // If part of input gradient of that operator is not calculated, fill // zero variables to that input gradient. - net->AddOp(OpRegistry::CreateOp("fill_zeros_like", {{"Src", {prefix}}}, - {{"Dst", {grad_input}}}, {})); + net->AppendOp(OpRegistry::CreateOp("fill_zeros_like", + {{"Src", {prefix}}}, + {{"Dst", {grad_input}}}, {})); } return false; }); @@ -195,7 +196,7 @@ static std::unique_ptr BackwardRecursive( if (net->ops_.empty()) { // Current no aux op is added to network return grad_op; } - net->AddOp(std::move(grad_op)); + net->AppendOp(std::move(grad_op)); } net->SetType("@GENERATED_BACKWARD@"); net->CompleteAddOp(); diff --git a/paddle/framework/backward_test.cc b/paddle/framework/backward_test.cc index 2c5ec76dfe..b93ab66f2f 100644 --- a/paddle/framework/backward_test.cc +++ b/paddle/framework/backward_test.cc @@ -75,13 +75,13 @@ class FcOp : public operators::NetOp { FcOp(const std::string &type, const VarNameMap &inputs, const VarNameMap &outputs, const AttributeMap &attrs) : NetOp(type, inputs, outputs, attrs) { - AddOp(OpRegistry::CreateOp("mul", - {{"X", {Input("X")}}, {"Y", {Input("W")}}}, - {{"Out", {Output("mul_result")}}}, {})); + AppendOp(OpRegistry::CreateOp("mul", + {{"X", {Input("X")}}, {"Y", {Input("W")}}}, + {{"Out", {Output("mul_result")}}}, {})); auto input_b = Inputs("b"); std::string before_act = "mul_result"; if (input_b.size() != 0) { - AddOp(OpRegistry::CreateOp( + AppendOp(OpRegistry::CreateOp( "rowwise_add", {{"X", {Output("mul_result")}}, {"b", {input_b[0]}}}, {{"Out", {Output("add_result")}}}, {})); before_act = "add_result"; @@ -92,8 +92,8 @@ class FcOp : public operators::NetOp { } } - AddOp(OpRegistry::CreateOp("sigmoid", {{"X", {Output(before_act)}}}, - {{"Out", {Output("Out")}}}, {})); + AppendOp(OpRegistry::CreateOp("sigmoid", {{"X", {Output(before_act)}}}, + {{"Out", {Output("Out")}}}, {})); CompleteAddOp(false); } }; @@ -234,13 +234,13 @@ TEST(Backward, net_fc_backward_not_have_b) { TEST(Backward, net_input_of_network_not_need_grad) { ops::NetOp net; - net.AddOp(f::OpRegistry::CreateOp( + net.AppendOp(f::OpRegistry::CreateOp( "fc", {{"X", {"x"}}, {"W", {"W1"}}, {"b", {"b1"}}}, {{"mul_result", {"mul_tmp_0"}}, {"add_result", {"add_tmp_0"}}, {"Out", {"hidden0"}}}, {})); - net.AddOp(f::OpRegistry::CreateOp( + net.AppendOp(f::OpRegistry::CreateOp( "fc", {{"X", {"hidden0"}}, {"W", {"W2"}}, {"b", {"b2"}}}, {{"mul_result", {"mul_tmp_1"}}, {"add_result", {"add_tmp_1"}}, @@ -273,10 +273,10 @@ TEST(Backward, net_input_of_network_not_need_grad) { TEST(Backward, net_shared_weight) { ops::NetOp net; - net.AddOp(f::OpRegistry::CreateOp("mul", {{"X", {"x"}}, {"Y", {"w"}}}, - {{"Out", {"out"}}}, {})); - net.AddOp(f::OpRegistry::CreateOp("mul", {{"X", {"out"}}, {"Y", {"w"}}}, - {{"Out", {"FinalOut"}}}, {})); + net.AppendOp(f::OpRegistry::CreateOp("mul", {{"X", {"x"}}, {"Y", {"w"}}}, + {{"Out", {"out"}}}, {})); + net.AppendOp(f::OpRegistry::CreateOp("mul", {{"X", {"out"}}, {"Y", {"w"}}}, + {{"Out", {"FinalOut"}}}, {})); net.CompleteAddOp(); auto bwd = f::Backward(net, {}); @@ -357,19 +357,19 @@ TEST(Backward, op_part_of_input_are_not_need) { TEST(Backward, linear_net_intermediate_variable_has_no_grad) { ops::NetOp net; - net.AddOp(f::OpRegistry::CreateOp( + net.AppendOp(f::OpRegistry::CreateOp( "fc", {{"X", {"x1"}}, {"W", {"w1"}}, {"b", {"b1"}}}, {{"mul_result", {"mul_out1"}}, {"add_result", {"add_out1"}}, {"Out", {"out1"}}}, {})); - net.AddOp(f::OpRegistry::CreateOp( + net.AppendOp(f::OpRegistry::CreateOp( "fc", {{"X", {"out1"}}, {"W", {"w2"}}, {"b", {"b2"}}}, {{"mul_result", {"mul_out2"}}, {"add_result", {"tmp_out2"}}, {"Out", {"out2"}}}, {})); - net.AddOp(f::OpRegistry::CreateOp( + net.AppendOp(f::OpRegistry::CreateOp( "fc", {{"X", {"out2"}}, {"W", {"w3"}}, {"b", {"b3"}}}, {{"mul_result", {"mul_out3"}}, {"add_result", {"tmp_out3"}}, diff --git a/paddle/framework/pybind.cc b/paddle/framework/pybind.cc index f0114b9e49..89219a77c3 100644 --- a/paddle/framework/pybind.cc +++ b/paddle/framework/pybind.cc @@ -222,8 +222,8 @@ All parameter, weight, gradient are variables in Paddle. retv->SetType("plain_net"); return retv; }) - .def("add_op", [](operators::NetOp &self, - const OperatorBase &op) { self.AddOp(op); }) + .def("append_op", [](operators::NetOp &self, + const OperatorBase &op) { self.AppendOp(op); }) .def("complete_add_op", &operators::NetOp::CompleteAddOp) .def("complete_add_op", [](std::shared_ptr &self) { self->CompleteAddOp(); diff --git a/paddle/operators/net_op.h b/paddle/operators/net_op.h index 885ac6eeca..3d3f996ef5 100644 --- a/paddle/operators/net_op.h +++ b/paddle/operators/net_op.h @@ -84,13 +84,14 @@ class NetOp : public framework::OperatorBase { return true; } - void AddOp(const framework::OperatorBase& op) { AddOp(op.Clone()); } + void AppendOp(const framework::OperatorBase& op) { AppendOp(op.Clone()); } /** * @brief Add an operator by ptr */ - void AddOp(std::unique_ptr op) { - PADDLE_ENFORCE(!add_op_done_, "Cannot AddOp when this network is sealed"); + void AppendOp(std::unique_ptr op) { + PADDLE_ENFORCE(!add_op_done_, + "Cannot AppendOp when this network is sealed"); PADDLE_ENFORCE_NOT_NULL(op, "Cannot Insert Null op"); ops_.push_back(std::move(op)); } diff --git a/paddle/operators/net_op_test.cc b/paddle/operators/net_op_test.cc index e9598610c0..99019754a9 100644 --- a/paddle/operators/net_op_test.cc +++ b/paddle/operators/net_op_test.cc @@ -38,10 +38,10 @@ TEST(OpKernel, all) { auto net = std::make_shared(); ASSERT_NE(net, nullptr); - net->AddOp(std::unique_ptr( + net->AppendOp(std::unique_ptr( new TestOp("test", {{"X", {"x"}}, {"W", {"w1"}}, {"b", {"b1"}}}, {{"Out", {"y"}}}, {}))); - net->AddOp(std::unique_ptr( + net->AppendOp(std::unique_ptr( new TestOp("test", {{"X", {"y"}}, {"W", {"w2"}}, {"b", {"b2"}}}, {{"Out", {"z"}}}, {}))); @@ -61,7 +61,7 @@ TEST(NetOp, insert_op) { auto op1 = std::unique_ptr( new framework::NOP("empty", {{"X", {"x"}}, {"W", {"w1"}}, {"b", {"b1"}}}, {{"Out", {"y"}}}, {})); - net.AddOp(*op1); + net.AppendOp(*op1); net.InsertOp(0, *op1); ASSERT_EQ(2UL, net.ops_.size()); net.InsertOp(2, std::move(op1)); @@ -70,9 +70,9 @@ TEST(NetOp, insert_op) { TEST(NetOp, Clone) { NetOp net; - net.AddOp( + net.AppendOp( std::unique_ptr(new framework::NOP{"empty", {}, {}, {}})); - net.AddOp(std::unique_ptr( + net.AppendOp(std::unique_ptr( new framework::NOP{"empty2", {}, {}, {}})); net.CompleteAddOp(true); auto new_net_op = net.Clone(); diff --git a/python/paddle/v2/framework/tests/test_net.py b/python/paddle/v2/framework/tests/test_net.py index b42cadd11a..9339cf28da 100644 --- a/python/paddle/v2/framework/tests/test_net.py +++ b/python/paddle/v2/framework/tests/test_net.py @@ -6,8 +6,8 @@ import unittest def fc(X, W, Y): ret_v = core.Net.create() - ret_v.add_op(Operator("mul", X="X", Y="W", Out="pre_activation")) - ret_v.add_op(Operator("sigmoid", X="pre_activation", Y=Y)) + ret_v.append_op(Operator("mul", X="X", Y="W", Out="pre_activation")) + ret_v.append_op(Operator("sigmoid", X="pre_activation", Y=Y)) ret_v.complete_add_op(True) return ret_v @@ -16,12 +16,12 @@ class TestNet(unittest.TestCase): def test_net_all(self): net = core.Net.create() op1 = Operator("add_two", X="X", Y="Y", Out="Out") - net.add_op(op1) + net.append_op(op1) net2 = core.Net.create() - net2.add_op(fc(X="X", W="w", Y="fc.out")) + net2.append_op(fc(X="X", W="w", Y="fc.out")) net2.complete_add_op(True) - net.add_op(net2) + net.append_op(net2) net.complete_add_op(True) expected = ''' diff --git a/python/paddle/v2/framework/tests/test_recurrent_op.py b/python/paddle/v2/framework/tests/test_recurrent_op.py index 3d4a34d8d7..d6000ab9f9 100644 --- a/python/paddle/v2/framework/tests/test_recurrent_op.py +++ b/python/paddle/v2/framework/tests/test_recurrent_op.py @@ -150,7 +150,7 @@ class TestRecurrentOp(unittest.TestCase): sig_op = Operator("sigmoid", X="sum", Y="h@alias") for op in [x_fc_op, h_fc_op, sum_op, sig_op]: - stepnet.add_op(op) + stepnet.append_op(op) stepnet.complete_add_op(True) self.rnnop.set_stepnet(stepnet) From 59b3df31aa3f960753bf0d0d922319124e04301e Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Sun, 20 Aug 2017 14:52:23 +0800 Subject: [PATCH 053/138] Extract OpInfo into a library Fix cycle dependencies, Fix #3583. --- paddle/framework/CMakeLists.txt | 4 +-- paddle/framework/backward_test.cc | 4 +-- paddle/framework/grad_op_builder.cc | 20 +++++++------- paddle/framework/op_info.cc | 30 +++++++++++++++++++++ paddle/framework/op_info.h | 42 +++++++++++++++++++++++++++++ paddle/framework/op_registry.cc | 37 +++++++++++++------------ paddle/framework/op_registry.h | 35 ++++++------------------ paddle/framework/operator.cc | 8 +++--- paddle/framework/operator.h | 27 ++++++++++--------- paddle/framework/operator_test.cc | 9 ++++--- paddle/framework/pybind.cc | 2 +- paddle/operators/net_op.cc | 5 ++-- paddle/operators/net_op.h | 6 +++-- paddle/operators/recurrent_op.cc | 8 +++--- paddle/operators/recurrent_op.h | 10 ++++--- 15 files changed, 152 insertions(+), 95 deletions(-) create mode 100644 paddle/framework/op_info.cc create mode 100644 paddle/framework/op_info.h diff --git a/paddle/framework/CMakeLists.txt b/paddle/framework/CMakeLists.txt index 68304c9fc8..59012ea8c1 100644 --- a/paddle/framework/CMakeLists.txt +++ b/paddle/framework/CMakeLists.txt @@ -18,8 +18,8 @@ cc_test(scope_test SRCS scope_test.cc DEPS scope) proto_library(framework_proto SRCS framework.proto) cc_library(attribute SRCS attribute.cc DEPS framework_proto) - -cc_library(operator SRCS operator.cc DEPS framework_proto device_context tensor scope attribute) +cc_library(op_info SRCS op_info.cc DEPS attribute framework_proto) +cc_library(operator SRCS operator.cc DEPS op_info device_context tensor scope) cc_test(operator_test SRCS operator_test.cc DEPS operator op_registry) cc_library(grad_op_builder SRCS grad_op_builder.cc DEPS operator) diff --git a/paddle/framework/backward_test.cc b/paddle/framework/backward_test.cc index 2c5ec76dfe..bcdfae132c 100644 --- a/paddle/framework/backward_test.cc +++ b/paddle/framework/backward_test.cc @@ -72,8 +72,8 @@ class NoGradOpMaker : public OpProtoAndCheckerMaker { class FcOp : public operators::NetOp { public: - FcOp(const std::string &type, const VarNameMap &inputs, - const VarNameMap &outputs, const AttributeMap &attrs) + FcOp(const std::string &type, const VariableNameMap &inputs, + const VariableNameMap &outputs, const AttributeMap &attrs) : NetOp(type, inputs, outputs, attrs) { AddOp(OpRegistry::CreateOp("mul", {{"X", {Input("X")}}, {"Y", {Input("W")}}}, diff --git a/paddle/framework/grad_op_builder.cc b/paddle/framework/grad_op_builder.cc index 0a2a41f6b6..fcc5d7a216 100644 --- a/paddle/framework/grad_op_builder.cc +++ b/paddle/framework/grad_op_builder.cc @@ -20,11 +20,11 @@ namespace framework { enum class OpArgType { IN, OUT }; static void TransOpArg(const OperatorBase* src_op, const OpArgType& src_type, - bool is_grad, OperatorBase::VarNameMap* vars) { + bool is_grad, VariableNameMap* vars) { const auto& src_inout = src_type == OpArgType::IN ? src_op->Inputs() : src_op->Outputs(); auto& dst_inout = *vars; - const OpProto* proto = OpRegistry::op_info_map().at(src_op->Type()).proto_; + const OpProto* proto = OpInfoMap().at(src_op->Type()).proto_; const auto& src_arg_list = src_type == OpArgType::IN ? proto->inputs() : proto->outputs(); for (const auto& arg : src_arg_list) { @@ -40,25 +40,25 @@ static void TransOpArg(const OperatorBase* src_op, const OpArgType& src_type, } OperatorBase* BuildGradOp(const OperatorBase* op) { - auto it = OpRegistry::op_info_map().find(op->Type()); - PADDLE_ENFORCE(it != OpRegistry::op_info_map().end(), - "'%s' has not been registered.", op->Type()); + auto it = OpInfoMap().find(op->Type()); + PADDLE_ENFORCE(it != OpInfoMap().end(), "'%s' has not been registered.", + op->Type()); PADDLE_ENFORCE(it->second.proto_ != nullptr, "'%s' has no OpProto.", op->Type()); std::string grad_op_type = it->second.grad_op_type_; PADDLE_ENFORCE(!grad_op_type.empty(), "'%s' has no gradient operator.", op->Type()); - OperatorBase::VarNameMap inputs; - OperatorBase::VarNameMap outputs; + VariableNameMap inputs; + VariableNameMap outputs; TransOpArg(op, OpArgType::IN, false, &inputs); // I TransOpArg(op, OpArgType::OUT, false, &inputs); // O TransOpArg(op, OpArgType::OUT, true, &inputs); // OG TransOpArg(op, OpArgType::IN, true, &outputs); // IG - it = OpRegistry::op_info_map().find(grad_op_type); - PADDLE_ENFORCE(it != OpRegistry::op_info_map().end(), - "'%s' has not been registered.", grad_op_type); + it = OpInfoMap().find(grad_op_type); + PADDLE_ENFORCE(it != OpInfoMap().end(), "'%s' has not been registered.", + grad_op_type); return it->second.creator_(grad_op_type, inputs, outputs, op->Attrs()); } diff --git a/paddle/framework/op_info.cc b/paddle/framework/op_info.cc new file mode 100644 index 0000000000..f928ac6473 --- /dev/null +++ b/paddle/framework/op_info.cc @@ -0,0 +1,30 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#include "paddle/framework/op_info.h" + +namespace paddle { +namespace framework { + +static std::unordered_map* + g_op_info_map = nullptr; +std::unordered_map& OpInfoMap() { + if (g_op_info_map == nullptr) { + g_op_info_map = + new std::unordered_map(); + } + return *g_op_info_map; +} +} // namespace framework +} // namespace paddle diff --git a/paddle/framework/op_info.h b/paddle/framework/op_info.h new file mode 100644 index 0000000000..fdd0ed77d4 --- /dev/null +++ b/paddle/framework/op_info.h @@ -0,0 +1,42 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#pragma once +#include +#include +#include +#include + +#include "paddle/framework/attribute.h" + +namespace paddle { +namespace framework { +class OperatorBase; +using VariableNameMap = std::map>; + +using OpCreator = std::function; + +struct OpInfo { + OpCreator creator_; + std::string grad_op_type_; + OpProto* proto_; + OpAttrChecker* checker_; +}; + +extern std::unordered_map& OpInfoMap(); + +} // namespace framework +} // namespace paddle diff --git a/paddle/framework/op_registry.cc b/paddle/framework/op_registry.cc index 8eae86e960..e03dc3a73d 100644 --- a/paddle/framework/op_registry.cc +++ b/paddle/framework/op_registry.cc @@ -19,32 +19,20 @@ limitations under the License. */ namespace paddle { namespace framework { -std::unique_ptr OpRegistry::CreateOp(const std::string& type, - const VarNameMap& inputs, - const VarNameMap& outputs, - AttributeMap attrs) { - auto it = op_info_map().find(type); - PADDLE_ENFORCE(it != op_info_map().end(), +std::unique_ptr OpRegistry::CreateOp( + const std::string& type, const VariableNameMap& inputs, + const VariableNameMap& outputs, AttributeMap attrs) { + auto it = OpInfoMap().find(type); + PADDLE_ENFORCE(it != OpInfoMap().end(), "Operator '%s' has not been registered.", type); it->second.checker_->Check(attrs); auto op = it->second.creator_(type, inputs, outputs, attrs); return std::unique_ptr(op); } -std::unique_ptr OpRegistry::CreateOp(const OpDesc& op_desc) { - VarNameMap inputs = ConvertOpDescVarsToVarNameMap(op_desc.inputs()); - VarNameMap outputs = ConvertOpDescVarsToVarNameMap(op_desc.outputs()); - AttributeMap attrs; - for (auto& attr : op_desc.attrs()) { - attrs[attr.name()] = GetAttrValue(attr); - } - - return CreateOp(op_desc.type(), inputs, outputs, attrs); -} - -OperatorBase::VarNameMap OpRegistry::ConvertOpDescVarsToVarNameMap( +static VariableNameMap ConvertOpDescVarsToVarNameMap( const google::protobuf::RepeatedPtrField& op_desc_vars) { - VarNameMap ret_val; + VariableNameMap ret_val; for (auto& var : op_desc_vars) { auto& var_names = ret_val[var.parameter()]; auto& var_names_in_proto = var.arguments(); @@ -55,6 +43,17 @@ OperatorBase::VarNameMap OpRegistry::ConvertOpDescVarsToVarNameMap( return ret_val; } +std::unique_ptr OpRegistry::CreateOp(const OpDesc& op_desc) { + VariableNameMap inputs = ConvertOpDescVarsToVarNameMap(op_desc.inputs()); + VariableNameMap outputs = ConvertOpDescVarsToVarNameMap(op_desc.outputs()); + AttributeMap attrs; + for (auto& attr : op_desc.attrs()) { + attrs[attr.name()] = GetAttrValue(attr); + } + + return CreateOp(op_desc.type(), inputs, outputs, attrs); +} + std::unique_ptr OpRegistry::CreateGradOp(const OperatorBase& op) { PADDLE_ENFORCE(!op.IsNetOp(), "Use framework::Backward to get backward ops"); return std::unique_ptr(BuildGradOp(&op)); diff --git a/paddle/framework/op_registry.h b/paddle/framework/op_registry.h index 4c2d13d639..06530bc7d0 100644 --- a/paddle/framework/op_registry.h +++ b/paddle/framework/op_registry.h @@ -23,6 +23,7 @@ limitations under the License. */ #include "paddle/framework/attribute.h" #include "paddle/framework/framework.pb.h" #include "paddle/framework/grad_op_builder.h" +#include "paddle/framework/op_info.h" #include "paddle/framework/operator.h" #include "paddle/framework/scope.h" @@ -30,28 +31,16 @@ namespace paddle { namespace framework { class OpRegistry { - using VarNameMap = OperatorBase::VarNameMap; - using OpCreator = std::function; - public: - struct OpInfo { - OpCreator creator_; - std::string grad_op_type_; - OpProto* proto_; - OpAttrChecker* checker_; - }; - template static void RegisterOp(const std::string& op_type, const std::string& grad_op_type) { - PADDLE_ENFORCE(op_info_map().count(op_type) == 0, + PADDLE_ENFORCE(OpInfoMap().count(op_type) == 0, "'%s' is registered more than once.", op_type); OpInfo op_info; - op_info.creator_ = [](const std::string& type, const VarNameMap& inputs, - const VarNameMap& outputs, - const AttributeMap& attrs) { + op_info.creator_ = []( + const std::string& type, const VariableNameMap& inputs, + const VariableNameMap& outputs, const AttributeMap& attrs) { return new OpType(type, inputs, outputs, attrs); }; op_info.grad_op_type_ = grad_op_type; @@ -70,7 +59,7 @@ class OpRegistry { op_info.proto_ = nullptr; op_info.checker_ = nullptr; } - op_info_map().insert(std::make_pair(op_type, op_info)); + OpInfoMap().insert(std::make_pair(op_type, op_info)); // register gradient op if (!grad_op_type.empty()) { RegisterOp(grad_op_type, ""); @@ -78,21 +67,13 @@ class OpRegistry { } static std::unique_ptr CreateOp(const std::string& type, - const VarNameMap& inputs, - const VarNameMap& outputs, + const VariableNameMap& inputs, + const VariableNameMap& outputs, AttributeMap attrs); static std::unique_ptr CreateOp(const OpDesc& op_desc); - static VarNameMap ConvertOpDescVarsToVarNameMap( - const google::protobuf::RepeatedPtrField& op_desc_vars); - static std::unique_ptr CreateGradOp(const OperatorBase& op); - - static std::unordered_map& op_info_map() { - static std::unordered_map op_info_map_; - return op_info_map_; - } }; class Registrar { diff --git a/paddle/framework/operator.cc b/paddle/framework/operator.cc index eadd8f3316..48a7fe64ac 100644 --- a/paddle/framework/operator.cc +++ b/paddle/framework/operator.cc @@ -115,8 +115,8 @@ void OperatorBase::Rename(const std::string& old_name, } OperatorBase::OperatorBase(const std::string& type, - const OperatorBase::VarNameMap& inputs, - const OperatorBase::VarNameMap& outputs, + const VariableNameMap& inputs, + const VariableNameMap& outputs, const AttributeMap& attrs) : type_(type), inputs_(inputs), outputs_(outputs), attrs_(attrs) { static std::atomic gUniqId(0UL); @@ -141,9 +141,9 @@ std::vector OperatorBase::OutputVars(bool has_intermediate) const { } return ret_val; } - auto it = OpRegistry::op_info_map().find(type_); + auto it = OpInfoMap().find(type_); PADDLE_ENFORCE( - it != OpRegistry::op_info_map().end(), + it != OpInfoMap().end(), "Operator %s not registered, cannot figure out intermediate outputs", type_); PADDLE_ENFORCE( diff --git a/paddle/framework/operator.h b/paddle/framework/operator.h index 8072980889..83dab8631d 100644 --- a/paddle/framework/operator.h +++ b/paddle/framework/operator.h @@ -19,6 +19,7 @@ limitations under the License. */ #include #include +#include "op_info.h" #include "paddle/framework/attribute.h" #include "paddle/framework/framework.pb.h" #include "paddle/framework/scope.h" @@ -62,10 +63,8 @@ class ExecutionContext; */ class OperatorBase { public: - using VarNameMap = std::map>; - - OperatorBase(const std::string& type, const VarNameMap& inputs, - const VarNameMap& outputs, const AttributeMap& attrs); + OperatorBase(const std::string& type, const VariableNameMap& inputs, + const VariableNameMap& outputs, const AttributeMap& attrs); virtual ~OperatorBase() {} @@ -93,8 +92,8 @@ class OperatorBase { /// rename inputs outputs name void Rename(const std::string& old_name, const std::string& new_name); - const VarNameMap& Inputs() const { return inputs_; } - const VarNameMap& Outputs() const { return outputs_; } + const VariableNameMap& Inputs() const { return inputs_; } + const VariableNameMap& Outputs() const { return outputs_; } //! Get a input with argument's name described in `op_proto` const std::string& Input(const std::string& name) const; //! Get a input which has multiple variables. @@ -122,11 +121,11 @@ class OperatorBase { // I (Inputs)opear // O (Outputs) // OG (Output Gradients) - VarNameMap inputs_; + VariableNameMap inputs_; // NOTE: in case of OpGrad, outputs_ contains // IG (Inputs Gradients) - VarNameMap outputs_; + VariableNameMap outputs_; AttributeMap attrs_; }; @@ -142,9 +141,11 @@ class OperatorBase { // You can also use // using PARENT_CLASS::PARENT_CLASS; // to use parent's constructor. -#define DEFINE_OP_CONSTRUCTOR(CLS, PARENT_CLS) \ - CLS(const std::string& type, const VarNameMap& inputs, \ - const VarNameMap& outputs, const paddle::framework::AttributeMap& attrs) \ +#define DEFINE_OP_CONSTRUCTOR(CLS, PARENT_CLS) \ + CLS(const std::string& type, \ + const ::paddle::framework::VariableNameMap& inputs, \ + const ::paddle::framework::VariableNameMap& outputs, \ + const paddle::framework::AttributeMap& attrs) \ : PARENT_CLS(type, inputs, outputs, attrs) {} class NOP : public OperatorBase { @@ -389,8 +390,8 @@ class OperatorWithKernel : public OperatorBase { using OpKernelMap = std::unordered_map, OpKernelHash>; - OperatorWithKernel(const std::string& type, const VarNameMap& inputs, - const VarNameMap& outputs, const AttributeMap& attrs) + OperatorWithKernel(const std::string& type, const VariableNameMap& inputs, + const VariableNameMap& outputs, const AttributeMap& attrs) : OperatorBase(type, inputs, outputs, attrs) {} void InferShape(const Scope& scope) const override { diff --git a/paddle/framework/operator_test.cc b/paddle/framework/operator_test.cc index 2425b87779..1d7efb7b94 100644 --- a/paddle/framework/operator_test.cc +++ b/paddle/framework/operator_test.cc @@ -23,8 +23,8 @@ static int op_run_num = 0; class OpWithoutKernelTest : public OperatorBase { public: - OpWithoutKernelTest(const std::string& type, const VarNameMap& inputs, - const VarNameMap& outputs, const AttributeMap& attrs) + OpWithoutKernelTest(const std::string& type, const VariableNameMap& inputs, + const VariableNameMap& outputs, const AttributeMap& attrs) : OperatorBase(type, inputs, outputs, attrs), x(1) {} void InferShape(const Scope& scope) const override {} void Run(const Scope& scope, @@ -249,8 +249,9 @@ TEST(OpKernel, multi_inputs) { class OperatorClone : public paddle::framework::OperatorBase { public: DEFINE_OP_CLONE_METHOD(OperatorClone); - OperatorClone(const std::string& type, const VarNameMap& inputs, - const VarNameMap& outputs, + OperatorClone(const std::string& type, + const paddle::framework::VariableNameMap& inputs, + const paddle::framework::VariableNameMap& outputs, const paddle::framework::AttributeMap& attrs) : OperatorBase(type, inputs, outputs, attrs) {} void InferShape(const paddle::framework::Scope& scope) const override {} diff --git a/paddle/framework/pybind.cc b/paddle/framework/pybind.cc index f0114b9e49..1aec483573 100644 --- a/paddle/framework/pybind.cc +++ b/paddle/framework/pybind.cc @@ -138,7 +138,7 @@ All parameter, weight, gradient are variables in Paddle. //! @note: Be careful! PyBind will return std::string as an unicode, not //! Python str. If you want a str object, you should cast them in Python. m.def("get_all_op_protos", []() -> std::vector { - auto &op_info_map = OpRegistry::op_info_map(); + auto &op_info_map = OpInfoMap(); std::vector ret_values; for (auto it = op_info_map.begin(); it != op_info_map.end(); ++it) { const OpProto *proto = it->second.proto_; diff --git a/paddle/operators/net_op.cc b/paddle/operators/net_op.cc index a7d7105110..9bfa712d98 100644 --- a/paddle/operators/net_op.cc +++ b/paddle/operators/net_op.cc @@ -81,9 +81,8 @@ std::vector NetOp::OutputVars(bool has_intermediate) const { return ret_val; } -NetOp::NetOp(const std::string& type, - const framework::OperatorBase::VarNameMap& inputs, - const framework::OperatorBase::VarNameMap& outputs, +NetOp::NetOp(const std::string& type, const framework::VariableNameMap& inputs, + const framework::VariableNameMap& outputs, const framework::AttributeMap& attrs) : framework::OperatorBase(type, inputs, outputs, attrs) {} diff --git a/paddle/operators/net_op.h b/paddle/operators/net_op.h index 885ac6eeca..05b475d88f 100644 --- a/paddle/operators/net_op.h +++ b/paddle/operators/net_op.h @@ -38,8 +38,10 @@ class NetOp : public framework::OperatorBase { public: static const char kAll[]; NetOp() : framework::OperatorBase("plain_net", {}, {}, {}) {} - NetOp(const std::string& type, const VarNameMap& inputs, - const VarNameMap& outputs, const framework::AttributeMap& attrs); + + NetOp(const std::string& type, const framework::VariableNameMap& inputs, + const framework::VariableNameMap& outputs, + const framework::AttributeMap& attrs); NetOp(const NetOp& o) : framework::OperatorBase(o.type_, {}, {}, o.attrs_) { this->ops_.reserve(o.ops_.size()); diff --git a/paddle/operators/recurrent_op.cc b/paddle/operators/recurrent_op.cc index 78ce0ba3c0..16bd249cb3 100644 --- a/paddle/operators/recurrent_op.cc +++ b/paddle/operators/recurrent_op.cc @@ -131,8 +131,8 @@ const rnn::ArgumentName RecurrentGradientOp::kArgName{ "memories", "pre_memories", "boot_memories@grad"}; RecurrentOp::RecurrentOp(const std::string& type, - const framework::OperatorBase::VarNameMap& inputs, - const framework::OperatorBase::VarNameMap& outputs, + const framework::VariableNameMap& inputs, + const framework::VariableNameMap& outputs, const framework::AttributeMap& attrs) : OperatorBase(type, inputs, outputs, attrs) { rnn::InitArgument(kArgName, &arg_, *this); @@ -223,8 +223,8 @@ void RecurrentGradientAlgorithm::InferShape(const Scope& scope) const { } RecurrentGradientOp::RecurrentGradientOp( - const std::string& type, const framework::OperatorBase::VarNameMap& inputs, - const framework::OperatorBase::VarNameMap& outputs, + const std::string& type, const framework::VariableNameMap& inputs, + const framework::VariableNameMap& outputs, const framework::AttributeMap& attrs) : OperatorBase(type, inputs, outputs, attrs) { rnn::InitArgument(kArgName, &arg_, *this); diff --git a/paddle/operators/recurrent_op.h b/paddle/operators/recurrent_op.h index bcfa817de8..1033d657a3 100644 --- a/paddle/operators/recurrent_op.h +++ b/paddle/operators/recurrent_op.h @@ -114,8 +114,9 @@ class RecurrentGradientAlgorithm { class RecurrentOp : public framework::OperatorBase { public: - RecurrentOp(const std::string& type, const VarNameMap& inputs, - const VarNameMap& outputs, const framework::AttributeMap& attrs); + RecurrentOp(const std::string& type, const framework::VariableNameMap& inputs, + const framework::VariableNameMap& outputs, + const framework::AttributeMap& attrs); RecurrentOp(const RecurrentOp& o) : framework::OperatorBase( @@ -150,8 +151,9 @@ class RecurrentOp : public framework::OperatorBase { class RecurrentGradientOp : public framework::OperatorBase { public: - RecurrentGradientOp(const std::string& type, const VarNameMap& inputs, - const VarNameMap& outputs, + RecurrentGradientOp(const std::string& type, + const framework::VariableNameMap& inputs, + const framework::VariableNameMap& outputs, const framework::AttributeMap& attrs); RecurrentGradientOp(const RecurrentGradientOp& o) From 7f6b5044b640edcbd77bbb368509569776f7e0ee Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Sun, 20 Aug 2017 15:28:00 +0800 Subject: [PATCH 054/138] Make OpInfoMap as a class * Add Get/Has methods to OpInfoMap * Add PADDLE_ENFORCE for OpInfo to get field. --- paddle/framework/grad_op_builder.cc | 20 +++------- paddle/framework/op_info.cc | 9 ++--- paddle/framework/op_info.h | 61 ++++++++++++++++++++++++++++- paddle/framework/op_registry.cc | 8 ++-- paddle/framework/op_registry.h | 4 +- paddle/framework/operator.cc | 12 +----- paddle/framework/pybind.cc | 17 ++++---- 7 files changed, 84 insertions(+), 47 deletions(-) diff --git a/paddle/framework/grad_op_builder.cc b/paddle/framework/grad_op_builder.cc index fcc5d7a216..b02a599a80 100644 --- a/paddle/framework/grad_op_builder.cc +++ b/paddle/framework/grad_op_builder.cc @@ -24,9 +24,9 @@ static void TransOpArg(const OperatorBase* src_op, const OpArgType& src_type, const auto& src_inout = src_type == OpArgType::IN ? src_op->Inputs() : src_op->Outputs(); auto& dst_inout = *vars; - const OpProto* proto = OpInfoMap().at(src_op->Type()).proto_; + auto& proto = OpInfoMap::Instance().Get(src_op->Type()).Proto(); const auto& src_arg_list = - src_type == OpArgType::IN ? proto->inputs() : proto->outputs(); + src_type == OpArgType::IN ? proto.inputs() : proto.outputs(); for (const auto& arg : src_arg_list) { if (arg.not_in_gradient() && !is_grad) continue; const std::string src_name = arg.name(); @@ -40,14 +40,8 @@ static void TransOpArg(const OperatorBase* src_op, const OpArgType& src_type, } OperatorBase* BuildGradOp(const OperatorBase* op) { - auto it = OpInfoMap().find(op->Type()); - PADDLE_ENFORCE(it != OpInfoMap().end(), "'%s' has not been registered.", - op->Type()); - PADDLE_ENFORCE(it->second.proto_ != nullptr, "'%s' has no OpProto.", - op->Type()); - std::string grad_op_type = it->second.grad_op_type_; - PADDLE_ENFORCE(!grad_op_type.empty(), "'%s' has no gradient operator.", - op->Type()); + auto& info = OpInfoMap::Instance().Get(op->Type()); + PADDLE_ENFORCE(info.HasGradientOp()); VariableNameMap inputs; VariableNameMap outputs; @@ -56,10 +50,8 @@ OperatorBase* BuildGradOp(const OperatorBase* op) { TransOpArg(op, OpArgType::OUT, true, &inputs); // OG TransOpArg(op, OpArgType::IN, true, &outputs); // IG - it = OpInfoMap().find(grad_op_type); - PADDLE_ENFORCE(it != OpInfoMap().end(), "'%s' has not been registered.", - grad_op_type); - return it->second.creator_(grad_op_type, inputs, outputs, op->Attrs()); + auto& grad_info = OpInfoMap::Instance().Get(info.grad_op_type_); + return grad_info.Creator()(info.grad_op_type_, inputs, outputs, op->Attrs()); } } // namespace framework diff --git a/paddle/framework/op_info.cc b/paddle/framework/op_info.cc index f928ac6473..81ba29797c 100644 --- a/paddle/framework/op_info.cc +++ b/paddle/framework/op_info.cc @@ -17,12 +17,11 @@ namespace paddle { namespace framework { -static std::unordered_map* - g_op_info_map = nullptr; -std::unordered_map& OpInfoMap() { +static OpInfoMap* g_op_info_map = nullptr; + +OpInfoMap& OpInfoMap::Instance() { if (g_op_info_map == nullptr) { - g_op_info_map = - new std::unordered_map(); + g_op_info_map = new OpInfoMap(); } return *g_op_info_map; } diff --git a/paddle/framework/op_info.h b/paddle/framework/op_info.h index fdd0ed77d4..94245c6c44 100644 --- a/paddle/framework/op_info.h +++ b/paddle/framework/op_info.h @@ -34,9 +34,68 @@ struct OpInfo { std::string grad_op_type_; OpProto* proto_; OpAttrChecker* checker_; + + bool HasOpProtoAndChecker() const { + return proto_ != nullptr && checker_ != nullptr; + } + + const OpProto& Proto() const { + PADDLE_ENFORCE_NOT_NULL(proto_, "Operator Proto has not been registered"); + PADDLE_ENFORCE(proto_->IsInitialized(), + "Operator Proto must be initialized in op info"); + return *proto_; + } + + const OpAttrChecker& Checker() const { + PADDLE_ENFORCE_NOT_NULL(checker_, + "Operator Checker has not been registered"); + return *checker_; + } + + const OpCreator& Creator() const { + PADDLE_ENFORCE_NOT_NULL(creator_, + "Operator Creator has not been registered"); + return creator_; + } + + bool HasGradientOp() const { return !grad_op_type_.empty(); } }; -extern std::unordered_map& OpInfoMap(); +class OpInfoMap { + public: + static OpInfoMap& Instance(); + + OpInfoMap(const OpInfoMap& o) = delete; + OpInfoMap(OpInfoMap&& o) = delete; + OpInfoMap& operator=(const OpInfoMap& o) = delete; + OpInfoMap& operator=(OpInfoMap&& o) = delete; + + bool Has(const std::string& op_type) const { + return map_.find(op_type) != map_.end(); + } + + void Insert(const std::string& type, const OpInfo& info) { + PADDLE_ENFORCE(!Has(type), "Operator %s has been registered", type); + map_.insert({type, info}); + } + + const OpInfo& Get(const std::string& type) const { + auto it = map_.find(type); + PADDLE_ENFORCE(it != map_.end(), "Operator %s are not found", type); + return it->second; + } + + template + void IterAllInfo(Callback callback) { + for (auto& it : map_) { + callback(it.first, it.second); + } + } + + private: + OpInfoMap() = default; + std::unordered_map map_; +}; } // namespace framework } // namespace paddle diff --git a/paddle/framework/op_registry.cc b/paddle/framework/op_registry.cc index e03dc3a73d..b0e85dd49f 100644 --- a/paddle/framework/op_registry.cc +++ b/paddle/framework/op_registry.cc @@ -22,11 +22,9 @@ namespace framework { std::unique_ptr OpRegistry::CreateOp( const std::string& type, const VariableNameMap& inputs, const VariableNameMap& outputs, AttributeMap attrs) { - auto it = OpInfoMap().find(type); - PADDLE_ENFORCE(it != OpInfoMap().end(), - "Operator '%s' has not been registered.", type); - it->second.checker_->Check(attrs); - auto op = it->second.creator_(type, inputs, outputs, attrs); + auto& info = OpInfoMap::Instance().Get(type); + info.Checker().Check(attrs); + auto op = info.Creator()(type, inputs, outputs, attrs); return std::unique_ptr(op); } diff --git a/paddle/framework/op_registry.h b/paddle/framework/op_registry.h index 06530bc7d0..2d09cde41e 100644 --- a/paddle/framework/op_registry.h +++ b/paddle/framework/op_registry.h @@ -35,7 +35,7 @@ class OpRegistry { template static void RegisterOp(const std::string& op_type, const std::string& grad_op_type) { - PADDLE_ENFORCE(OpInfoMap().count(op_type) == 0, + PADDLE_ENFORCE(!OpInfoMap::Instance().Has(op_type), "'%s' is registered more than once.", op_type); OpInfo op_info; op_info.creator_ = []( @@ -59,7 +59,7 @@ class OpRegistry { op_info.proto_ = nullptr; op_info.checker_ = nullptr; } - OpInfoMap().insert(std::make_pair(op_type, op_info)); + OpInfoMap::Instance().Insert(op_type, op_info); // register gradient op if (!grad_op_type.empty()) { RegisterOp(grad_op_type, ""); diff --git a/paddle/framework/operator.cc b/paddle/framework/operator.cc index 48a7fe64ac..7abbde610f 100644 --- a/paddle/framework/operator.cc +++ b/paddle/framework/operator.cc @@ -141,18 +141,10 @@ std::vector OperatorBase::OutputVars(bool has_intermediate) const { } return ret_val; } - auto it = OpInfoMap().find(type_); - PADDLE_ENFORCE( - it != OpInfoMap().end(), - "Operator %s not registered, cannot figure out intermediate outputs", - type_); - PADDLE_ENFORCE( - it->second.proto_ != nullptr, - "Operator %s has no OpProto, cannot figure out intermediate outputs", - type_); + auto& info = OpInfoMap::Instance().Get(Type()); // get all OpProto::Var for outputs - for (auto& o : it->second.proto_->outputs()) { + for (auto& o : info.Proto().outputs()) { // ignore all intermediate output if (o.intermediate()) continue; auto out = outputs_.find(o.name()); diff --git a/paddle/framework/pybind.cc b/paddle/framework/pybind.cc index 1aec483573..6212c84909 100644 --- a/paddle/framework/pybind.cc +++ b/paddle/framework/pybind.cc @@ -138,19 +138,16 @@ All parameter, weight, gradient are variables in Paddle. //! @note: Be careful! PyBind will return std::string as an unicode, not //! Python str. If you want a str object, you should cast them in Python. m.def("get_all_op_protos", []() -> std::vector { - auto &op_info_map = OpInfoMap(); std::vector ret_values; - for (auto it = op_info_map.begin(); it != op_info_map.end(); ++it) { - const OpProto *proto = it->second.proto_; - if (proto == nullptr) { - continue; - } - PADDLE_ENFORCE(proto->IsInitialized(), "OpProto must all be initialized"); + + OpInfoMap::Instance().IterAllInfo([&ret_values](const std::string &type, + const OpInfo &info) { + if (!info.HasOpProtoAndChecker()) return; std::string str; - PADDLE_ENFORCE(proto->SerializeToString(&str), + PADDLE_ENFORCE(info.Proto().SerializeToString(&str), "Serialize OpProto Error. This could be a bug of Paddle."); - ret_values.push_back(py::bytes(str)); - } + ret_values.emplace_back(str); + }); return ret_values; }); m.def_submodule( From 430e0e418bb34d6a14662a29a3e6d5fb906c9610 Mon Sep 17 00:00:00 2001 From: hedaoyuan Date: Mon, 21 Aug 2017 10:12:25 +0800 Subject: [PATCH 055/138] Follow comments. --- paddle/function/CMakeLists.txt | 4 +++- paddle/function/EigenGemm.cpp | 3 +-- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/paddle/function/CMakeLists.txt b/paddle/function/CMakeLists.txt index 9187294a49..c572a9d433 100644 --- a/paddle/function/CMakeLists.txt +++ b/paddle/function/CMakeLists.txt @@ -5,7 +5,9 @@ list(APPEND h_files Function.h) list(APPEND cpp_files Function.cpp) list(APPEND cpp_files BufferArg.cpp) list(APPEND cpp_files GemmFunctor.cpp) -list(APPEND cpp_files EigenGemm.cpp) +if(USE_EIGEN_FOR_BLAS) + list(APPEND cpp_files EigenGemm.cpp) +endif(USE_EIGEN_FOR_BLAS) if(WITH_GPU) file(GLOB cu_files . *OpGpu.cu) diff --git a/paddle/function/EigenGemm.cpp b/paddle/function/EigenGemm.cpp index 0b4220fcbe..674141ed39 100644 --- a/paddle/function/EigenGemm.cpp +++ b/paddle/function/EigenGemm.cpp @@ -77,8 +77,7 @@ struct EigenBlasGemm { } else if (alpha == T(1) && beta == T(1)) { c.device(device) += a.contract(b, dims); } else { - c.device(device) = - c.constant(alpha) * a.contract(b, dims) + c.constant(beta) * c; + c.device(device) = alpha * a.contract(b, dims) + beta * c; } } }; From d525abed955b5dd2e6c711205c11ac6a3bcca789 Mon Sep 17 00:00:00 2001 From: qijun Date: Mon, 21 Aug 2017 13:43:07 +0800 Subject: [PATCH 056/138] refine random related ops --- paddle/operators/CMakeLists.txt | 4 +- paddle/operators/gaussian_random_op.cc | 35 ++---------- paddle/operators/gaussian_random_op.cu | 41 ++------------ paddle/operators/gaussian_random_op.h | 38 +++++++++++++ paddle/operators/math/math_function.cc | 22 ++++++++ paddle/operators/math/math_function.cu | 36 ++++++++++++ paddle/operators/math/math_function.h | 8 +++ paddle/operators/mul_op.cc | 1 - paddle/operators/uniform_random_op.cc | 39 ++----------- paddle/operators/uniform_random_op.cu | 55 +------------------ paddle/operators/uniform_random_op.h | 38 +++++++++++++ paddle/platform/device_context.cc | 36 ++++++------ paddle/platform/device_context.h | 20 ++++--- .../paddle/v2/framework/tests/CMakeLists.txt | 2 +- .../tests/test_gaussian_random_op.py | 7 +-- .../framework/tests/test_uniform_random_op.py | 7 +-- 16 files changed, 192 insertions(+), 197 deletions(-) create mode 100644 paddle/operators/gaussian_random_op.h create mode 100644 paddle/operators/uniform_random_op.h diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index a7c89787e4..8f22a5fbc3 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -58,7 +58,7 @@ op_library(rowwise_add_op SRCS rowwise_add_op.cu rowwise_add_op.cc) op_library(sigmoid_op SRCS sigmoid_op.cc sigmoid_op.cu) op_library(softmax_op SRCS softmax_op.cc softmax_op.cu) -op_library(gaussian_random_op SRCS gaussian_random_op.cc gaussian_random_op.cu) +op_library(gaussian_random_op SRCS gaussian_random_op.cc gaussian_random_op.cu DEPS math_function) op_library(cross_entropy_op SRCS cross_entropy_op.cc cross_entropy_op.cu) op_library(fill_zeros_like_op SRCS fill_zeros_like_op.cc fill_zeros_like_op.cu) @@ -67,4 +67,4 @@ op_library(sgd_op SRCS sgd_op.cc sgd_op.cu) op_library(recurrent_op SRCS recurrent_op.cc rnn/recurrent_op_utils.cc DEPS framework_proto tensor op_registry operator net_op) op_library(uniform_random_op - SRCS uniform_random_op.cc uniform_random_op.cu) + SRCS uniform_random_op.cc uniform_random_op.cu DEPS math_function) diff --git a/paddle/operators/gaussian_random_op.cc b/paddle/operators/gaussian_random_op.cc index f30bbce958..aba8c6e5cd 100644 --- a/paddle/operators/gaussian_random_op.cc +++ b/paddle/operators/gaussian_random_op.cc @@ -12,36 +12,11 @@ See the License for the specific language governing permissions and limitations under the License. */ -#include -#include "paddle/framework/op_registry.h" +#include "paddle/operators/gaussian_random_op.h" namespace paddle { namespace operators { -template -class GaussianRandomKernel : public framework::OpKernel { - public: - void Compute(const framework::ExecutionContext& context) const override { - float mean = context.op_.GetAttr("mean"); - float std = context.op_.GetAttr("std"); - auto* tensor = context.Output(0); - T* data = tensor->mutable_data(context.GetPlace()); - - // TODO(dzh): attribute does not support unsigned int. - // And we need a global random seed configuration. - int seed = context.op_.GetAttr("seed"); - if (seed == 0) { - seed = std::random_device()(); - } - std::mt19937 g(seed); - std::normal_distribution distribution(mean, std); - ssize_t size = framework::product(tensor->dims()); - for (int i = 0; i < size; ++i) { - data[i] = distribution(g); - } - } -}; - class GaussianRandomOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; @@ -70,10 +45,6 @@ Use to initialize tensor with gaussian random generator. AddAttr>("dims", "The dimension of random tensor."); AddAttr("mean", "mean value of random.").SetDefault(.0f); AddAttr("std", "minimum value of random value.").SetDefault(1.0f); - AddAttr("seed", - "Random seed of generator." - "0 means use system wide seed") - .SetDefault(0); } }; @@ -83,4 +54,6 @@ Use to initialize tensor with gaussian random generator. namespace ops = paddle::operators; REGISTER_OP_WITHOUT_GRADIENT(gaussian_random, ops::GaussianRandomOp, ops::GaussianRandomOpMaker); -REGISTER_OP_CPU_KERNEL(gaussian_random, ops::GaussianRandomKernel); +REGISTER_OP_CPU_KERNEL( + gaussian_random, + ops::GaussianRandomKernel); diff --git a/paddle/operators/gaussian_random_op.cu b/paddle/operators/gaussian_random_op.cu index 1340b1e1e9..31be16fdc8 100644 --- a/paddle/operators/gaussian_random_op.cu +++ b/paddle/operators/gaussian_random_op.cu @@ -12,42 +12,9 @@ See the License for the specific language governing permissions and limitations under the License. */ -#include -#include -#include "paddle/platform/dynload/curand.h" -#include "paddle/platform/gpu_info.h" - -#include "paddle/framework/op_registry.h" - -namespace paddle { -namespace operators { - -template -class GaussianRandomKernel : public framework::OpKernel { - public: - void Compute(const framework::ExecutionContext& context) const override { - float mean = context.op_.GetAttr("mean"); - float std = context.op_.GetAttr("std"); - auto* tensor = context.Output(0); - T* data = tensor->mutable_data(context.GetPlace()); - - int seed = context.op_.GetAttr("seed"); - if (seed == 0) { - std::random_device rd; - seed = rd(); - } - curandGenerator_t g; - PADDLE_ENFORCE(platform::dynload::curandCreateGenerator( - &g, CURAND_RNG_PSEUDO_DEFAULT)); - PADDLE_ENFORCE( - platform::dynload::curandSetPseudoRandomGeneratorSeed(g, seed)); - platform::dynload::curandGenerateNormal( - g, data, framework::product(tensor->dims()), mean, std); - } -}; - -} // namespace operators -} // namespace paddle +#include "paddle/operators/gaussian_random_op.h" namespace ops = paddle::operators; -REGISTER_OP_GPU_KERNEL(gaussian_random, ops::GaussianRandomKernel); +REGISTER_OP_GPU_KERNEL( + gaussian_random, + ops::GaussianRandomKernel); diff --git a/paddle/operators/gaussian_random_op.h b/paddle/operators/gaussian_random_op.h new file mode 100644 index 0000000000..041390e954 --- /dev/null +++ b/paddle/operators/gaussian_random_op.h @@ -0,0 +1,38 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#pragma once + +#include "paddle/framework/op_registry.h" +#include "paddle/operators/math/math_function.h" + +namespace paddle { +namespace operators { +template +class GaussianRandomKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& context) const override { + auto* tensor = context.Output("Out"); + T* data = tensor->mutable_data(context.GetPlace()); + T mean = static_cast(context.op_.GetAttr("mean")); + T std = static_cast(context.op_.GetAttr("std")); + auto n = framework::product(tensor->dims()); + + auto* device_context = + const_cast(context.device_context_); + math::RandGaussian(n, mean, std, data, device_context); + } +}; +} +} diff --git a/paddle/operators/math/math_function.cc b/paddle/operators/math/math_function.cc index 1e86fc3d16..da59044899 100644 --- a/paddle/operators/math/math_function.cc +++ b/paddle/operators/math/math_function.cc @@ -109,6 +109,28 @@ void matmul(const framework::Tensor& matrix_a, matrix_b.data(), beta, matrix_out->data(), context); } +template <> +void RandUniform(const int n, const float min, + const float max, float* output, + platform::DeviceContext* context) { + auto* cpu_context = reinterpret_cast(context); + std::uniform_real_distribution distribution(min, max); + for (int i = 0; i < n; i++) { + output[i] = distribution(cpu_context->rand_engine()); + } +} + +template <> +void RandGaussian(const int n, const float mean, + const float std, float* output, + platform::DeviceContext* context) { + auto* cpu_context = reinterpret_cast(context); + std::normal_distribution distribution(mean, std); + for (int i = 0; i < n; i++) { + output[i] = distribution(cpu_context->rand_engine()); + } +} + } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/math/math_function.cu b/paddle/operators/math/math_function.cu index da40b27c94..5a400d4445 100644 --- a/paddle/operators/math/math_function.cu +++ b/paddle/operators/math/math_function.cu @@ -12,6 +12,10 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ +#include +#include +#include +#include #include "paddle/operators/math/math_function.h" namespace paddle { @@ -122,6 +126,38 @@ void matmul(const framework::Tensor& matrix_a, matrix_b.data(), beta, matrix_out->data(), context); } +template <> +void RandUniform(const int n, const float min, + const float max, float* output, + platform::DeviceContext* context) { + auto* cuda_context = reinterpret_cast(context); + thrust::uniform_real_distribution distribution(min, max); + thrust::minstd_rand engine = cuda_context->rand_enigne(); + engine->discard(n); + + thrust::counting_iterator index_sequence_begin(0); + + thrust::transform(thrust::cuda::par.on(cuda_context->stream()), + index_sequence_begin, index_sequence_begin + n, + thrust::device_ptr(output), distribution(engine)); +} + +template <> +void RandGaussian(const int n, const float mean, + const float std, float* output, + platform::DeviceContext* context) { + auto* cuda_context = reinterpret_cast(context); + thrust::normal_distribution distribution(mean, std); + thrust::minstd_rand engine = cuda_context->rand_enigne(); + engine->discard(n); + + thrust::counting_iterator index_sequence_begin(0); + + thrust::transform(thrust::cuda::par.on(cuda_context->stream()), + index_sequence_begin, index_sequence_begin + n, + thrust::device_ptr(output), distribution(engine)); +} + } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/math/math_function.h b/paddle/operators/math/math_function.h index 155589fadb..ea15e8fd2b 100644 --- a/paddle/operators/math/math_function.h +++ b/paddle/operators/math/math_function.h @@ -77,6 +77,14 @@ void matmul(const framework::Tensor& matrix_a, bool trans_a, framework::Tensor* matrix_out, T beta, platform::DeviceContext* context); +template +void RandUniform(const int n, const T min, const T max, T* output, + platform::DeviceContext* context); + +template +void RandGaussian(const int n, const T mean, const T std, T* output, + platform::DeviceContext* context); + } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/mul_op.cc b/paddle/operators/mul_op.cc index 460e458ca4..173cc3850c 100644 --- a/paddle/operators/mul_op.cc +++ b/paddle/operators/mul_op.cc @@ -13,7 +13,6 @@ limitations under the License. */ #include "paddle/operators/mul_op.h" -#include "paddle/operators/math/math_function.h" namespace paddle { namespace operators { diff --git a/paddle/operators/uniform_random_op.cc b/paddle/operators/uniform_random_op.cc index a0a0d4d914..81487a6bd8 100644 --- a/paddle/operators/uniform_random_op.cc +++ b/paddle/operators/uniform_random_op.cc @@ -12,39 +12,11 @@ See the License for the specific language governing permissions and limitations under the License. */ -#include -#include -#include "paddle/framework/op_registry.h" -#include "paddle/framework/operator.h" +#include "paddle/operators/uniform_random_op.h" namespace paddle { namespace operators { -// It seems that Eigen::Tensor::random in GPU will SEGFAULT. -// Use std::random and thrust::random(thrust is a std library in CUDA) to -// implement uniform random. -template -class CPUUniformRandomKernel : public framework::OpKernel { - public: - void Compute(const framework::ExecutionContext& context) const override { - auto* tensor = context.Output("Out"); - T* data = tensor->mutable_data(context.GetPlace()); - unsigned int seed = - static_cast(context.op_.GetAttr("seed")); - std::minstd_rand engine; - if (seed == 0) { - seed = std::random_device()(); - } - engine.seed(seed); - std::uniform_real_distribution dist( - static_cast(context.op_.GetAttr("min")), - static_cast(context.op_.GetAttr("max"))); - for (ssize_t i = 0; i < framework::product(tensor->dims()); ++i) { - data[i] = dist(engine); - } - } -}; - class UniformRandomOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; @@ -72,10 +44,6 @@ Used to initialize tensor with uniform random generator. AddAttr>("dims", "the dimension of random tensor"); AddAttr("min", "Minimum value of uniform random").SetDefault(-1.0f); AddAttr("max", "Maximun value of uniform random").SetDefault(1.0f); - AddAttr("seed", - "Random seed of uniform random. " - "0 means generate a seed by system") - .SetDefault(0); } }; } // namespace operators @@ -83,5 +51,6 @@ Used to initialize tensor with uniform random generator. REGISTER_OP_WITHOUT_GRADIENT(uniform_random, paddle::operators::UniformRandomOp, paddle::operators::UniformRandomOpMaker); -REGISTER_OP_CPU_KERNEL(uniform_random, - paddle::operators::CPUUniformRandomKernel); +REGISTER_OP_CPU_KERNEL( + uniform_random, + paddle::operators::UniformRandomKernel); diff --git a/paddle/operators/uniform_random_op.cu b/paddle/operators/uniform_random_op.cu index 7a243555b6..91368fa73e 100644 --- a/paddle/operators/uniform_random_op.cu +++ b/paddle/operators/uniform_random_op.cu @@ -12,60 +12,11 @@ See the License for the specific language governing permissions and limitations under the License. */ -#include -#include -#include -#include -#include "paddle/framework/op_registry.h" -#include "paddle/framework/operator.h" +#include "paddle/operators/uniform_random_op.h" namespace paddle { namespace operators { -template -struct UniformGenerator { - T min_, max_; - unsigned int seed_; - - __host__ __device__ UniformGenerator(T min, T max, int seed) - : min_(min), max_(max), seed_(seed) {} - - __host__ __device__ T operator()(const unsigned int n) const { - thrust::minstd_rand rng; - rng.seed(seed_); - thrust::uniform_real_distribution dist(min_, max_); - rng.discard(n); - return dist(rng); - } -}; - -// It seems that Eigen::Tensor::random in GPU will SEGFAULT. -// Use std::random and thrust::random(thrust is a std library in CUDA) to -// implement uniform random. -template -class GPUUniformRandomKernel : public framework::OpKernel { - public: - void Compute(const framework::ExecutionContext& context) const override { - auto* tensor = context.Output("Out"); - T* data = tensor->mutable_data(context.GetPlace()); - unsigned int seed = - static_cast(context.op_.GetAttr("seed")); - if (seed == 0) { - std::random_device rd; - seed = rd(); - } - T min = static_cast(context.op_.GetAttr("min")); - T max = static_cast(context.op_.GetAttr("max")); - thrust::counting_iterator index_sequence_begin(0); - ssize_t N = framework::product(tensor->dims()); - thrust::transform(index_sequence_begin, index_sequence_begin + N, - thrust::device_ptr(data), - UniformGenerator(min, max, seed)); - } -}; - -} // namespace operators -} // namespace paddle - REGISTER_OP_GPU_KERNEL(uniform_random, - paddle::operators::GPUUniformRandomKernel); + paddle::operators::GPUUniformRandomKernel< + paddle::platform::GPUPlace, float>); diff --git a/paddle/operators/uniform_random_op.h b/paddle/operators/uniform_random_op.h new file mode 100644 index 0000000000..ec009b025e --- /dev/null +++ b/paddle/operators/uniform_random_op.h @@ -0,0 +1,38 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#pragma once + +#include "paddle/framework/op_registry.h" +#include "paddle/operators/math/math_function.h" + +namespace paddle { +namespace operators { +template +class UniformRandomKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& context) const override { + auto* tensor = context.Output("Out"); + T* data = tensor->mutable_data(context.GetPlace()); + T min = static_cast(context.op_.GetAttr("min")); + T max = static_cast(context.op_.GetAttr("max")); + auto n = framework::product(tensor->dims()); + + auto* device_context = + const_cast(context.device_context_); + math::RandUniform(n, min, max, data, device_context); + } +}; +} +} diff --git a/paddle/platform/device_context.cc b/paddle/platform/device_context.cc index f92c15ae45..fabbb55443 100644 --- a/paddle/platform/device_context.cc +++ b/paddle/platform/device_context.cc @@ -25,8 +25,17 @@ CPUDeviceContext::CPUDeviceContext() { eigen_device_.reset(new Eigen::DefaultDevice()); } -CPUDeviceContext::CPUDeviceContext(CPUPlace place) { +CPUDeviceContext::CPUDeviceContext(CPUPlace place, int rand_seed) { eigen_device_.reset(new Eigen::DefaultDevice()); + rand_seed_ = rand_seed; +} + +std::minstd_rand& CPUDeviceContext::rand_engine() { + if (!rand_engine_) { + rand_engine_.reset(new std::minstd_rand()); + rand_engine_->seed(rand_seed_); + } + return *(rand_engine_.get()); } Eigen::DefaultDevice* CPUDeviceContext::eigen_device() const { @@ -95,7 +104,8 @@ Eigen::GpuDevice* DeviceContext::get_eigen_device() const { return reinterpret_cast(this)->eigen_device(); } -CUDADeviceContext::CUDADeviceContext(GPUPlace place) : place_(place) { +CUDADeviceContext::CUDADeviceContext(GPUPlace place, uint64_t seed) + : place_(place), seed_(seed) { SetDeviceId(place_.device); PADDLE_ENFORCE(cudaStreamCreate(&stream_)); eigen_stream_.reset(new EigenCudaStreamDevice()); @@ -114,9 +124,6 @@ CUDADeviceContext::~CUDADeviceContext() { PADDLE_ENFORCE(dynload::cudnnDestroy(cudnn_handle_)); } - if (curand_generator_) { - PADDLE_ENFORCE(dynload::curandDestroyGenerator(curand_generator_)); - } eigen_stream_.reset(); eigen_device_.reset(); PADDLE_ENFORCE(cudaStreamDestroy(stream_)); @@ -150,21 +157,16 @@ cudnnHandle_t CUDADeviceContext::cudnn_handle() { return cudnn_handle_; } -cudaStream_t CUDADeviceContext::stream() { return stream_; } - -curandGenerator_t CUDADeviceContext::curand_generator() { - if (!curand_generator_) { - SetDeviceId(place_.device); - PADDLE_ENFORCE(dynload::curandCreateGenerator(&curand_generator_, - CURAND_RNG_PSEUDO_DEFAULT)); - PADDLE_ENFORCE( - dynload::curandSetPseudoRandomGeneratorSeed(curand_generator_, seed_)); - - PADDLE_ENFORCE(dynload::curandSetStream(curand_generator_, stream_)); +thrust::minstd_rand& CPUDeviceContext::rand_engine() { + if (!rand_engine_) { + rand_engine_.reset(new thrust::minstd_rand()); + rand_engine_->seed(rand_seed_); } - return curand_generator_; + return *(rand_engine_.get()); } +cudaStream_t CUDADeviceContext::stream() { return stream_; } + #endif // PADDLE_ONLY_CPU } // namespace platform diff --git a/paddle/platform/device_context.h b/paddle/platform/device_context.h index c5042ae33e..e4de3807cd 100644 --- a/paddle/platform/device_context.h +++ b/paddle/platform/device_context.h @@ -15,9 +15,10 @@ limitations under the License. */ #include "paddle/platform/place.h" #ifndef PADDLE_ONLY_CPU +#include +#include #include "paddle/platform/dynload/cublas.h" #include "paddle/platform/dynload/cudnn.h" -#include "paddle/platform/dynload/curand.h" #include "paddle/platform/gpu_info.h" #define EIGEN_USE_GPU #endif @@ -40,14 +41,18 @@ class DeviceContext { class CPUDeviceContext : public DeviceContext { public: CPUDeviceContext(); - explicit CPUDeviceContext(CPUPlace); + explicit CPUDeviceContext(CPUPlace place, int rand_seed = 0); virtual ~CPUDeviceContext() {} Eigen::DefaultDevice* eigen_device() const; + std::minstd_rand& rand_engine(); + Place GetPlace() const override; private: + int rand_seed_; + std::unique_ptr rand_engine_; std::unique_ptr eigen_device_; }; @@ -56,7 +61,7 @@ class EigenCudaStreamDevice; class CUDADeviceContext : public DeviceContext { public: - explicit CUDADeviceContext(GPUPlace); + explicit CUDADeviceContext(GPUPlace place, uint64_t rand_seed = 0); virtual ~CUDADeviceContext(); /*! \brief Wait for all operations completion in the stream. */ @@ -75,8 +80,7 @@ class CUDADeviceContext : public DeviceContext { /*! \brief Return cudnn handle in the device context. */ cudnnHandle_t cudnn_handle(); - /*! \brief Return curand handle in the device context. */ - curandGenerator_t curand_generator(); + thrust::minstd_rand& CPUDeviceContext::rand_engine(); /*! \brief Return cuda stream in the device context. */ cudaStream_t stream(); @@ -85,18 +89,16 @@ class CUDADeviceContext : public DeviceContext { private: GPUPlace place_; - private: std::unique_ptr eigen_device_; std::unique_ptr eigen_stream_; - private: - uint64_t seed_; + uint64_t rand_seed_; + std::unique_ptr rand_engine_; // clang-format off cudaStream_t stream_{nullptr}; cudnnHandle_t cudnn_handle_{nullptr}; cublasHandle_t cublas_handle_{nullptr}; - curandGenerator_t curand_generator_{nullptr}; // clang-format on }; diff --git a/python/paddle/v2/framework/tests/CMakeLists.txt b/python/paddle/v2/framework/tests/CMakeLists.txt index ce57a07130..b07a65f4d1 100644 --- a/python/paddle/v2/framework/tests/CMakeLists.txt +++ b/python/paddle/v2/framework/tests/CMakeLists.txt @@ -22,7 +22,7 @@ py_test(test_rowwise_add_op SRCS test_rowwise_add_op.py) py_test(test_default_scope_funcs SRCS test_default_scope_funcs.py) py_test(test_operator SRCS test_operator.py) -# py_test(test_gaussian_random_op SRCS test_gaussian_random_op.py) +py_test(test_gaussian_random_op SRCS test_gaussian_random_op.py) py_test(test_uniform_random_op SRCS test_uniform_random_op.py) py_test(test_recurrent_op SRCS test_recurrent_op.py) py_test(test_sgd_op SRCS test_sgd_op.py) diff --git a/python/paddle/v2/framework/tests/test_gaussian_random_op.py b/python/paddle/v2/framework/tests/test_gaussian_random_op.py index f95ed70b58..367d21b301 100644 --- a/python/paddle/v2/framework/tests/test_gaussian_random_op.py +++ b/python/paddle/v2/framework/tests/test_gaussian_random_op.py @@ -17,12 +17,7 @@ class GaussianRandomTest(unittest.TestCase): scope.new_var("Out").get_tensor() op = Operator( - "gaussian_random", - Out="Out", - dims=[1000, 784], - mean=.0, - std=1., - seed=10) + "gaussian_random", Out="Out", dims=[1000, 784], mean=.0, std=1.) op.infer_shape(scope) context = core.DeviceContext.create(place) diff --git a/python/paddle/v2/framework/tests/test_uniform_random_op.py b/python/paddle/v2/framework/tests/test_uniform_random_op.py index c3d2bb44da..95c36a27cf 100644 --- a/python/paddle/v2/framework/tests/test_uniform_random_op.py +++ b/python/paddle/v2/framework/tests/test_uniform_random_op.py @@ -17,12 +17,7 @@ class UniformRandomTest(unittest.TestCase): scope.new_var("X").get_tensor() op = Operator( - "uniform_random", - Out="X", - dims=[1000, 784], - min=-5.0, - max=10.0, - seed=10) + "uniform_random", Out="X", dims=[1000, 784], min=-5.0, max=10.0) op.infer_shape(scope) ctx = core.DeviceContext.create(place) From 29d8825caf921f5349551a18344503345c7b9969 Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Mon, 21 Aug 2017 13:43:51 +0800 Subject: [PATCH 057/138] tune relative precision for unit test img_conv2 in test_NetworkCompare.cpp. 1. It's no problem with relative precision 1e-3 when testing several times in my local machine. 2. But the testing failed with 1e-2 in the TeamCity, and only one value's relative precision is over 1e-2. So tune it to 4e-2 --- paddle/gserver/tests/test_NetworkCompare.cpp | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/paddle/gserver/tests/test_NetworkCompare.cpp b/paddle/gserver/tests/test_NetworkCompare.cpp index f930c72fde..d36f72360f 100644 --- a/paddle/gserver/tests/test_NetworkCompare.cpp +++ b/paddle/gserver/tests/test_NetworkCompare.cpp @@ -269,7 +269,8 @@ TEST(Compare, img_conv2) { bool useGpu = FLAGS_use_gpu; double eps = FLAGS_checkgrad_eps; FLAGS_use_gpu = true; - FLAGS_checkgrad_eps = 1e-2; + // Sometimes, this unit test will fail with 1e-2 + FLAGS_checkgrad_eps = 4e-2; compareNetwork(config_file_a, config_file_b); FLAGS_use_gpu = useGpu; FLAGS_checkgrad_eps = eps; From c108d6108cbdd28424397341fb67be01a2f63413 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Mon, 21 Aug 2017 14:03:12 +0800 Subject: [PATCH 058/138] Identity operator and its gradient --- paddle/framework/CMakeLists.txt | 3 +- paddle/framework/pybind.cc | 1 + paddle/operators/CMakeLists.txt | 1 + paddle/operators/identity_op.cc | 71 +++++++++++++++++++ paddle/operators/identity_op.cu | 17 +++++ paddle/operators/identity_op.h | 32 +++++++++ .../paddle/v2/framework/tests/CMakeLists.txt | 1 + .../v2/framework/tests/test_identity_op.py | 24 +++++++ 8 files changed, 149 insertions(+), 1 deletion(-) create mode 100644 paddle/operators/identity_op.cc create mode 100644 paddle/operators/identity_op.cu create mode 100644 paddle/operators/identity_op.h create mode 100644 python/paddle/v2/framework/tests/test_identity_op.py diff --git a/paddle/framework/CMakeLists.txt b/paddle/framework/CMakeLists.txt index 68304c9fc8..f249512f47 100644 --- a/paddle/framework/CMakeLists.txt +++ b/paddle/framework/CMakeLists.txt @@ -55,5 +55,6 @@ cc_library(paddle_pybind SHARED recurrent_op uniform_random_op gaussian_random_op - fill_zeros_like_op) + fill_zeros_like_op + identity_op) endif(WITH_PYTHON) diff --git a/paddle/framework/pybind.cc b/paddle/framework/pybind.cc index f0114b9e49..ddb244623f 100644 --- a/paddle/framework/pybind.cc +++ b/paddle/framework/pybind.cc @@ -42,6 +42,7 @@ USE_OP(fill_zeros_like); USE_OP_ITSELF(recurrent_op); USE_OP(gaussian_random); USE_OP(uniform_random); +USE_OP(identity); namespace paddle { namespace framework { diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index a7c89787e4..20e562c7d3 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -68,3 +68,4 @@ op_library(recurrent_op SRCS recurrent_op.cc rnn/recurrent_op_utils.cc DEPS framework_proto tensor op_registry operator net_op) op_library(uniform_random_op SRCS uniform_random_op.cc uniform_random_op.cu) +op_library(identity_op SRCS identity_op.cc identity_op.cu DEPS net_op) diff --git a/paddle/operators/identity_op.cc b/paddle/operators/identity_op.cc new file mode 100644 index 0000000000..cac44020bc --- /dev/null +++ b/paddle/operators/identity_op.cc @@ -0,0 +1,71 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#include "paddle/operators/identity_op.h" +#include "paddle/operators/net_op.h" + +namespace paddle { +namespace operators { + +class IdentityOp : public framework::OperatorWithKernel { + public: + IdentityOp(const std::string &type, const VarNameMap &inputs, + const VarNameMap &outputs, const framework::AttributeMap &attrs) + : OperatorWithKernel(type, inputs, outputs, attrs) {} + + protected: + void InferShape(const framework::InferShapeContext &ctx) const override { + auto *in = ctx.Input("X"); + auto *out = ctx.Output("Out"); + out->Resize(in->dims()); + } +}; + +class IdentityOpMaker : public framework::OpProtoAndCheckerMaker { + public: + IdentityOpMaker(framework::OpProto *proto, + framework::OpAttrChecker *op_checker) + : OpProtoAndCheckerMaker(proto, op_checker) { + AddInput("X", "The input tensor of identity operator.").NotInGradient(); + AddOutput("Out", "The output tensor of identity operator.").NotInGradient(); + AddComment(R"DOC(Identity operator + +The equation is: Out = X +)DOC"); + } +}; + +// Identity Op's gradient is identity op, too. +// Grad(Out=identity_op(X)) => Grad(X) = identity_op(Grad(Out)) +class IdentityGradOp : public NetOp { + public: + IdentityGradOp(const std::string &type, const VarNameMap &inputs, + const VarNameMap &outputs, + const framework::AttributeMap &attrs) + : NetOp(type, inputs, outputs, attrs) { + AddOp(framework::OpRegistry::CreateOp( + "identity", {{"X", {Input(framework::GradVarName("Out"))}}}, + {{"Out", {Output(framework::GradVarName("X"))}}}, {})); + CompleteAddOp(false); + } +}; + +} // namespace operators +} // namespace paddle + +namespace ops = paddle::operators; + +REGISTER_OP(identity, ops::IdentityOp, ops::IdentityOpMaker, identity_grad, + ops::IdentityGradOp); +REGISTER_OP_CPU_KERNEL(identity, ops::IdentityKernel); diff --git a/paddle/operators/identity_op.cu b/paddle/operators/identity_op.cu new file mode 100644 index 0000000000..3053104bbe --- /dev/null +++ b/paddle/operators/identity_op.cu @@ -0,0 +1,17 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#include "paddle/operators/identity_op.h" + +REGISTER_OP_GPU_KERNEL(identity, paddle::operators::IdentityKernel); diff --git a/paddle/operators/identity_op.h b/paddle/operators/identity_op.h new file mode 100644 index 0000000000..14a832257b --- /dev/null +++ b/paddle/operators/identity_op.h @@ -0,0 +1,32 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#pragma once + +#include "paddle/framework/op_registry.h" +#include "paddle/memory/memcpy.h" +namespace paddle { +namespace operators { +template +class IdentityKernel : public framework::OpKernel { + public: + virtual void Compute(const framework::ExecutionContext& context) const { + auto* tensor = context.Output("Out"); + auto* in = context.Input("X"); + tensor->CopyFrom(*in, in->place()); + } +}; + +} // namespace operators +} // namespace paddle diff --git a/python/paddle/v2/framework/tests/CMakeLists.txt b/python/paddle/v2/framework/tests/CMakeLists.txt index ce57a07130..cf7baa5556 100644 --- a/python/paddle/v2/framework/tests/CMakeLists.txt +++ b/python/paddle/v2/framework/tests/CMakeLists.txt @@ -27,3 +27,4 @@ py_test(test_uniform_random_op SRCS test_uniform_random_op.py) py_test(test_recurrent_op SRCS test_recurrent_op.py) py_test(test_sgd_op SRCS test_sgd_op.py) py_test(test_gradient_checker SRCS test_gradient_checker.py) +py_test(test_identity_op SRCS test_identity_op.py) diff --git a/python/paddle/v2/framework/tests/test_identity_op.py b/python/paddle/v2/framework/tests/test_identity_op.py new file mode 100644 index 0000000000..181d9c0c21 --- /dev/null +++ b/python/paddle/v2/framework/tests/test_identity_op.py @@ -0,0 +1,24 @@ +import unittest +from op_test_util import OpTestMeta +from gradient_checker import GradientChecker, create_op +import numpy as np + + +class IdentityTest(unittest.TestCase): + __metaclass__ = OpTestMeta + + def setUp(self): + self.type = "identity" + self.inputs = {'X': np.random.random((32, 784)).astype("float32")} + self.outputs = {'Out': self.inputs['X']} + + +class IdentityGradOpTest(GradientChecker): + def test_normal(self): + op = create_op("identity") + inputs = {"X": np.random.random((10, 10)).astype("float32")} + self.check_grad(op, inputs, set("X"), "Out") + + +if __name__ == '__main__': + unittest.main() From 83abbce8eb750f7e7c844b0959851e901806aa91 Mon Sep 17 00:00:00 2001 From: guosheng Date: Mon, 21 Aug 2017 14:05:56 +0800 Subject: [PATCH 059/138] Follow comments and refine ScaleShiftLayer --- paddle/gserver/layers/ScaleShiftLayer.cpp | 5 +++-- paddle/gserver/tests/test_LayerGrad.cpp | 4 ++-- python/paddle/trainer_config_helpers/layers.py | 5 +++-- .../protostr/test_scale_shift_layer.protostr | 14 +++++++------- .../tests/configs/test_scale_shift_layer.py | 6 ++---- 5 files changed, 17 insertions(+), 17 deletions(-) diff --git a/paddle/gserver/layers/ScaleShiftLayer.cpp b/paddle/gserver/layers/ScaleShiftLayer.cpp index 4f5b1c6225..06dcb409f8 100644 --- a/paddle/gserver/layers/ScaleShiftLayer.cpp +++ b/paddle/gserver/layers/ScaleShiftLayer.cpp @@ -17,8 +17,9 @@ limitations under the License. */ namespace paddle { /** - * A layer does scaling and shifting to the input by appling a slope and - * an intercept which are trainable to the input element-wise. + * A layer applies a slope and an intercept to the input element-wise for + * scaling and shifting. Noting that this layer is trainable which differs + * from the SlopeInterceptLayer. * * \f[ * y = wx + b diff --git a/paddle/gserver/tests/test_LayerGrad.cpp b/paddle/gserver/tests/test_LayerGrad.cpp index 65429ebada..dd2c955e6a 100644 --- a/paddle/gserver/tests/test_LayerGrad.cpp +++ b/paddle/gserver/tests/test_LayerGrad.cpp @@ -2008,8 +2008,8 @@ TEST(Layer, RowL2NormLayer) { } TEST(Layer, ScaleShiftLayer) { - const size_t batchSize = 128; - const size_t size = 512; + const size_t batchSize = 16; + const size_t size = 32; TestConfig config; config.layerConfig.set_type("scale_shift"); config.layerConfig.set_size(size); diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py index 4c7217024a..ec3a87aa36 100755 --- a/python/paddle/trainer_config_helpers/layers.py +++ b/python/paddle/trainer_config_helpers/layers.py @@ -6219,8 +6219,9 @@ def kmax_sequence_score_layer(input, name=None, beam_size=1): @wrap_bias_attr_default() def scale_shift_layer(input, name=None, param_attr=None, bias_attr=None): """ - A layer does scaling and shifting to the input by appling a slope and - an intercept which are trainable to the input element-wise. + A layer applies a slope and an intercept to the input element-wise for + scaling and shifting. Noting that this layer is trainable which differs + from the slope_intercept_layer. .. math:: y = w * x + b diff --git a/python/paddle/trainer_config_helpers/tests/configs/protostr/test_scale_shift_layer.protostr b/python/paddle/trainer_config_helpers/tests/configs/protostr/test_scale_shift_layer.protostr index efaf20f8a7..35ade126a2 100644 --- a/python/paddle/trainer_config_helpers/tests/configs/protostr/test_scale_shift_layer.protostr +++ b/python/paddle/trainer_config_helpers/tests/configs/protostr/test_scale_shift_layer.protostr @@ -14,7 +14,6 @@ layers { input_layer_name: "data" input_parameter_name: "___scale_shift_0__.w0" } - bias_parameter_name: "___scale_shift_0__.wbias" } layers { name: "__scale_shift_1__" @@ -25,6 +24,7 @@ layers { input_layer_name: "data" input_parameter_name: "___scale_shift_1__.w0" } + bias_parameter_name: "___scale_shift_1__.wbias" } parameters { name: "___scale_shift_0__.w0" @@ -37,24 +37,24 @@ parameters { initial_smart: true } parameters { - name: "___scale_shift_0__.wbias" + name: "___scale_shift_1__.w0" size: 1 initial_mean: 0.0 - initial_std: 0.0 + initial_std: 1.0 dims: 1 dims: 1 initial_strategy: 0 - initial_smart: false + initial_smart: true } parameters { - name: "___scale_shift_1__.w0" + name: "___scale_shift_1__.wbias" size: 1 initial_mean: 0.0 - initial_std: 1.0 + initial_std: 0.0 dims: 1 dims: 1 initial_strategy: 0 - initial_smart: true + initial_smart: false } input_layer_names: "data" output_layer_names: "__scale_shift_0__" diff --git a/python/paddle/trainer_config_helpers/tests/configs/test_scale_shift_layer.py b/python/paddle/trainer_config_helpers/tests/configs/test_scale_shift_layer.py index 818d71f15d..dd589116fa 100644 --- a/python/paddle/trainer_config_helpers/tests/configs/test_scale_shift_layer.py +++ b/python/paddle/trainer_config_helpers/tests/configs/test_scale_shift_layer.py @@ -1,11 +1,9 @@ from paddle.trainer_config_helpers import * -settings(batch_size=1000, learning_rate=1e-5) - data = data_layer(name='data', size=100) -scale = scale_shift_layer(input=data) +scale = scale_shift_layer(input=data, bias_attr=False) -scale_shift = scale_shift_layer(input=data, bias_attr=False) +scale_shift = scale_shift_layer(input=data) outputs(scale, scale_shift) From 0af1c4a9feed5a38f34e1ea5a44e3887f702059f Mon Sep 17 00:00:00 2001 From: guosheng Date: Mon, 21 Aug 2017 14:39:05 +0800 Subject: [PATCH 060/138] Follow comments and refine annotations on ScaleShiftLayer --- paddle/gserver/layers/ScaleShiftLayer.cpp | 8 ++++---- python/paddle/trainer_config_helpers/layers.py | 10 +++++++--- 2 files changed, 11 insertions(+), 7 deletions(-) diff --git a/paddle/gserver/layers/ScaleShiftLayer.cpp b/paddle/gserver/layers/ScaleShiftLayer.cpp index 06dcb409f8..35fd038ab4 100644 --- a/paddle/gserver/layers/ScaleShiftLayer.cpp +++ b/paddle/gserver/layers/ScaleShiftLayer.cpp @@ -17,15 +17,15 @@ limitations under the License. */ namespace paddle { /** - * A layer applies a slope and an intercept to the input element-wise for - * scaling and shifting. Noting that this layer is trainable which differs - * from the SlopeInterceptLayer. + * A layer applies a linear transformation to each element in each row of + * the input matrix. For each element, the layer first re-scale it and then + * adds a bias to it. * * \f[ * y = wx + b * \f] * - * Here, w is scale and b is offset, which are scalars and trainable. + * Here, w is the scale and b is the bias. Both w and b are trainable scalars. * */ diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py index ec3a87aa36..c9e3ded65c 100755 --- a/python/paddle/trainer_config_helpers/layers.py +++ b/python/paddle/trainer_config_helpers/layers.py @@ -6219,9 +6219,13 @@ def kmax_sequence_score_layer(input, name=None, beam_size=1): @wrap_bias_attr_default() def scale_shift_layer(input, name=None, param_attr=None, bias_attr=None): """ - A layer applies a slope and an intercept to the input element-wise for - scaling and shifting. Noting that this layer is trainable which differs - from the slope_intercept_layer. + A layer applies a linear transformation to each element in each row of + the input matrix. For each element, the layer first re-scale it and then + adds a bias to it. + + This layer is very like the SlopeInterceptLayer, except the scale and + bias are trainable. + .. math:: y = w * x + b From 7c274dc0a16b77fae0faf527ef02a1f72abad593 Mon Sep 17 00:00:00 2001 From: qijun Date: Mon, 21 Aug 2017 16:41:22 +0800 Subject: [PATCH 061/138] use curand --- paddle/operators/math/math_function.cc | 9 +++++ paddle/operators/math/math_function.cu | 56 ++++++++++++++++++-------- paddle/operators/math/math_function.h | 8 ++++ paddle/platform/device_context.cc | 15 ++++--- paddle/platform/device_context.h | 6 +-- 5 files changed, 70 insertions(+), 24 deletions(-) diff --git a/paddle/operators/math/math_function.cc b/paddle/operators/math/math_function.cc index da59044899..d0b1f8ee48 100644 --- a/paddle/operators/math/math_function.cc +++ b/paddle/operators/math/math_function.cc @@ -109,6 +109,15 @@ void matmul(const framework::Tensor& matrix_a, matrix_b.data(), beta, matrix_out->data(), context); } +template <> +void Set(const int n, const float alpha, + float* output, + platform::DeviceContext* context) { + auto* cpu_context = reinterpret_cast(context); + framework::EigenVector::Type out(output, n); + out.device(*(cpu_context->eigen_device())) = t.constant(T(alpha)); +} + template <> void RandUniform(const int n, const float min, const float max, float* output, diff --git a/paddle/operators/math/math_function.cu b/paddle/operators/math/math_function.cu index 5a400d4445..76bbf790db 100644 --- a/paddle/operators/math/math_function.cu +++ b/paddle/operators/math/math_function.cu @@ -126,20 +126,48 @@ void matmul(const framework::Tensor& matrix_a, matrix_b.data(), beta, matrix_out->data(), context); } +template <> +void Set(const int n, const float alpha, + float* output, + platform::DeviceContext* context) { + auto* cuda_context = reinterpret_cast(context); + framework::EigenVector::Type out(output, n); + out.device(*(cuda_context->eigen_device())) = t.constant(T(alpha)); +} + +template +__global__ void UniformShift(const int n, const T min, const T max, T* x) { + float scale = max - min; + for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < n; + i += blockDim.x * gridDim.x) { + x[i] = x[i] * scale + min; + } +} + template <> void RandUniform(const int n, const float min, const float max, float* output, platform::DeviceContext* context) { auto* cuda_context = reinterpret_cast(context); - thrust::uniform_real_distribution distribution(min, max); - thrust::minstd_rand engine = cuda_context->rand_enigne(); - engine->discard(n); - - thrust::counting_iterator index_sequence_begin(0); + PADDLE_ENFORCE( + curandGenerateUniform(cuda_context->curand_generator(), output, n)); + int block = 512; + int grid = (n + block - 1) / block; + UniformShift<<stream()>>>(n, min, max, + output); +} - thrust::transform(thrust::cuda::par.on(cuda_context->stream()), - index_sequence_begin, index_sequence_begin + n, - thrust::device_ptr(output), distribution(engine)); +template +int HandleOddLengthRandGaussian(const int n, const T mean, const T std, + T* output, CUDADeviceContext* context) { + if (n % 2 == 1) { + std::default_random_engine generator; + std::normal_distribution distribution(mean, std); + const T random_value = distribution(generator); + Set(1, random_value, output + (n - 1), context); + return n - 1; + } + return n; } template <> @@ -147,15 +175,11 @@ void RandGaussian(const int n, const float mean, const float std, float* output, platform::DeviceContext* context) { auto* cuda_context = reinterpret_cast(context); - thrust::normal_distribution distribution(mean, std); - thrust::minstd_rand engine = cuda_context->rand_enigne(); - engine->discard(n); - - thrust::counting_iterator index_sequence_begin(0); - thrust::transform(thrust::cuda::par.on(cuda_context->stream()), - index_sequence_begin, index_sequence_begin + n, - thrust::device_ptr(output), distribution(engine)); + const int even_n = + HandleOddLengthRandGaussian(n, mean, std, output, cuda_context); + PADDLE_ENFORCE(curandGenerateNormal(cuda_context->curand_generator(), output, + even_n, mean, std)); } } // namespace math diff --git a/paddle/operators/math/math_function.h b/paddle/operators/math/math_function.h index ea15e8fd2b..afe6de7483 100644 --- a/paddle/operators/math/math_function.h +++ b/paddle/operators/math/math_function.h @@ -54,6 +54,7 @@ int LAPACKE_dgetri(int matrix_layout, int n, double* a, int lda, #include "paddle/framework/tensor.h" #include "paddle/platform/device_context.h" +#include "paddle/platform/eigen.h" #include "paddle/platform/enforce.h" namespace paddle { @@ -77,6 +78,13 @@ void matmul(const framework::Tensor& matrix_a, bool trans_a, framework::Tensor* matrix_out, T beta, platform::DeviceContext* context); +template +void Set(const int n, const T alpha, T* output, + platform::DeviceContext* context) { + framework::EigenVector::Type out(output, n); + out.device(*(context->eigen_device())) = t.constant(T(alpha)); +} + template void RandUniform(const int n, const T min, const T max, T* output, platform::DeviceContext* context); diff --git a/paddle/platform/device_context.cc b/paddle/platform/device_context.cc index fabbb55443..5fd93555a5 100644 --- a/paddle/platform/device_context.cc +++ b/paddle/platform/device_context.cc @@ -157,12 +157,17 @@ cudnnHandle_t CUDADeviceContext::cudnn_handle() { return cudnn_handle_; } -thrust::minstd_rand& CPUDeviceContext::rand_engine() { - if (!rand_engine_) { - rand_engine_.reset(new thrust::minstd_rand()); - rand_engine_->seed(rand_seed_); +curandGenerator_t CUDADeviceContext::curand_generator() { + if (!curand_generator_) { + SetDeviceId(place_.device); + PADDLE_ENFORCE(dynload::curandCreateGenerator(&curand_generator_, + CURAND_RNG_PSEUDO_DEFAULT)); + PADDLE_ENFORCE( + dynload::curandSetPseudoRandomGeneratorSeed(curand_generator_, seed_)); + + PADDLE_ENFORCE(dynload::curandSetStream(curand_generator_, stream_)); } - return *(rand_engine_.get()); + return curand_generator_; } cudaStream_t CUDADeviceContext::stream() { return stream_; } diff --git a/paddle/platform/device_context.h b/paddle/platform/device_context.h index e4de3807cd..7013343a8d 100644 --- a/paddle/platform/device_context.h +++ b/paddle/platform/device_context.h @@ -15,10 +15,9 @@ limitations under the License. */ #include "paddle/platform/place.h" #ifndef PADDLE_ONLY_CPU -#include -#include #include "paddle/platform/dynload/cublas.h" #include "paddle/platform/dynload/cudnn.h" +#include "paddle/platform/dynload/curand.h" #include "paddle/platform/gpu_info.h" #define EIGEN_USE_GPU #endif @@ -80,7 +79,8 @@ class CUDADeviceContext : public DeviceContext { /*! \brief Return cudnn handle in the device context. */ cudnnHandle_t cudnn_handle(); - thrust::minstd_rand& CPUDeviceContext::rand_engine(); + /*! \brief Return curand handle in the device context. */ + curandGenerator_t curand_generator(); /*! \brief Return cuda stream in the device context. */ cudaStream_t stream(); From 2f47f35b3efec36189a4c6757490b897130d3028 Mon Sep 17 00:00:00 2001 From: qijun Date: Mon, 21 Aug 2017 09:12:25 +0000 Subject: [PATCH 062/138] fix gpu build error --- paddle/operators/math/CMakeLists.txt | 4 ++-- paddle/operators/math/math_function.cc | 10 +++++----- paddle/operators/math/math_function.cu | 15 ++++++++------- paddle/operators/math/math_function.h | 7 ++----- paddle/operators/uniform_random_op.cu | 9 +++------ paddle/platform/device_context.cc | 10 +++++----- paddle/platform/device_context.h | 6 +++--- 7 files changed, 28 insertions(+), 33 deletions(-) diff --git a/paddle/operators/math/CMakeLists.txt b/paddle/operators/math/CMakeLists.txt index ed51d416ed..228f463f2b 100644 --- a/paddle/operators/math/CMakeLists.txt +++ b/paddle/operators/math/CMakeLists.txt @@ -1,8 +1,8 @@ if(WITH_GPU) - nv_library(math_function SRCS math_function.cc math_function.cu DEPS cblas device_context) + nv_library(math_function SRCS math_function.cc math_function.cu DEPS cblas device_context eigen3) else() - cc_library(math_function SRCS math_function.cc DEPS cblas device_context) + cc_library(math_function SRCS math_function.cc DEPS cblas device_context eigen3) endif() nv_test(math_function_test SRCS math_function_test.cc DEPS math_function tensor) diff --git a/paddle/operators/math/math_function.cc b/paddle/operators/math/math_function.cc index d0b1f8ee48..a098e02f95 100644 --- a/paddle/operators/math/math_function.cc +++ b/paddle/operators/math/math_function.cc @@ -110,12 +110,12 @@ void matmul(const framework::Tensor& matrix_a, } template <> -void Set(const int n, const float alpha, - float* output, - platform::DeviceContext* context) { +void Set(const int n, const float alpha, + float* output, + platform::DeviceContext* context) { auto* cpu_context = reinterpret_cast(context); - framework::EigenVector::Type out(output, n); - out.device(*(cpu_context->eigen_device())) = t.constant(T(alpha)); + framework::EigenVector::Type out(output, n); + out.device(*(cpu_context->eigen_device())) = out.constant(float(alpha)); } template <> diff --git a/paddle/operators/math/math_function.cu b/paddle/operators/math/math_function.cu index 76bbf790db..3ff622f308 100644 --- a/paddle/operators/math/math_function.cu +++ b/paddle/operators/math/math_function.cu @@ -127,12 +127,12 @@ void matmul(const framework::Tensor& matrix_a, } template <> -void Set(const int n, const float alpha, - float* output, - platform::DeviceContext* context) { +void Set(const int n, const float alpha, + float* output, + platform::DeviceContext* context) { auto* cuda_context = reinterpret_cast(context); - framework::EigenVector::Type out(output, n); - out.device(*(cuda_context->eigen_device())) = t.constant(T(alpha)); + framework::EigenVector::Type out(output, n); + out.device(*(cuda_context->eigen_device())) = out.constant(float(alpha)); } template @@ -159,12 +159,13 @@ void RandUniform(const int n, const float min, template int HandleOddLengthRandGaussian(const int n, const T mean, const T std, - T* output, CUDADeviceContext* context) { + T* output, + platform::CUDADeviceContext* context) { if (n % 2 == 1) { std::default_random_engine generator; std::normal_distribution distribution(mean, std); const T random_value = distribution(generator); - Set(1, random_value, output + (n - 1), context); + Set(1, random_value, output + (n - 1), context); return n - 1; } return n; diff --git a/paddle/operators/math/math_function.h b/paddle/operators/math/math_function.h index afe6de7483..6543a1b515 100644 --- a/paddle/operators/math/math_function.h +++ b/paddle/operators/math/math_function.h @@ -52,9 +52,9 @@ int LAPACKE_dgetri(int matrix_layout, int n, double* a, int lda, #include +#include "paddle/framework/eigen.h" #include "paddle/framework/tensor.h" #include "paddle/platform/device_context.h" -#include "paddle/platform/eigen.h" #include "paddle/platform/enforce.h" namespace paddle { @@ -80,10 +80,7 @@ void matmul(const framework::Tensor& matrix_a, bool trans_a, template void Set(const int n, const T alpha, T* output, - platform::DeviceContext* context) { - framework::EigenVector::Type out(output, n); - out.device(*(context->eigen_device())) = t.constant(T(alpha)); -} + platform::DeviceContext* context); template void RandUniform(const int n, const T min, const T max, T* output, diff --git a/paddle/operators/uniform_random_op.cu b/paddle/operators/uniform_random_op.cu index 91368fa73e..1bfffc4778 100644 --- a/paddle/operators/uniform_random_op.cu +++ b/paddle/operators/uniform_random_op.cu @@ -14,9 +14,6 @@ #include "paddle/operators/uniform_random_op.h" -namespace paddle { -namespace operators { - -REGISTER_OP_GPU_KERNEL(uniform_random, - paddle::operators::GPUUniformRandomKernel< - paddle::platform::GPUPlace, float>); +REGISTER_OP_GPU_KERNEL( + uniform_random, + paddle::operators::UniformRandomKernel); diff --git a/paddle/platform/device_context.cc b/paddle/platform/device_context.cc index 5fd93555a5..ad9b4e42f3 100644 --- a/paddle/platform/device_context.cc +++ b/paddle/platform/device_context.cc @@ -25,9 +25,9 @@ CPUDeviceContext::CPUDeviceContext() { eigen_device_.reset(new Eigen::DefaultDevice()); } -CPUDeviceContext::CPUDeviceContext(CPUPlace place, int rand_seed) { +CPUDeviceContext::CPUDeviceContext(CPUPlace place, int seed) { eigen_device_.reset(new Eigen::DefaultDevice()); - rand_seed_ = rand_seed; + rand_seed_ = seed; } std::minstd_rand& CPUDeviceContext::rand_engine() { @@ -105,7 +105,7 @@ Eigen::GpuDevice* DeviceContext::get_eigen_device() const { } CUDADeviceContext::CUDADeviceContext(GPUPlace place, uint64_t seed) - : place_(place), seed_(seed) { + : place_(place), rand_seed_(seed) { SetDeviceId(place_.device); PADDLE_ENFORCE(cudaStreamCreate(&stream_)); eigen_stream_.reset(new EigenCudaStreamDevice()); @@ -162,8 +162,8 @@ curandGenerator_t CUDADeviceContext::curand_generator() { SetDeviceId(place_.device); PADDLE_ENFORCE(dynload::curandCreateGenerator(&curand_generator_, CURAND_RNG_PSEUDO_DEFAULT)); - PADDLE_ENFORCE( - dynload::curandSetPseudoRandomGeneratorSeed(curand_generator_, seed_)); + PADDLE_ENFORCE(dynload::curandSetPseudoRandomGeneratorSeed( + curand_generator_, rand_seed_)); PADDLE_ENFORCE(dynload::curandSetStream(curand_generator_, stream_)); } diff --git a/paddle/platform/device_context.h b/paddle/platform/device_context.h index 7013343a8d..e18f48fef5 100644 --- a/paddle/platform/device_context.h +++ b/paddle/platform/device_context.h @@ -40,7 +40,7 @@ class DeviceContext { class CPUDeviceContext : public DeviceContext { public: CPUDeviceContext(); - explicit CPUDeviceContext(CPUPlace place, int rand_seed = 0); + explicit CPUDeviceContext(CPUPlace place, int seed = 0); virtual ~CPUDeviceContext() {} Eigen::DefaultDevice* eigen_device() const; @@ -60,7 +60,7 @@ class EigenCudaStreamDevice; class CUDADeviceContext : public DeviceContext { public: - explicit CUDADeviceContext(GPUPlace place, uint64_t rand_seed = 0); + explicit CUDADeviceContext(GPUPlace place, uint64_t seed = 0); virtual ~CUDADeviceContext(); /*! \brief Wait for all operations completion in the stream. */ @@ -93,12 +93,12 @@ class CUDADeviceContext : public DeviceContext { std::unique_ptr eigen_stream_; uint64_t rand_seed_; - std::unique_ptr rand_engine_; // clang-format off cudaStream_t stream_{nullptr}; cudnnHandle_t cudnn_handle_{nullptr}; cublasHandle_t cublas_handle_{nullptr}; + curandGenerator_t curand_generator_{nullptr}; // clang-format on }; From 08c987d7c086e4176a27f2685712bbb9226e635e Mon Sep 17 00:00:00 2001 From: qijun Date: Mon, 21 Aug 2017 17:23:15 +0800 Subject: [PATCH 063/138] use dynload curand --- paddle/operators/gaussian_random_op.h | 4 ++-- paddle/operators/math/math_function.cu | 8 ++++---- paddle/operators/uniform_random_op.h | 4 ++-- 3 files changed, 8 insertions(+), 8 deletions(-) diff --git a/paddle/operators/gaussian_random_op.h b/paddle/operators/gaussian_random_op.h index 041390e954..c90b665fe0 100644 --- a/paddle/operators/gaussian_random_op.h +++ b/paddle/operators/gaussian_random_op.h @@ -34,5 +34,5 @@ class GaussianRandomKernel : public framework::OpKernel { math::RandGaussian(n, mean, std, data, device_context); } }; -} -} +} // namespace operators +} // namespace paddle diff --git a/paddle/operators/math/math_function.cu b/paddle/operators/math/math_function.cu index 3ff622f308..908efe9e0f 100644 --- a/paddle/operators/math/math_function.cu +++ b/paddle/operators/math/math_function.cu @@ -149,8 +149,8 @@ void RandUniform(const int n, const float min, const float max, float* output, platform::DeviceContext* context) { auto* cuda_context = reinterpret_cast(context); - PADDLE_ENFORCE( - curandGenerateUniform(cuda_context->curand_generator(), output, n)); + PADDLE_ENFORCE(platform::dynload::curandGenerateUniform( + cuda_context->curand_generator(), output, n)); int block = 512; int grid = (n + block - 1) / block; UniformShift<<stream()>>>(n, min, max, @@ -179,8 +179,8 @@ void RandGaussian(const int n, const float mean, const int even_n = HandleOddLengthRandGaussian(n, mean, std, output, cuda_context); - PADDLE_ENFORCE(curandGenerateNormal(cuda_context->curand_generator(), output, - even_n, mean, std)); + PADDLE_ENFORCE(platform::dynload::curandGenerateNormal( + cuda_context->curand_generator(), output, even_n, mean, std)); } } // namespace math diff --git a/paddle/operators/uniform_random_op.h b/paddle/operators/uniform_random_op.h index ec009b025e..dffa640f84 100644 --- a/paddle/operators/uniform_random_op.h +++ b/paddle/operators/uniform_random_op.h @@ -34,5 +34,5 @@ class UniformRandomKernel : public framework::OpKernel { math::RandUniform(n, min, max, data, device_context); } }; -} -} +} // namespace operators +} // namespace paddle From b054392e2abebb2a55dabeeb2f12e414bbc2c5af Mon Sep 17 00:00:00 2001 From: qijun Date: Mon, 21 Aug 2017 17:46:46 +0800 Subject: [PATCH 064/138] fix gaussion op bug --- paddle/operators/gaussian_random_op.cc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/operators/gaussian_random_op.cc b/paddle/operators/gaussian_random_op.cc index aba8c6e5cd..899f05fa47 100644 --- a/paddle/operators/gaussian_random_op.cc +++ b/paddle/operators/gaussian_random_op.cc @@ -23,7 +23,7 @@ class GaussianRandomOp : public framework::OperatorWithKernel { protected: void InferShape(const framework::InferShapeContext& context) const override { - auto* tensor = context.Output(0); + auto* tensor = context.Output("Out"); auto dims = GetAttr>("dims"); PADDLE_ENFORCE(dims.size() > 0UL, "dims can be one int or array. dims must be set."); From d3f219aa9911015bd8c4a1316b85620a07eb9f49 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Mon, 21 Aug 2017 18:09:17 +0800 Subject: [PATCH 065/138] Change IdentityOp to ScaleOp --- paddle/framework/CMakeLists.txt | 2 +- paddle/framework/pybind.cc | 3 +- paddle/framework/tensor.h | 5 +- paddle/operators/CMakeLists.txt | 2 +- paddle/operators/identity_op.cc | 71 ------------ paddle/operators/net_op.cc | 9 +- paddle/operators/scale_op.cc | 102 ++++++++++++++++++ .../operators/{identity_op.cu => scale_op.cu} | 5 +- .../operators/{identity_op.h => scale_op.h} | 16 ++- .../paddle/v2/framework/tests/CMakeLists.txt | 2 +- .../v2/framework/tests/gradient_checker.py | 7 +- ...ty_op.py => test_scale_and_identity_op.py} | 19 ++++ 12 files changed, 158 insertions(+), 85 deletions(-) delete mode 100644 paddle/operators/identity_op.cc create mode 100644 paddle/operators/scale_op.cc rename paddle/operators/{identity_op.cu => scale_op.cu} (81%) rename paddle/operators/{identity_op.h => scale_op.h} (66%) rename python/paddle/v2/framework/tests/{test_identity_op.py => test_scale_and_identity_op.py} (51%) diff --git a/paddle/framework/CMakeLists.txt b/paddle/framework/CMakeLists.txt index f249512f47..5df14ae78d 100644 --- a/paddle/framework/CMakeLists.txt +++ b/paddle/framework/CMakeLists.txt @@ -56,5 +56,5 @@ cc_library(paddle_pybind SHARED uniform_random_op gaussian_random_op fill_zeros_like_op - identity_op) + scale_op) endif(WITH_PYTHON) diff --git a/paddle/framework/pybind.cc b/paddle/framework/pybind.cc index ddb244623f..3aaf0de150 100644 --- a/paddle/framework/pybind.cc +++ b/paddle/framework/pybind.cc @@ -42,7 +42,8 @@ USE_OP(fill_zeros_like); USE_OP_ITSELF(recurrent_op); USE_OP(gaussian_random); USE_OP(uniform_random); -USE_OP(identity); +USE_OP(scale); +USE_OP_ITSELF(identity); namespace paddle { namespace framework { diff --git a/paddle/framework/tensor.h b/paddle/framework/tensor.h index b8c779f4e5..643f875491 100644 --- a/paddle/framework/tensor.h +++ b/paddle/framework/tensor.h @@ -105,7 +105,10 @@ class Tensor { template inline Tensor Slice(const int& begin_idx, const int& end_idx) const; - platform::Place place() const { return holder_->place(); } + platform::Place place() const { + PADDLE_ENFORCE_NOT_NULL(holder_, "Tensor get place() must contains holder"); + return holder_->place(); + } private: template diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index 20e562c7d3..0ba598823b 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -68,4 +68,4 @@ op_library(recurrent_op SRCS recurrent_op.cc rnn/recurrent_op_utils.cc DEPS framework_proto tensor op_registry operator net_op) op_library(uniform_random_op SRCS uniform_random_op.cc uniform_random_op.cu) -op_library(identity_op SRCS identity_op.cc identity_op.cu DEPS net_op) +op_library(scale_op SRCS scale_op.cc scale_op.cu DEPS net_op) diff --git a/paddle/operators/identity_op.cc b/paddle/operators/identity_op.cc deleted file mode 100644 index cac44020bc..0000000000 --- a/paddle/operators/identity_op.cc +++ /dev/null @@ -1,71 +0,0 @@ -/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - - Licensed under the Apache License, Version 2.0 (the "License"); - you may not use this file except in compliance with the License. - You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the License for the specific language governing permissions and - limitations under the License. */ - -#include "paddle/operators/identity_op.h" -#include "paddle/operators/net_op.h" - -namespace paddle { -namespace operators { - -class IdentityOp : public framework::OperatorWithKernel { - public: - IdentityOp(const std::string &type, const VarNameMap &inputs, - const VarNameMap &outputs, const framework::AttributeMap &attrs) - : OperatorWithKernel(type, inputs, outputs, attrs) {} - - protected: - void InferShape(const framework::InferShapeContext &ctx) const override { - auto *in = ctx.Input("X"); - auto *out = ctx.Output("Out"); - out->Resize(in->dims()); - } -}; - -class IdentityOpMaker : public framework::OpProtoAndCheckerMaker { - public: - IdentityOpMaker(framework::OpProto *proto, - framework::OpAttrChecker *op_checker) - : OpProtoAndCheckerMaker(proto, op_checker) { - AddInput("X", "The input tensor of identity operator.").NotInGradient(); - AddOutput("Out", "The output tensor of identity operator.").NotInGradient(); - AddComment(R"DOC(Identity operator - -The equation is: Out = X -)DOC"); - } -}; - -// Identity Op's gradient is identity op, too. -// Grad(Out=identity_op(X)) => Grad(X) = identity_op(Grad(Out)) -class IdentityGradOp : public NetOp { - public: - IdentityGradOp(const std::string &type, const VarNameMap &inputs, - const VarNameMap &outputs, - const framework::AttributeMap &attrs) - : NetOp(type, inputs, outputs, attrs) { - AddOp(framework::OpRegistry::CreateOp( - "identity", {{"X", {Input(framework::GradVarName("Out"))}}}, - {{"Out", {Output(framework::GradVarName("X"))}}}, {})); - CompleteAddOp(false); - } -}; - -} // namespace operators -} // namespace paddle - -namespace ops = paddle::operators; - -REGISTER_OP(identity, ops::IdentityOp, ops::IdentityOpMaker, identity_grad, - ops::IdentityGradOp); -REGISTER_OP_CPU_KERNEL(identity, ops::IdentityKernel); diff --git a/paddle/operators/net_op.cc b/paddle/operators/net_op.cc index a7d7105110..7e3779ed2e 100644 --- a/paddle/operators/net_op.cc +++ b/paddle/operators/net_op.cc @@ -68,10 +68,15 @@ std::string NetOp::DebugString() const { bool NetOp::IsNetOp() const { return true; } std::vector NetOp::OutputVars(bool has_intermediate) const { + std::vector all; + for (auto& pair : this->outputs_) { + for (auto& var_name : pair.second) { + all.push_back(var_name); + } + } if (has_intermediate) { - return this->outputs_.at(kAll); + return all; } - auto& all = this->outputs_.at(kAll); std::vector ret_val; for (auto& each : all) { if (!Contains(intermediate_outputs_, each)) { diff --git a/paddle/operators/scale_op.cc b/paddle/operators/scale_op.cc new file mode 100644 index 0000000000..3b18ff078e --- /dev/null +++ b/paddle/operators/scale_op.cc @@ -0,0 +1,102 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#include "paddle/operators/scale_op.h" +#include "paddle/operators/net_op.h" + +namespace paddle { +namespace operators { + +class ScaleOp : public framework::OperatorWithKernel { + public: + ScaleOp(const std::string &type, const VarNameMap &inputs, + const VarNameMap &outputs, const framework::AttributeMap &attrs) + : OperatorWithKernel(type, inputs, outputs, attrs) {} + + protected: + void InferShape(const framework::InferShapeContext &ctx) const override { + auto *in = ctx.Input("X"); + auto *out = ctx.Output("Out"); + out->Resize(in->dims()); + } +}; + +template +class ScaleOpMaker : public framework::OpProtoAndCheckerMaker { + public: + ScaleOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker) + : OpProtoAndCheckerMaker(proto, op_checker) { + AddInput("X", "The input tensor of scale operator.").NotInGradient(); + AddOutput("Out", "The output tensor of scale operator.").NotInGradient(); + AddComment(R"DOC(Scale operator + +The equation is: Out = scale*X +)DOC"); + AddAttr("scale", "scale of scale operator.").SetDefault(1.0); + } +}; + +// Identity Op's gradient is identity op, too. +// Grad(Out=scale(X)) => Grad(X) = scale(Grad(Out)) +template +class ScaleGradOp : public NetOp { + public: + ScaleGradOp(const std::string &type, const VarNameMap &inputs, + const VarNameMap &outputs, const framework::AttributeMap &attrs) + : NetOp(type, inputs, outputs, attrs) { + AddOp(framework::OpRegistry::CreateOp( + "scale", {{"X", {Input(framework::GradVarName("Out"))}}}, + {{"Out", {Output(framework::GradVarName("X"))}}}, + {{"scale", GetAttr("scale")}})); + CompleteAddOp(false); + } +}; + +// identity is a alias of scale op. This is also a example for creating a alias +// operator. +template +class IdentityOpMaker : public framework::OpProtoAndCheckerMaker { + public: + IdentityOpMaker(framework::OpProto *proto, + framework::OpAttrChecker *op_checker) + : OpProtoAndCheckerMaker(proto, op_checker) { + AddInput("X", "input tensor of identity op"); + AddOutput("Out", "output tensor of identity op"); + AddComment("identity operator. Just a alias of scale op which scale = 1.0"); + } +}; + +template +class IdentityOp : public NetOp { + public: + IdentityOp(const std::string &type, const VarNameMap &inputs, + const VarNameMap &outputs, const framework::AttributeMap &attrs) + : NetOp(type, inputs, outputs, attrs) { + AddOp(framework::OpRegistry::CreateOp( + "scale", {{"X", {Input("X")}}}, {{"Out", {Output("Out")}}}, + {{"scale", static_cast(1)}})); + } +}; + +} // namespace operators +} // namespace paddle + +namespace ops = paddle::operators; + +REGISTER_OP(scale, ops::ScaleOp, ops::ScaleOpMaker, scale_grad, + ops::ScaleGradOp); +REGISTER_OP_CPU_KERNEL(scale, + ops::ScaleKernel); +REGISTER_OP_WITHOUT_GRADIENT(identity, ops::IdentityOp, + ops::IdentityOpMaker); diff --git a/paddle/operators/identity_op.cu b/paddle/operators/scale_op.cu similarity index 81% rename from paddle/operators/identity_op.cu rename to paddle/operators/scale_op.cu index 3053104bbe..63efbe0da8 100644 --- a/paddle/operators/identity_op.cu +++ b/paddle/operators/scale_op.cu @@ -12,6 +12,7 @@ See the License for the specific language governing permissions and limitations under the License. */ -#include "paddle/operators/identity_op.h" +#include "paddle/operators/scale_op.h" -REGISTER_OP_GPU_KERNEL(identity, paddle::operators::IdentityKernel); +REGISTER_OP_GPU_KERNEL( + scale, paddle::operators::ScaleKernel); diff --git a/paddle/operators/identity_op.h b/paddle/operators/scale_op.h similarity index 66% rename from paddle/operators/identity_op.h rename to paddle/operators/scale_op.h index 14a832257b..aea64f1b04 100644 --- a/paddle/operators/identity_op.h +++ b/paddle/operators/scale_op.h @@ -14,17 +14,25 @@ #pragma once +#include "paddle/framework/eigen.h" #include "paddle/framework/op_registry.h" -#include "paddle/memory/memcpy.h" + namespace paddle { namespace operators { -template -class IdentityKernel : public framework::OpKernel { +template +class ScaleKernel : public framework::OpKernel { public: virtual void Compute(const framework::ExecutionContext& context) const { auto* tensor = context.Output("Out"); auto* in = context.Input("X"); - tensor->CopyFrom(*in, in->place()); + tensor->mutable_data(in->place()); + + auto scale = static_cast(context.op_.GetAttr("scale")); + + auto eigen_out = framework::EigenVector::Flatten(*tensor); + auto eigen_in = framework::EigenVector::Flatten(*in); + auto& dev = context.GetEigenDevice(); + eigen_out.device(dev) = scale * eigen_in; } }; diff --git a/python/paddle/v2/framework/tests/CMakeLists.txt b/python/paddle/v2/framework/tests/CMakeLists.txt index cf7baa5556..0e8811bfe7 100644 --- a/python/paddle/v2/framework/tests/CMakeLists.txt +++ b/python/paddle/v2/framework/tests/CMakeLists.txt @@ -27,4 +27,4 @@ py_test(test_uniform_random_op SRCS test_uniform_random_op.py) py_test(test_recurrent_op SRCS test_recurrent_op.py) py_test(test_sgd_op SRCS test_sgd_op.py) py_test(test_gradient_checker SRCS test_gradient_checker.py) -py_test(test_identity_op SRCS test_identity_op.py) +py_test(test_scale_and_identity_op SRCS test_scale_and_identity_op.py) diff --git a/python/paddle/v2/framework/tests/gradient_checker.py b/python/paddle/v2/framework/tests/gradient_checker.py index 8b8e2f444b..c22c6f8831 100644 --- a/python/paddle/v2/framework/tests/gradient_checker.py +++ b/python/paddle/v2/framework/tests/gradient_checker.py @@ -160,8 +160,13 @@ class GradientChecker(unittest.TestCase): grad_tensor.set(data, place) # run backward op - for name in backward_op.outputs(): + backward_outs = backward_op.outputs() + backward_names = [ + item for key in backward_outs for item in backward_outs[key] + ] + for name in backward_names: scope.new_var(name) + backward_op.infer_shape(scope) backward_op.run(scope, ctx) diff --git a/python/paddle/v2/framework/tests/test_identity_op.py b/python/paddle/v2/framework/tests/test_scale_and_identity_op.py similarity index 51% rename from python/paddle/v2/framework/tests/test_identity_op.py rename to python/paddle/v2/framework/tests/test_scale_and_identity_op.py index 181d9c0c21..69b301c376 100644 --- a/python/paddle/v2/framework/tests/test_identity_op.py +++ b/python/paddle/v2/framework/tests/test_scale_and_identity_op.py @@ -2,6 +2,7 @@ import unittest from op_test_util import OpTestMeta from gradient_checker import GradientChecker, create_op import numpy as np +from paddle.v2.framework.op import Operator class IdentityTest(unittest.TestCase): @@ -20,5 +21,23 @@ class IdentityGradOpTest(GradientChecker): self.check_grad(op, inputs, set("X"), "Out") +class ScaleTest(unittest.TestCase): + __metaclass__ = OpTestMeta + + def setUp(self): + self.type = "scale" + self.inputs = {'X': np.random.random((32, 784)).astype("float32")} + self.attrs = {'scale': -2.3} + self.outputs = {'Out': self.inputs['X'] * self.attrs['scale']} + + +class ScaleGradTest(GradientChecker): + def test_normal(self): + op = Operator("scale", X="X", Out="Out", scale=3.2) + self.check_grad(op, + {"X": np.random.random((10, 10)).astype("float32")}, + set("X"), "Out") + + if __name__ == '__main__': unittest.main() From 117ce4cbc1a16da1ba8489aaab754aa0ebe5d3ab Mon Sep 17 00:00:00 2001 From: guosheng Date: Mon, 21 Aug 2017 19:23:42 +0800 Subject: [PATCH 066/138] Change class to struct in GemmFunctor to avoid errors on special compilers --- paddle/function/GemmFunctor.cpp | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/paddle/function/GemmFunctor.cpp b/paddle/function/GemmFunctor.cpp index dc83278d8e..9e25ee58a1 100644 --- a/paddle/function/GemmFunctor.cpp +++ b/paddle/function/GemmFunctor.cpp @@ -84,7 +84,7 @@ struct BlasGemm { } }; -template class BlasGemm; -template class BlasGemm; +template struct BlasGemm; +template struct BlasGemm; } // namespace paddle From 950dbde56c989f79bace3d53ae38bfae26e84c53 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Mon, 21 Aug 2017 08:41:35 -0700 Subject: [PATCH 067/138] fix rowwise add grad op --- paddle/operators/rowwise_add_op.h | 2 +- python/paddle/v2/framework/tests/test_rowwise_add_op.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/paddle/operators/rowwise_add_op.h b/paddle/operators/rowwise_add_op.h index 232135c38d..771c5d7c0a 100644 --- a/paddle/operators/rowwise_add_op.h +++ b/paddle/operators/rowwise_add_op.h @@ -63,7 +63,7 @@ class RowwiseAddGradKernel : public framework::OpKernel { // https://eigen.tuxfamily.org/dox/unsupported/TensorBase_8h_source.html // colwise add - Eigen::array dims{{1}}; /* dimension to reduce */ + Eigen::array dims{{0}}; /* dimension to reduce */ EigenVector::Flatten(*db).device(place) = OutGrad.sum(dims); } }; diff --git a/python/paddle/v2/framework/tests/test_rowwise_add_op.py b/python/paddle/v2/framework/tests/test_rowwise_add_op.py index 29d72e8500..45d569da29 100644 --- a/python/paddle/v2/framework/tests/test_rowwise_add_op.py +++ b/python/paddle/v2/framework/tests/test_rowwise_add_op.py @@ -20,7 +20,7 @@ class RowwiseAddGradOpTest(GradientChecker): def test_rowwise_add(self): op = create_op("rowwise_add") inputs = { - "X": np.random.uniform(0.1, 1, [10, 10]).astype("float32"), + "X": np.random.uniform(0.1, 1, [5, 10]).astype("float32"), "b": np.random.uniform(0.1, 1, [10]).astype("float32") } self.check_grad(op, inputs, set(["X", "b"]), "Out") From a75a638fb16ac5b08509c3f185d25ec670d3cb12 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Mon, 21 Aug 2017 09:13:19 -0700 Subject: [PATCH 068/138] format Copyright --- paddle/operators/rowwise_add_op.h | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/paddle/operators/rowwise_add_op.h b/paddle/operators/rowwise_add_op.h index 771c5d7c0a..1cbd8bb31a 100644 --- a/paddle/operators/rowwise_add_op.h +++ b/paddle/operators/rowwise_add_op.h @@ -1,16 +1,16 @@ /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - Licensed under the Apache License, Version 2.0 (the "License"); - you may not use this file except in compliance with the License. - You may obtain a copy of the License at +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at - http://www.apache.org/licenses/LICENSE-2.0 + http://www.apache.org/licenses/LICENSE-2.0 - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the License for the specific language governing permissions and - limitations under the License. */ +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ #pragma once #include "paddle/framework/eigen.h" From 93539093f4727d4028ca7e592f5fa4f7abdb8bc3 Mon Sep 17 00:00:00 2001 From: xuwei06 Date: Wed, 2 Aug 2017 11:28:25 -0700 Subject: [PATCH 069/138] Allow boot_bias for recurrent group to be static --- paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp b/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp index f98bf95064..157b1ab451 100644 --- a/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp +++ b/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp @@ -184,7 +184,7 @@ public: } void backward(const UpdateCallback& callback) override { - if (biases_) { + if (biases_ && biases_->getWGrad()) { backwardActivation(); biases_->getWGrad()->collectBias(*getOutputGrad(), 1); biases_->getParameterPtr()->incUpdate(callback); From d7b80f03b0064ac9db5db5f313bc381f9046f689 Mon Sep 17 00:00:00 2001 From: xuwei06 Date: Wed, 2 Aug 2017 11:29:46 -0700 Subject: [PATCH 070/138] Correctly handle width and height for some layers --- python/paddle/trainer/config_parser.py | 11 ++++--- .../paddle/trainer_config_helpers/layers.py | 29 +++++++++++++++---- 2 files changed, 30 insertions(+), 10 deletions(-) diff --git a/python/paddle/trainer/config_parser.py b/python/paddle/trainer/config_parser.py index 8d71629faa..b3d5ef95cc 100644 --- a/python/paddle/trainer/config_parser.py +++ b/python/paddle/trainer/config_parser.py @@ -338,7 +338,8 @@ def RecurrentLayerGroupWithoutOutLinksBegin(name, in_links_count += 1 layer_name = MakeLayerNameInParentSubmodel(name) layer = g_layer_map[layer_name] - ScatterAgentLayer(name=name, size=layer.size) + ScatterAgentLayer( + name=name, size=layer.size, width=layer.width, height=layer.height) pair = g_current_submodel.in_links.add() pair.layer_name = layer_name @@ -2197,8 +2198,8 @@ class MaxOutLayer(LayerBase): maxout_conf = self.config.inputs[0].maxout_conf parse_maxout(self.inputs[0].maxout, input_layer.name, maxout_conf) out_channels = maxout_conf.image_conf.channels / maxout_conf.groups - self.set_cnn_layer(name, g_layer_map[input_layer.name].height, - g_layer_map[input_layer.name].width, out_channels) + self.set_cnn_layer(name, maxout_conf.image_conf.img_size_y, + maxout_conf.image_conf.img_size, out_channels) @config_layer('row_conv') @@ -2405,9 +2406,11 @@ class GatherAgentLayer(LayerBase): @config_layer('scatter_agent') class ScatterAgentLayer(LayerBase): - def __init__(self, name, size, device=None): + def __init__(self, name, size, width=None, height=None, device=None): super(ScatterAgentLayer, self).__init__( name, 'scatter_agent', size, inputs=[], device=device) + if height and width: + self.set_layer_height_width(height, width) @config_layer('multiplex') diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py index c9e3ded65c..dd6d1f7f8c 100755 --- a/python/paddle/trainer_config_helpers/layers.py +++ b/python/paddle/trainer_config_helpers/layers.py @@ -16,11 +16,13 @@ import functools import collections import inspect +import paddle.trainer.config_parser as cp from paddle.trainer.config_parser import * from .activations import LinearActivation, SigmoidActivation, TanhActivation, \ ReluActivation, IdentityActivation, SoftmaxActivation, BaseActivation from .evaluators import * -from .poolings import MaxPooling, AvgPooling, BasePoolingType +from .poolings import MaxPooling, AvgPooling, BasePoolingType, \ + CudnnAvgPooling, CudnnMaxPooling from .attrs import * from .default_decorators import * @@ -330,6 +332,14 @@ class LayerOutput(object): self.outputs = outputs self.reverse = reverse + @property + def width(self): + return cp.g_layer_map[self.full_name].width + + @property + def height(self): + return cp.g_layer_map[self.full_name].height + def set_input(self, input): """ Set the input for a memory layer. Can only be used for memory layer @@ -911,7 +921,13 @@ def data_layer(name, size, height=None, width=None, layer_attr=None): width=width, **ExtraLayerAttribute.to_kwargs(layer_attr)) - return LayerOutput(name, LayerType.DATA, size=size) + num_filters = None + if height is not None and width is not None: + num_filters = size / (width * height) + assert num_filters * width * height == size, \ + "size=%s width=%s height=%s" % (size, width, height) + + return LayerOutput(name, LayerType.DATA, size=size, num_filters=num_filters) @wrap_name_default("embedding") @@ -2571,6 +2587,10 @@ def img_pool_layer(input, assert input.num_filters is not None num_channels = input.num_filters + assert type(pool_type) in [AvgPooling, MaxPooling, CudnnAvgPooling, + CudnnMaxPooling], \ + "only AvgPooling and MaxPooling are supported" + if pool_type is None: pool_type = MaxPooling() elif isinstance(pool_type, AvgPooling): @@ -2580,7 +2600,6 @@ def img_pool_layer(input, if ( isinstance(pool_type, AvgPooling) or isinstance(pool_type, MaxPooling)) \ else pool_type.name - pool_size_y = pool_size if pool_size_y is None else pool_size_y stride_y = stride if stride_y is None else stride_y padding_y = padding if padding_y is None else padding_y @@ -4204,8 +4223,7 @@ def conv_operator(img, num_channels = img.num_filters assert isinstance(filter, LayerOutput) - if filter.size is not None: - filter.size = filter_size * filter_size_y * num_filters * num_channels + assert filter.size is not None opCls = ConvTransOperator if trans else ConvOperator @@ -4916,7 +4934,6 @@ def maxout_layer(input, groups, num_channels=None, name=None, layer_attr=None): :return: LayerOutput object. :rtype: LayerOutput """ - assert input.layer_type == LayerType.CONV_LAYER assert isinstance(input.activation, LinearActivation) assert groups > 1 if num_channels is None: From 99af29e3f29f0392727bba312282e56a431dfc7b Mon Sep 17 00:00:00 2001 From: xuwei06 Date: Mon, 21 Aug 2017 14:17:13 -0700 Subject: [PATCH 071/138] Fix error message for img_pool_layer --- python/paddle/trainer_config_helpers/layers.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py index dd6d1f7f8c..be854c38f7 100755 --- a/python/paddle/trainer_config_helpers/layers.py +++ b/python/paddle/trainer_config_helpers/layers.py @@ -2589,7 +2589,7 @@ def img_pool_layer(input, assert type(pool_type) in [AvgPooling, MaxPooling, CudnnAvgPooling, CudnnMaxPooling], \ - "only AvgPooling and MaxPooling are supported" + "only (Cudnn)AvgPooling, (Cudnn)MaxPooling are supported" if pool_type is None: pool_type = MaxPooling() @@ -6236,11 +6236,11 @@ def kmax_sequence_score_layer(input, name=None, beam_size=1): @wrap_bias_attr_default() def scale_shift_layer(input, name=None, param_attr=None, bias_attr=None): """ - A layer applies a linear transformation to each element in each row of - the input matrix. For each element, the layer first re-scale it and then + A layer applies a linear transformation to each element in each row of + the input matrix. For each element, the layer first re-scale it and then adds a bias to it. - This layer is very like the SlopeInterceptLayer, except the scale and + This layer is very like the SlopeInterceptLayer, except the scale and bias are trainable. .. math:: From 118dd1494fbe3654da8f71c2245523e27616d475 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Mon, 21 Aug 2017 18:22:59 -0700 Subject: [PATCH 072/138] can run, for debug --- .../paddle/v2/framework/tests/CMakeLists.txt | 1 + python/paddle/v2/framework/tests/mnist.py | 73 +++++++++++++++++-- 2 files changed, 66 insertions(+), 8 deletions(-) diff --git a/python/paddle/v2/framework/tests/CMakeLists.txt b/python/paddle/v2/framework/tests/CMakeLists.txt index ce57a07130..41682c8350 100644 --- a/python/paddle/v2/framework/tests/CMakeLists.txt +++ b/python/paddle/v2/framework/tests/CMakeLists.txt @@ -27,3 +27,4 @@ py_test(test_uniform_random_op SRCS test_uniform_random_op.py) py_test(test_recurrent_op SRCS test_recurrent_op.py) py_test(test_sgd_op SRCS test_sgd_op.py) py_test(test_gradient_checker SRCS test_gradient_checker.py) +py_test(mnist SRCS mnist.py) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index 32a088ac28..d0c56c457d 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -2,7 +2,7 @@ import paddle.v2.framework.core as core from paddle.v2.framework.op import Operator import numpy -BATCH_SIZE = 100 +BATCH_SIZE = 2 scope = core.Scope() place = core.CPUPlace() @@ -35,10 +35,15 @@ def data_layer(name, dims): def feed_data(name, data): - assert isinstance(data, numpy.array) + assert isinstance(data, numpy.ndarray) tensor = scope.find_var(name).get_tensor() tensor.set_dims(data.shape) - tensor.alloc_float(place) + if data.dtype == numpy.dtype('int32'): + tensor.alloc_float(place) + elif data.dtype == numpy.dtype('float32'): + tensor.alloc_int(place) + else: + raise ValueError("data type not supported") tensor.set(data, place) @@ -49,7 +54,11 @@ def grad_var_name(var_name): def sgd_optimizer(net, param_name, learning_rate=0.01): grad_name = grad_var_name(param_name) optimize_op = Operator( - "sgd", param=param_name, grad=grad_name, learning_rate=learning_rate) + "sgd", + param=param_name, + grad=grad_name, + param_out=param_name, + learning_rate=learning_rate) net.add_op(optimize_op) @@ -65,7 +74,7 @@ def init_param(param_name, dims): # fc_layer -def fc_layer(net, input, size, act="sigmoid", bias=True, param=None, name=None): +def fc_layer(net, input, size, act="softmax", bias=True, param=None, name=None): """ Add a fc layer to net @@ -125,16 +134,64 @@ def cross_entropy_layer(net, input, label): return cost_name +def get_backward_net(forward_net): + net = core.Operator.backward(forward_net, set()) + for input in net.inputs()["all"]: + var = scope.new_var(input) + var.get_tensor() + for output in net.outputs()["all"]: + var = scope.new_var(output) + var.get_tensor() + return net + + +def print_inputs_outputs(op): + print("===============" + op.type() + "==============") + print("***inputs:***") + for input in op.inputs()["all"]: + print input, scope.find_var(input).get_tensor().get_dims() + print("***outputs:***") + for output in op.outputs()["all"]: + print output, scope.find_var(output).get_tensor().get_dims() + print("") + print("") + + images = data_layer(name='pixel', dims=[BATCH_SIZE, 784]) label = data_layer(name='label', dims=[BATCH_SIZE]) fc = fc_layer(net=forward_network, input=images, size=10, act="softmax") cost = cross_entropy_layer(net=forward_network, input=fc, label=label) forward_network.complete_add_op(True) print(forward_network) -backward_net = core.Operator.backward(forward_network, set()) - +backward_net = get_backward_net(forward_network) print(backward_net) +optimize_net.complete_add_op(True) +print(optimize_net) PASS_NUM = 10 for pass_id in range(PASS_NUM): - print pass_id + print("===========forward==========") + feed_data("pixel", numpy.random.random((BATCH_SIZE, 784)).astype('float32')) + feed_data("label", numpy.ones(BATCH_SIZE).astype("int32")) + forward_network.infer_shape(scope) + print_inputs_outputs(forward_network) + + print(numpy.array(scope.find_var("label").get_tensor())) + forward_network.run(scope, dev_ctx) + # print(numpy.array(scope.find_var("fc_0").get_tensor())) + + print("===========backward==========") + cost_data = numpy.array(scope.find_var("cross_entropy_1").get_tensor()) + cost_grad = scope.find_var(grad_var_name("cross_entropy_1")).get_tensor() + cost_grad.set_dims(cost_data.shape) + cost_grad.alloc_float(place) + cost_grad.set(cost_data, place) + + backward_net.infer_shape(scope) + print_inputs_outputs(backward_net) + + backward_net.run(scope, dev_ctx) + + print("===========optimize_net==========") + print_inputs_outputs(optimize_net) + optimize_net.run(scope, dev_ctx) From 53e71b44f41860e6482651b9e92dd1e6d3213c8a Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Tue, 22 Aug 2017 03:28:21 +0000 Subject: [PATCH 073/138] gather op bp passed --- paddle/operators/CMakeLists.txt | 2 -- paddle/operators/gather.h | 6 +++--- paddle/operators/gather_op.cc | 8 ++++---- paddle/operators/gather_op.h | 19 ++++++++++--------- .../v2/framework/tests/test_gather_op.py | 18 ++++++++++++++---- 5 files changed, 31 insertions(+), 22 deletions(-) diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index 6849e39cb7..ba1362e8bf 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -44,8 +44,6 @@ endfunction() add_subdirectory(math) cc_test(gather_test SRCS gather_test.cc DEPS tensor) op_library(gather_op SRCS gather_op.cc gather_op.cu) -# DEPS op_registry) -# cc_test(gather_op_test SRCS gather_op_test.cc DEPS gather_op) cc_test(scatter_test SRCS scatter_test.cc DEPS tensor) diff --git a/paddle/operators/gather.h b/paddle/operators/gather.h index 3f299ea1a6..edac29f6db 100644 --- a/paddle/operators/gather.h +++ b/paddle/operators/gather.h @@ -27,13 +27,13 @@ namespace operators { // Implementation of CPU copy template -void CPUGather(const T* params, const int* indices, const int slice_size, +void CPUGather(const T* src, const int* indices, const int slice_size, const int index_size, T* output) { const size_t slice_bytes = slice_size * sizeof(T); for (int i = 0; i < index_size; ++i) { int index_ = indices[i]; - memcpy(output + i * slice_size, params + index_ * slice_size, slice_bytes); + memcpy(output + i * slice_size, src + index_ * slice_size, slice_bytes); } } @@ -57,7 +57,7 @@ void Gather(const platform::Place& place, const paddle::framework::Tensor* src, int index_size = index->dims()[0]; auto src_dims = src->dims(); - paddle::framework::DDim output_dims(src_dims); + framework::DDim output_dims(src_dims); output_dims[0] = index_size; // slice size diff --git a/paddle/operators/gather_op.cc b/paddle/operators/gather_op.cc index 499def05a7..123bed296c 100644 --- a/paddle/operators/gather_op.cc +++ b/paddle/operators/gather_op.cc @@ -26,9 +26,9 @@ class GatherOp : public framework::OperatorWithKernel { void InferShape(const framework::InferShapeContext &ctx) const override { int batch_size = ctx.Input("Index")->dims()[0]; PADDLE_ENFORCE_GE(batch_size, 0, "Batch size must be >0"); - paddle::framework::DDim output_dims(ctx.Input("X")->dims()); + framework::DDim output_dims(ctx.Input("X")->dims()); output_dims[0] = batch_size; - ctx.Output("Y")->Resize(output_dims); + ctx.Output("Out")->Resize(output_dims); } }; @@ -51,11 +51,11 @@ class GatherOpMaker : public framework::OpProtoAndCheckerMaker { : OpProtoAndCheckerMaker(proto, op_checker) { AddInput("X", "The source input of gather op"); AddInput("Index", "The index input of gather op"); - AddOutput("Y", "The output of add op"); + AddOutput("Out", "The output of add op"); AddComment(R"DOC( Gather Operator by selecting from the first axis, -Y = X[Index] +Out = X[Index] )DOC"); } }; diff --git a/paddle/operators/gather_op.h b/paddle/operators/gather_op.h index 13e4c9b058..381854f301 100644 --- a/paddle/operators/gather_op.h +++ b/paddle/operators/gather_op.h @@ -26,10 +26,10 @@ using Tensor = framework::Tensor; template class GatherOpKernel : public framework::OpKernel { public: - void Compute(const framework::ExecutionContext& ctx) const override { - auto X = ctx.Input("X"); - auto Index = ctx.Input("Index"); - auto Y = ctx.Output("Y"); + void Compute(const framework::ExecutionContext &ctx) const override { + auto *X = ctx.Input("X"); + auto *Index = ctx.Input("Index"); + auto *Y = ctx.Output("Out"); Y->mutable_data(ctx.GetPlace()); Gather(ctx.GetPlace(), X, Index, Y); @@ -39,12 +39,13 @@ class GatherOpKernel : public framework::OpKernel { template class GatherGradientOpKernel : public framework::OpKernel { public: - void Compute(const framework::ExecutionContext& ctx) const override { - auto Index = ctx.Input("Index"); - auto dX = ctx.Output(framework::GradVarName("X")); - auto dY = ctx.Input(framework::GradVarName("Y")); + void Compute(const framework::ExecutionContext &ctx) const override { + auto *Index = ctx.Input("Index"); + auto *dX = ctx.Output(framework::GradVarName("X")); + auto *dO = ctx.Input(framework::GradVarName("Out")); - ScatterUpdate(ctx.GetPlace(), dY, Index, dX); + dX->mutable_data(ctx.GetPlace()); + ScatterUpdate(ctx.GetPlace(), dO, Index, dX); } }; diff --git a/python/paddle/v2/framework/tests/test_gather_op.py b/python/paddle/v2/framework/tests/test_gather_op.py index 049054d07b..e868983042 100644 --- a/python/paddle/v2/framework/tests/test_gather_op.py +++ b/python/paddle/v2/framework/tests/test_gather_op.py @@ -1,11 +1,10 @@ import unittest - +from op_test_util import OpTestMeta +from gradient_checker import GradientChecker, create_op import numpy import paddle.v2.framework.core as core from paddle.v2.framework.op import Operator -from op_test_util import OpTestMeta - class TestGatherOp(unittest.TestCase): __metaclass__ = OpTestMeta @@ -17,7 +16,18 @@ class TestGatherOp(unittest.TestCase): 'X': xnp, 'Index': numpy.array([1, 3, 5]).astype("int32") } - self.outputs = {'Y': self.inputs['X'][self.inputs['Index']]} + self.outputs = {'Out': self.inputs['X'][self.inputs['Index']]} + + +class TestGatherGradOp(GradientChecker): + def test_gather_grad(self): + print 'creating op' + op = create_op("gather") + print 'creating op done' + xnp = numpy.random.random((10, 20)).astype("float32") + inputs = {'X': xnp, 'Index': numpy.array([1, 3, 5]).astype("int32")} + print 'correct before check gradient' + self.check_grad(op, inputs, set("X"), "Out") if __name__ == "__main__": From 36e8e725669a20b272f9ace1cf7c9df646c840a3 Mon Sep 17 00:00:00 2001 From: qijun Date: Tue, 22 Aug 2017 11:40:57 +0800 Subject: [PATCH 074/138] expose random seed to users --- paddle/operators/CMakeLists.txt | 4 +- paddle/operators/gaussian_random_op.cc | 42 ++++++++++--- paddle/operators/gaussian_random_op.cu | 61 +++++++++++++++--- paddle/operators/gaussian_random_op.h | 38 ----------- paddle/operators/math/math_function.cc | 22 ------- paddle/operators/math/math_function.cu | 48 -------------- paddle/operators/math/math_function.h | 8 --- paddle/operators/uniform_random_op.cc | 44 ++++++++++--- paddle/operators/uniform_random_op.cu | 63 ++++++++++++++++--- paddle/operators/uniform_random_op.h | 38 ----------- paddle/platform/device_context.cc | 27 +------- paddle/platform/device_context.h | 15 +---- .../tests/test_gaussian_random_op.py | 7 ++- .../framework/tests/test_uniform_random_op.py | 7 ++- 14 files changed, 196 insertions(+), 228 deletions(-) delete mode 100644 paddle/operators/gaussian_random_op.h delete mode 100644 paddle/operators/uniform_random_op.h diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index 8f22a5fbc3..a7c89787e4 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -58,7 +58,7 @@ op_library(rowwise_add_op SRCS rowwise_add_op.cu rowwise_add_op.cc) op_library(sigmoid_op SRCS sigmoid_op.cc sigmoid_op.cu) op_library(softmax_op SRCS softmax_op.cc softmax_op.cu) -op_library(gaussian_random_op SRCS gaussian_random_op.cc gaussian_random_op.cu DEPS math_function) +op_library(gaussian_random_op SRCS gaussian_random_op.cc gaussian_random_op.cu) op_library(cross_entropy_op SRCS cross_entropy_op.cc cross_entropy_op.cu) op_library(fill_zeros_like_op SRCS fill_zeros_like_op.cc fill_zeros_like_op.cu) @@ -67,4 +67,4 @@ op_library(sgd_op SRCS sgd_op.cc sgd_op.cu) op_library(recurrent_op SRCS recurrent_op.cc rnn/recurrent_op_utils.cc DEPS framework_proto tensor op_registry operator net_op) op_library(uniform_random_op - SRCS uniform_random_op.cc uniform_random_op.cu DEPS math_function) + SRCS uniform_random_op.cc uniform_random_op.cu) diff --git a/paddle/operators/gaussian_random_op.cc b/paddle/operators/gaussian_random_op.cc index 899f05fa47..dcd2237459 100644 --- a/paddle/operators/gaussian_random_op.cc +++ b/paddle/operators/gaussian_random_op.cc @@ -1,22 +1,44 @@ /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at - http://www.apache.org/licenses/LICENSE-2.0 - Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ -#include "paddle/operators/gaussian_random_op.h" +#include +#include "paddle/framework/op_registry.h" namespace paddle { namespace operators { +template +class CPUGaussianRandomKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& context) const override { + float mean = context.op_.GetAttr("mean"); + float std = context.op_.GetAttr("std"); + auto* tensor = context.Output("Out"); + T* data = tensor->mutable_data(context.GetPlace()); + + unsigned int seed = + static_cast(context.op_.GetAttr("seed")); + std::minstd_rand engine; + if (seed == 0) { + seed = std::random_device()(); + } + engine.seed(seed); + std::normal_distribution dist(mean, std); + ssize_t size = framework::product(tensor->dims()); + for (ssize_t i = 0; i < size; ++i) { + data[i] = dist(engine); + } + } +}; + class GaussianRandomOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; @@ -43,8 +65,12 @@ Use to initialize tensor with gaussian random generator. )DOC"); AddAttr>("dims", "The dimension of random tensor."); - AddAttr("mean", "mean value of random.").SetDefault(.0f); - AddAttr("std", "minimum value of random value.").SetDefault(1.0f); + AddAttr("mean", "mean of random tensor.").SetDefault(.0f); + AddAttr("std", "std of random tensor.").SetDefault(1.0f); + AddAttr("seed", + "Random seed of generator." + "0 means use system wide seed") + .SetDefault(0); } }; @@ -54,6 +80,4 @@ Use to initialize tensor with gaussian random generator. namespace ops = paddle::operators; REGISTER_OP_WITHOUT_GRADIENT(gaussian_random, ops::GaussianRandomOp, ops::GaussianRandomOpMaker); -REGISTER_OP_CPU_KERNEL( - gaussian_random, - ops::GaussianRandomKernel); +REGISTER_OP_CPU_KERNEL(gaussian_random, ops::CPUGaussianRandomKernel); \ No newline at end of file diff --git a/paddle/operators/gaussian_random_op.cu b/paddle/operators/gaussian_random_op.cu index 31be16fdc8..1d312e7b5d 100644 --- a/paddle/operators/gaussian_random_op.cu +++ b/paddle/operators/gaussian_random_op.cu @@ -1,20 +1,65 @@ /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at - http://www.apache.org/licenses/LICENSE-2.0 - Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ -#include "paddle/operators/gaussian_random_op.h" +#include +#include +#include +#include +#include "paddle/framework/op_registry.h" +#include "paddle/framework/operator.h" + +namespace paddle { +namespace operators { + +template +struct GaussianGenerator { + T mean_, std_; + unsigned int seed_; + + __host__ __device__ GaussianGenerator(T mean, T std, int seed) + : mean_(mean), std_(std), seed_(seed) {} + + __host__ __device__ T operator()(const unsigned int n) const { + thrust::minstd_rand rng; + rng.seed(seed_); + thrust::normal_distribution dist(min_, max_); + rng.discard(n); + return dist(rng); + } +}; + +template +class GPUGaussianRandomKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& context) const override { + auto* tensor = context.Output("Out"); + T* data = tensor->mutable_data(context.GetPlace()); + unsigned int seed = + static_cast(context.op_.GetAttr("seed")); + if (seed == 0) { + std::random_device rd; + seed = rd(); + } + T mean = static_cast(context.op_.GetAttr("mean")); + T std = static_cast(context.op_.GetAttr("std")); + thrust::counting_iterator index_sequence_begin(0); + ssize_t N = framework::product(tensor->dims()); + thrust::transform(index_sequence_begin, index_sequence_begin + N, + thrust::device_ptr(data), + GaussianGenerator(mean, std, seed)); + } +}; + +} // namespace operators +} // namespace paddle -namespace ops = paddle::operators; -REGISTER_OP_GPU_KERNEL( - gaussian_random, - ops::GaussianRandomKernel); +REGISTER_OP_GPU_KERNEL(gaussian_random, + paddle::operators::GPUGaussianRandomKernel); \ No newline at end of file diff --git a/paddle/operators/gaussian_random_op.h b/paddle/operators/gaussian_random_op.h deleted file mode 100644 index c90b665fe0..0000000000 --- a/paddle/operators/gaussian_random_op.h +++ /dev/null @@ -1,38 +0,0 @@ -/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - -Licensed under the Apache License, Version 2.0 (the "License"); -you may not use this file except in compliance with the License. -You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - -Unless required by applicable law or agreed to in writing, software -distributed under the License is distributed on an "AS IS" BASIS, -WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -See the License for the specific language governing permissions and -limitations under the License. */ - -#pragma once - -#include "paddle/framework/op_registry.h" -#include "paddle/operators/math/math_function.h" - -namespace paddle { -namespace operators { -template -class GaussianRandomKernel : public framework::OpKernel { - public: - void Compute(const framework::ExecutionContext& context) const override { - auto* tensor = context.Output("Out"); - T* data = tensor->mutable_data(context.GetPlace()); - T mean = static_cast(context.op_.GetAttr("mean")); - T std = static_cast(context.op_.GetAttr("std")); - auto n = framework::product(tensor->dims()); - - auto* device_context = - const_cast(context.device_context_); - math::RandGaussian(n, mean, std, data, device_context); - } -}; -} // namespace operators -} // namespace paddle diff --git a/paddle/operators/math/math_function.cc b/paddle/operators/math/math_function.cc index a098e02f95..d9824e5f96 100644 --- a/paddle/operators/math/math_function.cc +++ b/paddle/operators/math/math_function.cc @@ -118,28 +118,6 @@ void Set(const int n, const float alpha, out.device(*(cpu_context->eigen_device())) = out.constant(float(alpha)); } -template <> -void RandUniform(const int n, const float min, - const float max, float* output, - platform::DeviceContext* context) { - auto* cpu_context = reinterpret_cast(context); - std::uniform_real_distribution distribution(min, max); - for (int i = 0; i < n; i++) { - output[i] = distribution(cpu_context->rand_engine()); - } -} - -template <> -void RandGaussian(const int n, const float mean, - const float std, float* output, - platform::DeviceContext* context) { - auto* cpu_context = reinterpret_cast(context); - std::normal_distribution distribution(mean, std); - for (int i = 0; i < n; i++) { - output[i] = distribution(cpu_context->rand_engine()); - } -} - } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/math/math_function.cu b/paddle/operators/math/math_function.cu index 908efe9e0f..9dff6f05fb 100644 --- a/paddle/operators/math/math_function.cu +++ b/paddle/operators/math/math_function.cu @@ -135,54 +135,6 @@ void Set(const int n, const float alpha, out.device(*(cuda_context->eigen_device())) = out.constant(float(alpha)); } -template -__global__ void UniformShift(const int n, const T min, const T max, T* x) { - float scale = max - min; - for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < n; - i += blockDim.x * gridDim.x) { - x[i] = x[i] * scale + min; - } -} - -template <> -void RandUniform(const int n, const float min, - const float max, float* output, - platform::DeviceContext* context) { - auto* cuda_context = reinterpret_cast(context); - PADDLE_ENFORCE(platform::dynload::curandGenerateUniform( - cuda_context->curand_generator(), output, n)); - int block = 512; - int grid = (n + block - 1) / block; - UniformShift<<stream()>>>(n, min, max, - output); -} - -template -int HandleOddLengthRandGaussian(const int n, const T mean, const T std, - T* output, - platform::CUDADeviceContext* context) { - if (n % 2 == 1) { - std::default_random_engine generator; - std::normal_distribution distribution(mean, std); - const T random_value = distribution(generator); - Set(1, random_value, output + (n - 1), context); - return n - 1; - } - return n; -} - -template <> -void RandGaussian(const int n, const float mean, - const float std, float* output, - platform::DeviceContext* context) { - auto* cuda_context = reinterpret_cast(context); - - const int even_n = - HandleOddLengthRandGaussian(n, mean, std, output, cuda_context); - PADDLE_ENFORCE(platform::dynload::curandGenerateNormal( - cuda_context->curand_generator(), output, even_n, mean, std)); -} - } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/math/math_function.h b/paddle/operators/math/math_function.h index 6543a1b515..a0e9660564 100644 --- a/paddle/operators/math/math_function.h +++ b/paddle/operators/math/math_function.h @@ -82,14 +82,6 @@ template void Set(const int n, const T alpha, T* output, platform::DeviceContext* context); -template -void RandUniform(const int n, const T min, const T max, T* output, - platform::DeviceContext* context); - -template -void RandGaussian(const int n, const T mean, const T std, T* output, - platform::DeviceContext* context); - } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/uniform_random_op.cc b/paddle/operators/uniform_random_op.cc index 81487a6bd8..876b3ef557 100644 --- a/paddle/operators/uniform_random_op.cc +++ b/paddle/operators/uniform_random_op.cc @@ -1,22 +1,48 @@ /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at - http://www.apache.org/licenses/LICENSE-2.0 - Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ -#include "paddle/operators/uniform_random_op.h" +#include +#include +#include "paddle/framework/op_registry.h" +#include "paddle/framework/operator.h" namespace paddle { namespace operators { +// It seems that Eigen::Tensor::random in GPU will SEGFAULT. +// Use std::random and thrust::random(thrust is a std library in CUDA) to +// implement uniform random. +template +class CPUUniformRandomKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& context) const override { + auto* tensor = context.Output("Out"); + T* data = tensor->mutable_data(context.GetPlace()); + unsigned int seed = + static_cast(context.op_.GetAttr("seed")); + std::minstd_rand engine; + if (seed == 0) { + seed = std::random_device()(); + } + engine.seed(seed); + std::uniform_real_distribution dist( + static_cast(context.op_.GetAttr("min")), + static_cast(context.op_.GetAttr("max"))); + ssize_t size = framework::product(tensor->dims()); + for (ssize_t i = 0; i < size; ++i) { + data[i] = dist(engine); + } + } +}; + class UniformRandomOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; @@ -38,12 +64,15 @@ class UniformRandomOpMaker : public framework::OpProtoAndCheckerMaker { : framework::OpProtoAndCheckerMaker(proto, op_checker) { AddOutput("Out", "The output tensor of uniform random op"); AddComment(R"DOC(Uniform random operator. - Used to initialize tensor with uniform random generator. )DOC"); AddAttr>("dims", "the dimension of random tensor"); AddAttr("min", "Minimum value of uniform random").SetDefault(-1.0f); AddAttr("max", "Maximun value of uniform random").SetDefault(1.0f); + AddAttr("seed", + "Random seed of uniform random. " + "0 means generate a seed by system") + .SetDefault(0); } }; } // namespace operators @@ -51,6 +80,5 @@ Used to initialize tensor with uniform random generator. REGISTER_OP_WITHOUT_GRADIENT(uniform_random, paddle::operators::UniformRandomOp, paddle::operators::UniformRandomOpMaker); -REGISTER_OP_CPU_KERNEL( - uniform_random, - paddle::operators::UniformRandomKernel); +REGISTER_OP_CPU_KERNEL(uniform_random, + paddle::operators::CPUUniformRandomKernel); \ No newline at end of file diff --git a/paddle/operators/uniform_random_op.cu b/paddle/operators/uniform_random_op.cu index 1bfffc4778..6716b7c7f2 100644 --- a/paddle/operators/uniform_random_op.cu +++ b/paddle/operators/uniform_random_op.cu @@ -1,19 +1,68 @@ /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at - http://www.apache.org/licenses/LICENSE-2.0 - Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ -#include "paddle/operators/uniform_random_op.h" +#include +#include +#include +#include +#include "paddle/framework/op_registry.h" +#include "paddle/framework/operator.h" + +namespace paddle { +namespace operators { + +template +struct UniformGenerator { + T min_, max_; + unsigned int seed_; + + __host__ __device__ UniformGenerator(T min, T max, int seed) + : min_(min), max_(max), seed_(seed) {} + + __host__ __device__ T operator()(const unsigned int n) const { + thrust::minstd_rand rng; + rng.seed(seed_); + thrust::uniform_real_distribution dist(min_, max_); + rng.discard(n); + return dist(rng); + } +}; + +// It seems that Eigen::Tensor::random in GPU will SEGFAULT. +// Use std::random and thrust::random(thrust is a std library in CUDA) to +// implement uniform random. +template +class GPUUniformRandomKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& context) const override { + auto* tensor = context.Output("Out"); + T* data = tensor->mutable_data(context.GetPlace()); + unsigned int seed = + static_cast(context.op_.GetAttr("seed")); + if (seed == 0) { + std::random_device rd; + seed = rd(); + } + T min = static_cast(context.op_.GetAttr("min")); + T max = static_cast(context.op_.GetAttr("max")); + thrust::counting_iterator index_sequence_begin(0); + ssize_t N = framework::product(tensor->dims()); + thrust::transform(index_sequence_begin, index_sequence_begin + N, + thrust::device_ptr(data), + UniformGenerator(min, max, seed)); + } +}; + +} // namespace operators +} // namespace paddle -REGISTER_OP_GPU_KERNEL( - uniform_random, - paddle::operators::UniformRandomKernel); +REGISTER_OP_GPU_KERNEL(uniform_random, + paddle::operators::GPUUniformRandomKernel); \ No newline at end of file diff --git a/paddle/operators/uniform_random_op.h b/paddle/operators/uniform_random_op.h deleted file mode 100644 index dffa640f84..0000000000 --- a/paddle/operators/uniform_random_op.h +++ /dev/null @@ -1,38 +0,0 @@ -/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - -Licensed under the Apache License, Version 2.0 (the "License"); -you may not use this file except in compliance with the License. -You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - -Unless required by applicable law or agreed to in writing, software -distributed under the License is distributed on an "AS IS" BASIS, -WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -See the License for the specific language governing permissions and -limitations under the License. */ - -#pragma once - -#include "paddle/framework/op_registry.h" -#include "paddle/operators/math/math_function.h" - -namespace paddle { -namespace operators { -template -class UniformRandomKernel : public framework::OpKernel { - public: - void Compute(const framework::ExecutionContext& context) const override { - auto* tensor = context.Output("Out"); - T* data = tensor->mutable_data(context.GetPlace()); - T min = static_cast(context.op_.GetAttr("min")); - T max = static_cast(context.op_.GetAttr("max")); - auto n = framework::product(tensor->dims()); - - auto* device_context = - const_cast(context.device_context_); - math::RandUniform(n, min, max, data, device_context); - } -}; -} // namespace operators -} // namespace paddle diff --git a/paddle/platform/device_context.cc b/paddle/platform/device_context.cc index ad9b4e42f3..ad212c5b2c 100644 --- a/paddle/platform/device_context.cc +++ b/paddle/platform/device_context.cc @@ -25,17 +25,8 @@ CPUDeviceContext::CPUDeviceContext() { eigen_device_.reset(new Eigen::DefaultDevice()); } -CPUDeviceContext::CPUDeviceContext(CPUPlace place, int seed) { +CPUDeviceContext::CPUDeviceContext(CPUPlace place) { eigen_device_.reset(new Eigen::DefaultDevice()); - rand_seed_ = seed; -} - -std::minstd_rand& CPUDeviceContext::rand_engine() { - if (!rand_engine_) { - rand_engine_.reset(new std::minstd_rand()); - rand_engine_->seed(rand_seed_); - } - return *(rand_engine_.get()); } Eigen::DefaultDevice* CPUDeviceContext::eigen_device() const { @@ -104,8 +95,7 @@ Eigen::GpuDevice* DeviceContext::get_eigen_device() const { return reinterpret_cast(this)->eigen_device(); } -CUDADeviceContext::CUDADeviceContext(GPUPlace place, uint64_t seed) - : place_(place), rand_seed_(seed) { +CUDADeviceContext::CUDADeviceContext(GPUPlace place) : place_(place) { SetDeviceId(place_.device); PADDLE_ENFORCE(cudaStreamCreate(&stream_)); eigen_stream_.reset(new EigenCudaStreamDevice()); @@ -157,19 +147,6 @@ cudnnHandle_t CUDADeviceContext::cudnn_handle() { return cudnn_handle_; } -curandGenerator_t CUDADeviceContext::curand_generator() { - if (!curand_generator_) { - SetDeviceId(place_.device); - PADDLE_ENFORCE(dynload::curandCreateGenerator(&curand_generator_, - CURAND_RNG_PSEUDO_DEFAULT)); - PADDLE_ENFORCE(dynload::curandSetPseudoRandomGeneratorSeed( - curand_generator_, rand_seed_)); - - PADDLE_ENFORCE(dynload::curandSetStream(curand_generator_, stream_)); - } - return curand_generator_; -} - cudaStream_t CUDADeviceContext::stream() { return stream_; } #endif // PADDLE_ONLY_CPU diff --git a/paddle/platform/device_context.h b/paddle/platform/device_context.h index e18f48fef5..11528e1194 100644 --- a/paddle/platform/device_context.h +++ b/paddle/platform/device_context.h @@ -17,7 +17,6 @@ limitations under the License. */ #ifndef PADDLE_ONLY_CPU #include "paddle/platform/dynload/cublas.h" #include "paddle/platform/dynload/cudnn.h" -#include "paddle/platform/dynload/curand.h" #include "paddle/platform/gpu_info.h" #define EIGEN_USE_GPU #endif @@ -40,18 +39,14 @@ class DeviceContext { class CPUDeviceContext : public DeviceContext { public: CPUDeviceContext(); - explicit CPUDeviceContext(CPUPlace place, int seed = 0); + explicit CPUDeviceContext(CPUPlace place); virtual ~CPUDeviceContext() {} Eigen::DefaultDevice* eigen_device() const; - std::minstd_rand& rand_engine(); - Place GetPlace() const override; private: - int rand_seed_; - std::unique_ptr rand_engine_; std::unique_ptr eigen_device_; }; @@ -60,7 +55,7 @@ class EigenCudaStreamDevice; class CUDADeviceContext : public DeviceContext { public: - explicit CUDADeviceContext(GPUPlace place, uint64_t seed = 0); + explicit CUDADeviceContext(GPUPlace place); virtual ~CUDADeviceContext(); /*! \brief Wait for all operations completion in the stream. */ @@ -79,9 +74,6 @@ class CUDADeviceContext : public DeviceContext { /*! \brief Return cudnn handle in the device context. */ cudnnHandle_t cudnn_handle(); - /*! \brief Return curand handle in the device context. */ - curandGenerator_t curand_generator(); - /*! \brief Return cuda stream in the device context. */ cudaStream_t stream(); // clang-format on @@ -92,13 +84,10 @@ class CUDADeviceContext : public DeviceContext { std::unique_ptr eigen_device_; std::unique_ptr eigen_stream_; - uint64_t rand_seed_; - // clang-format off cudaStream_t stream_{nullptr}; cudnnHandle_t cudnn_handle_{nullptr}; cublasHandle_t cublas_handle_{nullptr}; - curandGenerator_t curand_generator_{nullptr}; // clang-format on }; diff --git a/python/paddle/v2/framework/tests/test_gaussian_random_op.py b/python/paddle/v2/framework/tests/test_gaussian_random_op.py index 367d21b301..f95ed70b58 100644 --- a/python/paddle/v2/framework/tests/test_gaussian_random_op.py +++ b/python/paddle/v2/framework/tests/test_gaussian_random_op.py @@ -17,7 +17,12 @@ class GaussianRandomTest(unittest.TestCase): scope.new_var("Out").get_tensor() op = Operator( - "gaussian_random", Out="Out", dims=[1000, 784], mean=.0, std=1.) + "gaussian_random", + Out="Out", + dims=[1000, 784], + mean=.0, + std=1., + seed=10) op.infer_shape(scope) context = core.DeviceContext.create(place) diff --git a/python/paddle/v2/framework/tests/test_uniform_random_op.py b/python/paddle/v2/framework/tests/test_uniform_random_op.py index 95c36a27cf..c3d2bb44da 100644 --- a/python/paddle/v2/framework/tests/test_uniform_random_op.py +++ b/python/paddle/v2/framework/tests/test_uniform_random_op.py @@ -17,7 +17,12 @@ class UniformRandomTest(unittest.TestCase): scope.new_var("X").get_tensor() op = Operator( - "uniform_random", Out="X", dims=[1000, 784], min=-5.0, max=10.0) + "uniform_random", + Out="X", + dims=[1000, 784], + min=-5.0, + max=10.0, + seed=10) op.infer_shape(scope) ctx = core.DeviceContext.create(place) From 1918ad875980a7b5fb54c207e56d86b4376e2505 Mon Sep 17 00:00:00 2001 From: qijun Date: Tue, 22 Aug 2017 12:16:30 +0800 Subject: [PATCH 075/138] fix gpu build error --- paddle/operators/math/CMakeLists.txt | 4 ++-- paddle/operators/math/math_function.cc | 9 --------- paddle/operators/math/math_function.cu | 13 ------------- paddle/operators/math/math_function.h | 5 ----- paddle/platform/device_context_test.cc | 2 -- 5 files changed, 2 insertions(+), 31 deletions(-) diff --git a/paddle/operators/math/CMakeLists.txt b/paddle/operators/math/CMakeLists.txt index 228f463f2b..ed51d416ed 100644 --- a/paddle/operators/math/CMakeLists.txt +++ b/paddle/operators/math/CMakeLists.txt @@ -1,8 +1,8 @@ if(WITH_GPU) - nv_library(math_function SRCS math_function.cc math_function.cu DEPS cblas device_context eigen3) + nv_library(math_function SRCS math_function.cc math_function.cu DEPS cblas device_context) else() - cc_library(math_function SRCS math_function.cc DEPS cblas device_context eigen3) + cc_library(math_function SRCS math_function.cc DEPS cblas device_context) endif() nv_test(math_function_test SRCS math_function_test.cc DEPS math_function tensor) diff --git a/paddle/operators/math/math_function.cc b/paddle/operators/math/math_function.cc index d9824e5f96..1e86fc3d16 100644 --- a/paddle/operators/math/math_function.cc +++ b/paddle/operators/math/math_function.cc @@ -109,15 +109,6 @@ void matmul(const framework::Tensor& matrix_a, matrix_b.data(), beta, matrix_out->data(), context); } -template <> -void Set(const int n, const float alpha, - float* output, - platform::DeviceContext* context) { - auto* cpu_context = reinterpret_cast(context); - framework::EigenVector::Type out(output, n); - out.device(*(cpu_context->eigen_device())) = out.constant(float(alpha)); -} - } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/math/math_function.cu b/paddle/operators/math/math_function.cu index 9dff6f05fb..da40b27c94 100644 --- a/paddle/operators/math/math_function.cu +++ b/paddle/operators/math/math_function.cu @@ -12,10 +12,6 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ -#include -#include -#include -#include #include "paddle/operators/math/math_function.h" namespace paddle { @@ -126,15 +122,6 @@ void matmul(const framework::Tensor& matrix_a, matrix_b.data(), beta, matrix_out->data(), context); } -template <> -void Set(const int n, const float alpha, - float* output, - platform::DeviceContext* context) { - auto* cuda_context = reinterpret_cast(context); - framework::EigenVector::Type out(output, n); - out.device(*(cuda_context->eigen_device())) = out.constant(float(alpha)); -} - } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/operators/math/math_function.h b/paddle/operators/math/math_function.h index a0e9660564..155589fadb 100644 --- a/paddle/operators/math/math_function.h +++ b/paddle/operators/math/math_function.h @@ -52,7 +52,6 @@ int LAPACKE_dgetri(int matrix_layout, int n, double* a, int lda, #include -#include "paddle/framework/eigen.h" #include "paddle/framework/tensor.h" #include "paddle/platform/device_context.h" #include "paddle/platform/enforce.h" @@ -78,10 +77,6 @@ void matmul(const framework::Tensor& matrix_a, bool trans_a, framework::Tensor* matrix_out, T beta, platform::DeviceContext* context); -template -void Set(const int n, const T alpha, T* output, - platform::DeviceContext* context); - } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/platform/device_context_test.cc b/paddle/platform/device_context_test.cc index 8b764bdcd9..5883a55272 100644 --- a/paddle/platform/device_context_test.cc +++ b/paddle/platform/device_context_test.cc @@ -43,8 +43,6 @@ TEST(Device, CUDADeviceContext) { ASSERT_NE(nullptr, cudnn_handle); cublasHandle_t cublas_handle = device_context->cublas_handle(); ASSERT_NE(nullptr, cublas_handle); - curandGenerator_t curand_handle = device_context->curand_generator(); - ASSERT_NE(nullptr, curand_handle); ASSERT_NE(nullptr, device_context->stream()); delete device_context; } From aff90d8ee78be398b2984d63f2eb985f15f430d1 Mon Sep 17 00:00:00 2001 From: qijun Date: Tue, 22 Aug 2017 04:34:35 +0000 Subject: [PATCH 076/138] fix gpu build error --- paddle/operators/gaussian_random_op.cu | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/paddle/operators/gaussian_random_op.cu b/paddle/operators/gaussian_random_op.cu index 1d312e7b5d..018a4bfcb2 100644 --- a/paddle/operators/gaussian_random_op.cu +++ b/paddle/operators/gaussian_random_op.cu @@ -30,7 +30,7 @@ struct GaussianGenerator { __host__ __device__ T operator()(const unsigned int n) const { thrust::minstd_rand rng; rng.seed(seed_); - thrust::normal_distribution dist(min_, max_); + thrust::normal_distribution dist(mean_, std_); rng.discard(n); return dist(rng); } @@ -62,4 +62,4 @@ class GPUGaussianRandomKernel : public framework::OpKernel { } // namespace paddle REGISTER_OP_GPU_KERNEL(gaussian_random, - paddle::operators::GPUGaussianRandomKernel); \ No newline at end of file + paddle::operators::GPUGaussianRandomKernel); From dc5f0dbc324e0e15bef1753aeaed6700f5972cf0 Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Tue, 22 Aug 2017 05:27:02 +0000 Subject: [PATCH 077/138] remove opregistry in gather function --- paddle/operators/gather.h | 1 - 1 file changed, 1 deletion(-) diff --git a/paddle/operators/gather.h b/paddle/operators/gather.h index edac29f6db..92fb51ec17 100644 --- a/paddle/operators/gather.h +++ b/paddle/operators/gather.h @@ -18,7 +18,6 @@ limitations under the License. */ #include "paddle/framework/ddim.h" #include "paddle/framework/eigen.h" -#include "paddle/framework/op_registry.h" #include "paddle/framework/tensor.h" #include "paddle/platform/place.h" From 6eab5638f03f49ab1ff3d3a4fc30d870f42a6153 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E6=AD=A6=E6=AF=85?= Date: Tue, 22 Aug 2017 13:28:51 +0800 Subject: [PATCH 078/138] Fix remote large update core (#3518) * fix remote large update core * wip * working version * fix style check * fix style check * update style check --- .../gserver/gradientmachines/NeuralNetwork.cpp | 2 +- paddle/parameter/Parameter.h | 5 ++++- paddle/pserver/ParameterClient2.cpp | 16 ++++++++++++++-- paddle/pserver/ParameterClient2.h | 1 + 4 files changed, 20 insertions(+), 4 deletions(-) diff --git a/paddle/gserver/gradientmachines/NeuralNetwork.cpp b/paddle/gserver/gradientmachines/NeuralNetwork.cpp index cfa80a8936..26cff3e677 100644 --- a/paddle/gserver/gradientmachines/NeuralNetwork.cpp +++ b/paddle/gserver/gradientmachines/NeuralNetwork.cpp @@ -202,7 +202,7 @@ void NeuralNetwork::prefetch(const std::vector& inArgs) { auto mat = dynamic_cast( para->getMat(PARAMETER_VALUE).get()); para->clearGradient(); - mat->clearIndices(); + if (mat) mat->clearIndices(); } } } diff --git a/paddle/parameter/Parameter.h b/paddle/parameter/Parameter.h index e31cbc3dee..321f4275d8 100644 --- a/paddle/parameter/Parameter.h +++ b/paddle/parameter/Parameter.h @@ -65,7 +65,10 @@ public: size_t getSize() const { return config_.size(); } bool isFullSize() const { - return this->getSize() == bufs_[PARAMETER_VALUE]->getSize(); + if (bufs_[PARAMETER_VALUE]) { + return this->getSize() == bufs_[PARAMETER_VALUE]->getSize(); + } + return false; } inline bool useGpu() const { return useGpu_; } diff --git a/paddle/pserver/ParameterClient2.cpp b/paddle/pserver/ParameterClient2.cpp index f7e391f763..54063a809a 100644 --- a/paddle/pserver/ParameterClient2.cpp +++ b/paddle/pserver/ParameterClient2.cpp @@ -65,7 +65,6 @@ void ParameterClient2::initThreads() { LOG(INFO) << "parallel_thread_num dosent need to set"; } syncThreadPool_.reset(new SyncThreadPool(threadNum_)); - startThreads(); } @@ -224,6 +223,14 @@ void ParameterClient2::prepareSendData( request.set_cost(cost); request.set_batch_status(batchStatus); CHECK_EQ(request.blocks_size(), 0); + VLOG(10) << "request: trainer_id: " << request.trainer_id() + << " update_mode" << request.update_mode() + << " send_back_parameter: " << request.send_back_parameter() + << " send_back_parameter_type: " + << request.send_back_parameter_type() + << " num_samples: " << request.num_samples() + << " cost: " << request.cost() + << " batch_status: " << request.batch_status(); } for (const auto& segments : parameterSegments) { const auto it = parameterMap_.find(segments.id); @@ -251,11 +258,17 @@ void ParameterClient2::prepareSendData( CHECK(sendMat != nullptr) << "sendMat is nullptr"; syncThreadPool_->exec([&](int tid, size_t numThreads) { + std::lock_guard guard(sparseAutoGrowthMutex_); const auto& localIndices = prefetchMat->getLocalIndices(); /// num of sparse rows size_t nLocalBlocks = localIndices.size(); uint64_t beginDim = 0; uint64_t endDim = 0; + + // FIXME(typhoonzero): let it resize first + prefetchMat->getLocalRow(nLocalBlocks + 1); + sendMat->getLocalRow(nLocalBlocks + 1); + for (size_t row = 0; row < nLocalBlocks; ++row) { int64_t blockId = localIndices[row]; // local row -> sparse row int serverId = std::abs((blockId + nameHash) % serviceNum_); @@ -275,7 +288,6 @@ void ParameterClient2::prepareSendData( block->set_begin_pos(row * blockSize); /// block len block->set_block_size(endDim - beginDim); - if (sendingPara) { sendJob->parallelInputIovs[serverId].push_back( {sendMat->getLocalRow(row), sizeof(real) * (size_t)blockSize}); diff --git a/paddle/pserver/ParameterClient2.h b/paddle/pserver/ParameterClient2.h index 89b3ddd502..29b9eeacdd 100644 --- a/paddle/pserver/ParameterClient2.h +++ b/paddle/pserver/ParameterClient2.h @@ -583,6 +583,7 @@ protected: #ifndef PADDLE_DISABLE_TIMER uint64_t forwardbackwordTime_; #endif + std::mutex sparseAutoGrowthMutex_; /// map id to parameter used for decoding protobuf data std::unordered_map parameterMap_; From 950cc60d2b2e6ab9c05f82df3f2d3f3179541209 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 22 Aug 2017 15:29:38 +0800 Subject: [PATCH 079/138] Add minus --- paddle/framework/CMakeLists.txt | 3 +- paddle/framework/pybind.cc | 1 + paddle/operators/CMakeLists.txt | 1 + paddle/operators/minus_op.cc | 84 +++++++++++++++++++++++++++++++++ paddle/operators/minus_op.cu | 18 +++++++ paddle/operators/minus_op.h | 39 +++++++++++++++ 6 files changed, 145 insertions(+), 1 deletion(-) create mode 100644 paddle/operators/minus_op.cc create mode 100644 paddle/operators/minus_op.cu create mode 100644 paddle/operators/minus_op.h diff --git a/paddle/framework/CMakeLists.txt b/paddle/framework/CMakeLists.txt index 5df14ae78d..c9cf45e9d7 100644 --- a/paddle/framework/CMakeLists.txt +++ b/paddle/framework/CMakeLists.txt @@ -56,5 +56,6 @@ cc_library(paddle_pybind SHARED uniform_random_op gaussian_random_op fill_zeros_like_op - scale_op) + scale_op + minus_op) endif(WITH_PYTHON) diff --git a/paddle/framework/pybind.cc b/paddle/framework/pybind.cc index 3aaf0de150..b4b7921d33 100644 --- a/paddle/framework/pybind.cc +++ b/paddle/framework/pybind.cc @@ -44,6 +44,7 @@ USE_OP(gaussian_random); USE_OP(uniform_random); USE_OP(scale); USE_OP_ITSELF(identity); +USE_OP(minus); namespace paddle { namespace framework { diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index 0ba598823b..61f7a4070f 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -69,3 +69,4 @@ op_library(recurrent_op SRCS recurrent_op.cc rnn/recurrent_op_utils.cc op_library(uniform_random_op SRCS uniform_random_op.cc uniform_random_op.cu) op_library(scale_op SRCS scale_op.cc scale_op.cu DEPS net_op) +op_library(minus_op SRCS minus_op.cc minus_op.cu DEPS scale_op) diff --git a/paddle/operators/minus_op.cc b/paddle/operators/minus_op.cc new file mode 100644 index 0000000000..c660ab5d32 --- /dev/null +++ b/paddle/operators/minus_op.cc @@ -0,0 +1,84 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#include "paddle/operators/minus_op.h" +#include "paddle/operators/net_op.h" + +namespace paddle { +namespace operators { + +class MinusOp : public framework::OperatorWithKernel { + public: + MinusOp(const std::string &type, const VarNameMap &inputs, + const VarNameMap &outputs, const framework::AttributeMap &attrs) + : OperatorWithKernel(type, inputs, outputs, attrs) {} + + protected: + void InferShape(const framework::InferShapeContext &ctx) const override { + auto *left_tensor = ctx.Input("X"); + auto *right_tensor = ctx.Input("Y"); + + PADDLE_ENFORCE_EQ( + framework::product(left_tensor->dims()), + framework::product(right_tensor->dims()), + "Minus operator must take two tensor with same num of elements"); + ctx.Output("Out")->Resize(left_tensor->dims()); + } +}; + +class MinusOpMaker : public framework::OpProtoAndCheckerMaker { + public: + MinusOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker) + : OpProtoAndCheckerMaker(proto, op_checker) { + AddInput("X", "The left tensor of minus operator.").NotInGradient(); + AddInput("Y", "The right tensor of minus operator.").NotInGradient(); + AddOutput("Out", "The output tensor of minus operator.").NotInGradient(); + + AddComment(R"DOC(Minus Operator + +Equation: Out = X - Y +)DOC"); + } +}; +template +class MinusGradOp : public NetOp { + public: + MinusGradOp(const std::string &type, const VarNameMap &inputs, + const VarNameMap &outputs, const framework::AttributeMap &attrs) + : NetOp(type, inputs, outputs, attrs) { + auto out_grad = Input(framework::GradVarName("Out")); + auto x_grad = Output(framework::GradVarName("X")); + auto y_grad = Output(framework::GradVarName("Y")); + + // x_grad = out_grad + AddOp(framework::OpRegistry::CreateOp("identity", {{"X", {out_grad}}}, + {{"Out", {x_grad}}}, {})); + + framework::AttributeMap scale_attr; + scale_attr["scale"] = static_cast(-1); + AddOp(framework::OpRegistry::CreateOp("scale", {{"X", {out_grad}}}, + {{"Out", {y_grad}}}, scale_attr)); + } +}; + +} // namespace operators +} // namespace paddle + +USE_OP(scale); +USE_OP_ITSELF(identity); +namespace ops = paddle::operators; +REGISTER_OP(minus, ops::MinusOp, ops::MinusOpMaker, minus_grad, + ops::MinusGradOp); +REGISTER_OP_CPU_KERNEL(minus, + ops::MinusKernel); diff --git a/paddle/operators/minus_op.cu b/paddle/operators/minus_op.cu new file mode 100644 index 0000000000..a8375cc630 --- /dev/null +++ b/paddle/operators/minus_op.cu @@ -0,0 +1,18 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#include "paddle/operators/minus_op.h" + +REGISTER_OP_GPU_KERNEL( + minus, paddle::operators::MinusKernel); diff --git a/paddle/operators/minus_op.h b/paddle/operators/minus_op.h new file mode 100644 index 0000000000..6310a4fd51 --- /dev/null +++ b/paddle/operators/minus_op.h @@ -0,0 +1,39 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#pragma once +#include "paddle/framework/eigen.h" +#include "paddle/framework/op_registry.h" + +namespace paddle { +namespace operators { + +template +class MinusKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& context) const override { + auto* left_tensor = context.Input("X"); + auto* right_tensor = context.Input("Y"); + auto* out_tensor = context.Output("Out"); + + out_tensor->mutable_data(context.GetPlace()); + auto& dev = context.GetEigenDevice(); + framework::EigenVector::Flatten(*out_tensor).device(dev) = + framework::EigenVector::Flatten(*left_tensor) - + framework::EigenVector::Flatten(*right_tensor); + } +}; + +} // namespace operators +} // namespace paddle From 5a8fbb7d19e95f3be16bbee029e82e14f0a240df Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Tue, 22 Aug 2017 00:56:34 -0700 Subject: [PATCH 080/138] add data --- python/paddle/v2/framework/tests/mnist.py | 26 +++++++++++++++++------ 1 file changed, 19 insertions(+), 7 deletions(-) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index d0c56c457d..f75f196168 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -1,8 +1,9 @@ import paddle.v2.framework.core as core from paddle.v2.framework.op import Operator import numpy +import paddle.v2 as paddle -BATCH_SIZE = 2 +BATCH_SIZE = 100 scope = core.Scope() place = core.CPUPlace() @@ -39,9 +40,9 @@ def feed_data(name, data): tensor = scope.find_var(name).get_tensor() tensor.set_dims(data.shape) if data.dtype == numpy.dtype('int32'): - tensor.alloc_float(place) - elif data.dtype == numpy.dtype('float32'): tensor.alloc_int(place) + elif data.dtype == numpy.dtype('float32'): + tensor.alloc_float(place) else: raise ValueError("data type not supported") tensor.set(data, place) @@ -168,20 +169,31 @@ print(backward_net) optimize_net.complete_add_op(True) print(optimize_net) -PASS_NUM = 10 +reader = paddle.batch( + paddle.reader.shuffle( + paddle.dataset.mnist.train(), buf_size=8192), + batch_size=BATCH_SIZE) + +PASS_NUM = 1000 for pass_id in range(PASS_NUM): print("===========forward==========") - feed_data("pixel", numpy.random.random((BATCH_SIZE, 784)).astype('float32')) - feed_data("label", numpy.ones(BATCH_SIZE).astype("int32")) + # feed_data("pixel", numpy.random.random((BATCH_SIZE, 784)).astype('float32')) + # feed_data("label", numpy.ones(BATCH_SIZE).astype("int32")) + data = reader().next() + image = numpy.array(map(lambda x: x[0], data)).astype("float32") + label = numpy.array(map(lambda x: x[1], data)).astype("int32") + feed_data("pixel", image) + feed_data("label", label) forward_network.infer_shape(scope) print_inputs_outputs(forward_network) - print(numpy.array(scope.find_var("label").get_tensor())) + # print(numpy.array(scope.find_var("label").get_tensor())) forward_network.run(scope, dev_ctx) # print(numpy.array(scope.find_var("fc_0").get_tensor())) print("===========backward==========") cost_data = numpy.array(scope.find_var("cross_entropy_1").get_tensor()) + print(cost_data.sum() / len(cost_data)) cost_grad = scope.find_var(grad_var_name("cross_entropy_1")).get_tensor() cost_grad.set_dims(cost_data.shape) cost_grad.alloc_float(place) From 9b4a9da9f293d7decca3dbedf47ead19914e48ff Mon Sep 17 00:00:00 2001 From: qijun Date: Tue, 22 Aug 2017 08:07:35 +0000 Subject: [PATCH 081/138] fix code style --- paddle/operators/gaussian_random_op.cc | 3 ++- paddle/operators/gaussian_random_op.cu | 1 + paddle/operators/uniform_random_op.cc | 3 ++- paddle/operators/uniform_random_op.cu | 3 ++- 4 files changed, 7 insertions(+), 3 deletions(-) diff --git a/paddle/operators/gaussian_random_op.cc b/paddle/operators/gaussian_random_op.cc index dcd2237459..5755de70cd 100644 --- a/paddle/operators/gaussian_random_op.cc +++ b/paddle/operators/gaussian_random_op.cc @@ -80,4 +80,5 @@ Use to initialize tensor with gaussian random generator. namespace ops = paddle::operators; REGISTER_OP_WITHOUT_GRADIENT(gaussian_random, ops::GaussianRandomOp, ops::GaussianRandomOpMaker); -REGISTER_OP_CPU_KERNEL(gaussian_random, ops::CPUGaussianRandomKernel); \ No newline at end of file +REGISTER_OP_CPU_KERNEL(gaussian_random, ops::CPUGaussianRandomKernel); + diff --git a/paddle/operators/gaussian_random_op.cu b/paddle/operators/gaussian_random_op.cu index 018a4bfcb2..3fe76ee7e8 100644 --- a/paddle/operators/gaussian_random_op.cu +++ b/paddle/operators/gaussian_random_op.cu @@ -63,3 +63,4 @@ class GPUGaussianRandomKernel : public framework::OpKernel { REGISTER_OP_GPU_KERNEL(gaussian_random, paddle::operators::GPUGaussianRandomKernel); + diff --git a/paddle/operators/uniform_random_op.cc b/paddle/operators/uniform_random_op.cc index 876b3ef557..c2e2d7ba4c 100644 --- a/paddle/operators/uniform_random_op.cc +++ b/paddle/operators/uniform_random_op.cc @@ -81,4 +81,5 @@ Used to initialize tensor with uniform random generator. REGISTER_OP_WITHOUT_GRADIENT(uniform_random, paddle::operators::UniformRandomOp, paddle::operators::UniformRandomOpMaker); REGISTER_OP_CPU_KERNEL(uniform_random, - paddle::operators::CPUUniformRandomKernel); \ No newline at end of file + paddle::operators::CPUUniformRandomKernel); + diff --git a/paddle/operators/uniform_random_op.cu b/paddle/operators/uniform_random_op.cu index 6716b7c7f2..f05ffe3068 100644 --- a/paddle/operators/uniform_random_op.cu +++ b/paddle/operators/uniform_random_op.cu @@ -65,4 +65,5 @@ class GPUUniformRandomKernel : public framework::OpKernel { } // namespace paddle REGISTER_OP_GPU_KERNEL(uniform_random, - paddle::operators::GPUUniformRandomKernel); \ No newline at end of file + paddle::operators::GPUUniformRandomKernel); + From 5d0d44a0189142363ee680631ade44b6de163ec6 Mon Sep 17 00:00:00 2001 From: qijun Date: Tue, 22 Aug 2017 08:25:41 +0000 Subject: [PATCH 082/138] use clang-format --- paddle/operators/gaussian_random_op.cc | 1 - paddle/operators/gaussian_random_op.cu | 1 - paddle/operators/uniform_random_op.cc | 1 - paddle/operators/uniform_random_op.cu | 1 - 4 files changed, 4 deletions(-) diff --git a/paddle/operators/gaussian_random_op.cc b/paddle/operators/gaussian_random_op.cc index 5755de70cd..a85363ad81 100644 --- a/paddle/operators/gaussian_random_op.cc +++ b/paddle/operators/gaussian_random_op.cc @@ -81,4 +81,3 @@ namespace ops = paddle::operators; REGISTER_OP_WITHOUT_GRADIENT(gaussian_random, ops::GaussianRandomOp, ops::GaussianRandomOpMaker); REGISTER_OP_CPU_KERNEL(gaussian_random, ops::CPUGaussianRandomKernel); - diff --git a/paddle/operators/gaussian_random_op.cu b/paddle/operators/gaussian_random_op.cu index 3fe76ee7e8..018a4bfcb2 100644 --- a/paddle/operators/gaussian_random_op.cu +++ b/paddle/operators/gaussian_random_op.cu @@ -63,4 +63,3 @@ class GPUGaussianRandomKernel : public framework::OpKernel { REGISTER_OP_GPU_KERNEL(gaussian_random, paddle::operators::GPUGaussianRandomKernel); - diff --git a/paddle/operators/uniform_random_op.cc b/paddle/operators/uniform_random_op.cc index c2e2d7ba4c..29491137e6 100644 --- a/paddle/operators/uniform_random_op.cc +++ b/paddle/operators/uniform_random_op.cc @@ -82,4 +82,3 @@ REGISTER_OP_WITHOUT_GRADIENT(uniform_random, paddle::operators::UniformRandomOp, paddle::operators::UniformRandomOpMaker); REGISTER_OP_CPU_KERNEL(uniform_random, paddle::operators::CPUUniformRandomKernel); - diff --git a/paddle/operators/uniform_random_op.cu b/paddle/operators/uniform_random_op.cu index f05ffe3068..1d6709934c 100644 --- a/paddle/operators/uniform_random_op.cu +++ b/paddle/operators/uniform_random_op.cu @@ -66,4 +66,3 @@ class GPUUniformRandomKernel : public framework::OpKernel { REGISTER_OP_GPU_KERNEL(uniform_random, paddle::operators::GPUUniformRandomKernel); - From 0f3b9e4112cbedd1b026f6cd09955d15f6207864 Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Tue, 22 Aug 2017 15:36:43 +0800 Subject: [PATCH 083/138] lookup table op, cuda helper and set functor 1. finish lookup table CPU and GPU kernel 2. Add some cuda helper 3. Add some math funtor --- paddle/framework/pybind.cc | 1 + paddle/operators/CMakeLists.txt | 6 +- paddle/operators/functor/CMakeLists.txt | 5 + paddle/operators/functor/math_functor.cc | 42 +++++++ paddle/operators/functor/math_functor.cu | 42 +++++++ paddle/operators/functor/math_functor.h | 32 +++++ paddle/operators/lookup_table_op.cc | 71 +++++++++++ paddle/operators/lookup_table_op.cu | 116 ++++++++++++++++++ paddle/operators/lookup_table_op.h | 75 +++++++++++ paddle/platform/cuda_helper.h | 57 +++++++++ .../paddle/v2/framework/tests/CMakeLists.txt | 1 + .../v2/framework/tests/test_lookup_table.py | 31 +++++ 12 files changed, 477 insertions(+), 2 deletions(-) create mode 100644 paddle/operators/functor/CMakeLists.txt create mode 100644 paddle/operators/functor/math_functor.cc create mode 100644 paddle/operators/functor/math_functor.cu create mode 100644 paddle/operators/functor/math_functor.h create mode 100644 paddle/operators/lookup_table_op.cc create mode 100644 paddle/operators/lookup_table_op.cu create mode 100644 paddle/operators/lookup_table_op.h create mode 100644 paddle/platform/cuda_helper.h create mode 100644 python/paddle/v2/framework/tests/test_lookup_table.py diff --git a/paddle/framework/pybind.cc b/paddle/framework/pybind.cc index f0114b9e49..68c5526bbb 100644 --- a/paddle/framework/pybind.cc +++ b/paddle/framework/pybind.cc @@ -42,6 +42,7 @@ USE_OP(fill_zeros_like); USE_OP_ITSELF(recurrent_op); USE_OP(gaussian_random); USE_OP(uniform_random); +USE_OP(lookup_table); namespace paddle { namespace framework { diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index a7c89787e4..1ca5010eae 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -42,6 +42,8 @@ function(op_library TARGET) endfunction() add_subdirectory(math) +add_subdirectory(functor) + cc_test(gather_test SRCS gather_test.cc DEPS tensor) cc_test(scatter_test SRCS scatter_test.cc DEPS tensor) @@ -66,5 +68,5 @@ op_library(sgd_op SRCS sgd_op.cc sgd_op.cu) op_library(recurrent_op SRCS recurrent_op.cc rnn/recurrent_op_utils.cc DEPS framework_proto tensor op_registry operator net_op) -op_library(uniform_random_op - SRCS uniform_random_op.cc uniform_random_op.cu) +op_library(uniform_random_op SRCS uniform_random_op.cc uniform_random_op.cu) +op_library(lookup_table_op SRCS lookup_table_op.cc lookup_table_op.cu DEPS math_functor) diff --git a/paddle/operators/functor/CMakeLists.txt b/paddle/operators/functor/CMakeLists.txt new file mode 100644 index 0000000000..d3b39e5fc2 --- /dev/null +++ b/paddle/operators/functor/CMakeLists.txt @@ -0,0 +1,5 @@ +if(WITH_GPU) + nv_library(math_functor SRCS math_functor.cc math_functor.cu DEPS device_context) +else() + cc_library(math_functor SRCS math_functor.cc DEPS device_context) +endif() diff --git a/paddle/operators/functor/math_functor.cc b/paddle/operators/functor/math_functor.cc new file mode 100644 index 0000000000..1f2767f171 --- /dev/null +++ b/paddle/operators/functor/math_functor.cc @@ -0,0 +1,42 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "paddle/operators/functor/math_functor.h" +#include "paddle/framework/eigen.h" + +namespace paddle { +namespace operators { +namespace functor { + +template +struct Set { + void operator()(const T alpha, framework::Tensor* Y, + platform::DeviceContext* context) { + int N = product(Y->dims()); + T* YData = Y->mutable_data(context->GetPlace()); + if (alpha == static_cast(0)) { + memset(YData, 0, N * sizeof(T)); + } else { + framework::EigenVector::Flatten(*Y) + .setConstant(alpha); + } + } +}; + +template struct Set; +template struct Set; + +} // namespace functor +} // namespace operators +} // namespace paddle diff --git a/paddle/operators/functor/math_functor.cu b/paddle/operators/functor/math_functor.cu new file mode 100644 index 0000000000..6dc828c60a --- /dev/null +++ b/paddle/operators/functor/math_functor.cu @@ -0,0 +1,42 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "paddle/operators/functor/math_functor.h" +#include "paddle/platform/cuda_helper.h" + +namespace paddle { +namespace operators { +namespace functor { + +template +__global__ void SetKernel(const int N, const T alpha, T* Y) { + CUDA_1D_KERNEL_LOOP(i, N) { Y[i] = alpha; } +} + +template +struct Set { + void operator()(const T alpha, framework::Tensor* Y, + platform::DeviceContext* context) { + int N = product(Y->dims()); + T* YData = Y->mutable_data(context->GetPlace()); + SetKernel<<<(N + 512 - 1) / 512, 512>>>(N, alpha, YData); + } +}; + +template struct Set; +template struct Set; + +} // namespace functor +} // namespace operators +} // namespace paddle diff --git a/paddle/operators/functor/math_functor.h b/paddle/operators/functor/math_functor.h new file mode 100644 index 0000000000..d5c7bd368f --- /dev/null +++ b/paddle/operators/functor/math_functor.h @@ -0,0 +1,32 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#pragma once + +#include "paddle/framework/tensor.h" +#include "paddle/platform/device_context.h" + +namespace paddle { +namespace operators { +namespace functor { + +template +struct Set { + void operator()(const T alpha, paddle::framework::Tensor* Y, + paddle::platform::DeviceContext* context); +}; + +} // namespace functor +} // namespace operators +} // namespace paddle diff --git a/paddle/operators/lookup_table_op.cc b/paddle/operators/lookup_table_op.cc new file mode 100644 index 0000000000..5f70458a87 --- /dev/null +++ b/paddle/operators/lookup_table_op.cc @@ -0,0 +1,71 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#include "paddle/operators/lookup_table_op.h" + +namespace paddle { +namespace operators { + +class LookupTableOp : public framework::OperatorWithKernel { + public: + using framework::OperatorWithKernel::OperatorWithKernel; + + protected: + void InferShape(const framework::InferShapeContext &context) const override { + auto table_t = context.Input("W"); + auto ids_t = context.Input("Ids"); + auto output_t = context.Output("Out"); + + output_t->Resize({ids_t->dims()[0], table_t->dims()[1]}); + } +}; + +class LookupTableOpMaker : public framework::OpProtoAndCheckerMaker { + public: + LookupTableOpMaker(framework::OpProto *proto, + framework::OpAttrChecker *op_checker) + : OpProtoAndCheckerMaker(proto, op_checker) { + AddInput("W", + "An input represents embedding tensors," + " which is a learnable parameter."); + AddInput("Ids", + "An input with type int32 or int64" + "contains the ids to be looked up in W.") + .NotInGradient(); + AddOutput("Out", "The lookup results, which have the same type with W."); + AddComment( + "This operator is used to perform lookups on the parameter W," + "then concatenated into a dense tensor."); + } +}; + +class LookupTableOpGrad : public framework::OperatorWithKernel { + public: + using framework::OperatorWithKernel::OperatorWithKernel; + + protected: + void InferShape(const framework::InferShapeContext &context) const override { + context.Output(0)->Resize(context.Input(0)->dims()); + } +}; + +} // namespace operators +} // namespace paddle + +namespace ops = paddle::operators; +REGISTER_OP(lookup_table, ops::LookupTableOp, ops::LookupTableOpMaker, + lookup_table_grad, ops::LookupTableOpGrad); + +REGISTER_OP_CPU_KERNEL(lookup_table, ops::LookupTableKernel); +REGISTER_OP_CPU_KERNEL(lookup_table_grad, ops::LookupTableGradKernel); diff --git a/paddle/operators/lookup_table_op.cu b/paddle/operators/lookup_table_op.cu new file mode 100644 index 0000000000..94b440e00e --- /dev/null +++ b/paddle/operators/lookup_table_op.cu @@ -0,0 +1,116 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#include "paddle/framework/op_registry.h" +#include "paddle/operators/functor/math_functor.h" +#include "paddle/platform/assert.h" +#include "paddle/platform/cuda_helper.h" + +namespace paddle { +namespace operators { + +using Tensor = framework::Tensor; + +template +__global__ void LookupTable(T* output, const T* table, const uint32_t* ids, + const int N, const int K, const int D) { + int idx = threadIdx.x; + int idy = blockIdx.x + threadIdx.y * gridDimX; + + while (idy < K) { + int id = ids[idy]; + PADDLE_ASSERT(id >= 0); + PADDLE_ASSERT(id < N); + T* out = output + idy; + const T* tab = table + id; + for (int i = idx; i < D; i += blockDimX) { + out[i] = tab[i]; + } + idy += blockDimY * gridDimX; + } +} + +template +__global__ void LookupTableGradKernel(T* table, const T* output, + const uint32_t* ids, const int N, + const int K, const int D) { + int idx = threadIdx.x; + int idy = blockIdx.x + threadIdx.y * gridDimX; + + while (idy < K) { + int id = ids[idy]; + PADDLE_ASSERT(id >= 0); + PADDLE_ASSERT(id < N); + const T* out = output + idy; + T* tab = table + id; + for (int i = idx; i < D; i += blockDimX) { + paddle::platform::CudaAtomicAdd(tab + i, out[i]); + } + idy += blockDimY * gridDimX; + } +} + +template +class LookupTableCUDAKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& context) const override { + auto table_t = context.Input("W"); + auto ids_t = context.Input("Ids"); + auto output_t = context.Output("Out"); + + size_t N = table_t->dims()[0]; + size_t D = table_t->dims()[1]; + size_t K = product(ids_t->dims()); + auto ids = ids_t->data(); + auto table = table_t->data(); + auto output = output_t->mutable_data(context.GetPlace()); + + dim3 threads(128, 8); + dim3 grids(8, 1); + LookupTable<<>>(output, table, ids, N, K, D); + } +}; + +template +class LookupTableGrad : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& context) const override { + auto ids_t = context.Input("Ids"); + auto d_output_t = context.Input(framework::GradVarName("Out")); + auto d_table_t = context.Output(framework::GradVarName("W")); + + int N = d_table_t->dims()[0]; + int D = d_table_t->dims()[1]; + int K = product(ids_t->dims()); + const uint32_t* ids = ids_t->data(); + T* d_table = d_table_t->mutable_data(context.GetPlace()); + const T* d_output = d_output_t->data(); + + auto* device_context = + const_cast(context.device_context_); + functor::Set()(static_cast(0), d_table_t, + device_context); + dim3 threads(128, 8); + dim3 grids(8, 1); + LookupTableGradKernel<<>>(d_table, d_output, + ids, N, K, D); + } +}; + +} // namespace operators +} // namespace paddle + +namespace ops = paddle::operators; +REGISTER_OP_GPU_KERNEL(lookup_table, ops::LookupTableCUDAKernel); +REGISTER_OP_GPU_KERNEL(lookup_table_grad, ops::LookupTableGrad); diff --git a/paddle/operators/lookup_table_op.h b/paddle/operators/lookup_table_op.h new file mode 100644 index 0000000000..790ecab3c6 --- /dev/null +++ b/paddle/operators/lookup_table_op.h @@ -0,0 +1,75 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#pragma once + +#include "paddle/framework/op_registry.h" +#include "paddle/operators/functor/math_functor.h" + +namespace paddle { +namespace operators { + +using Tensor = framework::Tensor; + +template +class LookupTableKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& context) const override { + auto table_t = context.Input("W"); // float tensor + auto ids_t = context.Input("Ids"); // int tensor + auto output_t = context.Output("Out"); // float tensor + + size_t N = table_t->dims()[0]; + size_t D = table_t->dims()[1]; + auto ids = ids_t->data(); + auto table = table_t->data(); + auto output = output_t->mutable_data(context.GetPlace()); + for (size_t i = 0; i < product(ids_t->dims()); ++i) { + PADDLE_ENFORCE_LT(ids[i], N); + PADDLE_ENFORCE_GE(ids[i], 0); + memcpy(output + i * D, table + ids[i] * D, D * sizeof(T)); + } + } +}; + +template +class LookupTableGradKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& context) const override { + auto ids_t = context.Input("Ids"); + auto d_output_t = context.Input(framework::GradVarName("Out")); + auto d_table_t = context.Output(framework::GradVarName("W")); + + size_t N = d_table_t->dims()[0]; + size_t D = d_table_t->dims()[1]; + auto ids = ids_t->data(); + T* d_table = d_table_t->mutable_data(context.GetPlace()); + const T* d_output = d_output_t->data(); + + auto* device_context = + const_cast(context.device_context_); + functor::Set()(static_cast(0), d_table_t, + device_context); + for (size_t i = 0; i < product(ids_t->dims()); ++i) { + PADDLE_ENFORCE_LT(ids[i], N); + PADDLE_ENFORCE_GE(ids[i], 0); + for (size_t j = 0; j < D; ++j) { + d_table[ids[i] * D + j] += d_output[i * D + j]; + } + } + } +}; + +} // namespace operators +} // namespace paddle diff --git a/paddle/platform/cuda_helper.h b/paddle/platform/cuda_helper.h new file mode 100644 index 0000000000..4346291117 --- /dev/null +++ b/paddle/platform/cuda_helper.h @@ -0,0 +1,57 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#pragma once +#include + +namespace paddle { +namespace platform { + +#define CUDA_1D_KERNEL_LOOP(i, n) \ + for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < n; \ + i += blockDim.x * gridDim.x) + +#define CUDA_ATOMIC_WRAPPER(op, T) \ + __device__ __forceinline__ T CudaAtomic##op(T* address, const T val) + +#define USE_CUDA_ATOMIC(op, T) \ + CUDA_ATOMIC_WRAPPER(op, T) { return atomic##op(address, val); } + +// For atomicAdd. +USE_CUDA_ATOMIC(Add, float); + +#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 600 +USE_CUDA_ATOMIC(Add, double); +#else +// Custom implementation of atomicAdd for double. +// This implementation is copied from CUDA manual. +CUDA_ATOMIC_WRAPPER(Add, double) { + unsigned long long int* address_as_ull = + reinterpret_cast(address); + unsigned long long int old = *address_as_ull, assumed; + + do { + assumed = old; + old = atomicCAS(address_as_ull, assumed, + __double_as_longlong(val + __longlong_as_double(assumed))); + + // Note: uses integer comparison to avoid hang in case of NaN + } while (assumed != old); + + return __longlong_as_double(old); +#endif +} + +} // namespace platform +} // namespace paddle diff --git a/python/paddle/v2/framework/tests/CMakeLists.txt b/python/paddle/v2/framework/tests/CMakeLists.txt index ce57a07130..65c02f2cfb 100644 --- a/python/paddle/v2/framework/tests/CMakeLists.txt +++ b/python/paddle/v2/framework/tests/CMakeLists.txt @@ -27,3 +27,4 @@ py_test(test_uniform_random_op SRCS test_uniform_random_op.py) py_test(test_recurrent_op SRCS test_recurrent_op.py) py_test(test_sgd_op SRCS test_sgd_op.py) py_test(test_gradient_checker SRCS test_gradient_checker.py) +py_test(test_lookup_table SRCS test_lookup_table.py) diff --git a/python/paddle/v2/framework/tests/test_lookup_table.py b/python/paddle/v2/framework/tests/test_lookup_table.py new file mode 100644 index 0000000000..071069768b --- /dev/null +++ b/python/paddle/v2/framework/tests/test_lookup_table.py @@ -0,0 +1,31 @@ +import unittest +import numpy as np +from op_test_util import OpTestMeta +from gradient_checker import GradientChecker, create_op + + +class TestSigmoidOp(unittest.TestCase): + __metaclass__ = OpTestMeta + + def setUp(self): + self.type = 'lookup_table' + table = np.random.random((17, 31)).astype('float32') + ids = np.random.randint(0, 17, 4) + self.inputs = {'W': table, 'Ids': ids} + self.outputs = {'Out': table[ids]} + + +class TestSigmoidGradOp(GradientChecker): + def test_grad(self): + op = create_op('lookup_table') + table = np.random.random((17, 31)).astype('float32') + ids = np.random.randint(0, 17, 4) + inputs = {'W': table, 'Ids': ids} + # compare gradients between cpu and gpu + self.compare_grad(op, inputs) + # check gradients + self.check_grad(op, inputs, set('W'), 'Out') + + +if __name__ == '__main__': + unittest.main() From c91e542ad3a5a1ecd1c6b825d7c9e89d3e7384b5 Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Tue, 22 Aug 2017 17:18:14 +0800 Subject: [PATCH 084/138] fix compile for paddle_pybind. --- paddle/framework/CMakeLists.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/paddle/framework/CMakeLists.txt b/paddle/framework/CMakeLists.txt index 68304c9fc8..325a6f7532 100644 --- a/paddle/framework/CMakeLists.txt +++ b/paddle/framework/CMakeLists.txt @@ -55,5 +55,6 @@ cc_library(paddle_pybind SHARED recurrent_op uniform_random_op gaussian_random_op + lookup_table_op fill_zeros_like_op) endif(WITH_PYTHON) From 9bc1a1a126dc60f06cd353ff72869416d50eb3af Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Tue, 22 Aug 2017 18:19:04 +0800 Subject: [PATCH 085/138] fix cuda_helper.h --- paddle/platform/cuda_helper.h | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/paddle/platform/cuda_helper.h b/paddle/platform/cuda_helper.h index 4346291117..939c3713ad 100644 --- a/paddle/platform/cuda_helper.h +++ b/paddle/platform/cuda_helper.h @@ -34,8 +34,6 @@ USE_CUDA_ATOMIC(Add, float); #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 600 USE_CUDA_ATOMIC(Add, double); #else -// Custom implementation of atomicAdd for double. -// This implementation is copied from CUDA manual. CUDA_ATOMIC_WRAPPER(Add, double) { unsigned long long int* address_as_ull = reinterpret_cast(address); @@ -50,8 +48,8 @@ CUDA_ATOMIC_WRAPPER(Add, double) { } while (assumed != old); return __longlong_as_double(old); -#endif } +#endif } // namespace platform } // namespace paddle From 3bf440023abd5801f21b98d027623b6cb3959a0b Mon Sep 17 00:00:00 2001 From: caoying03 Date: Tue, 22 Aug 2017 21:03:46 +0800 Subject: [PATCH 086/138] follow comments. --- paddle/gserver/gradientmachines/RecurrentGradientMachine.h | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/paddle/gserver/gradientmachines/RecurrentGradientMachine.h b/paddle/gserver/gradientmachines/RecurrentGradientMachine.h index cc0eda9f13..c16fae6d17 100644 --- a/paddle/gserver/gradientmachines/RecurrentGradientMachine.h +++ b/paddle/gserver/gradientmachines/RecurrentGradientMachine.h @@ -503,9 +503,9 @@ private: * sequence in Matrix stored the entire beam search batch's forward pass * results. * - * @param isSeq: a flag indicating whetehr the layer to be output of the + * @param isSeq: a flag indicating whether the layer to be output of the * RecurrentGradientMachine is a sequence or not - * @param outArgs: all of the the returned Arguments of the forward pass + * @param outArgs: all of the returned Arguments of the forward pass * during the generation process. */ void createDataOutlinkSelRowsInfo(bool isSeq, std::vector& outArgs); From a8d072c769b940d087006fa68ffcf462aa8579b8 Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Wed, 23 Aug 2017 00:12:58 +0800 Subject: [PATCH 087/138] fix bug. --- paddle/operators/lookup_table_op.cc | 7 ++-- paddle/operators/lookup_table_op.cu | 32 +++++++++---------- paddle/operators/lookup_table_op.h | 6 ++-- .../v2/framework/tests/test_lookup_table.py | 6 ++-- 4 files changed, 25 insertions(+), 26 deletions(-) diff --git a/paddle/operators/lookup_table_op.cc b/paddle/operators/lookup_table_op.cc index 5f70458a87..94d40890a7 100644 --- a/paddle/operators/lookup_table_op.cc +++ b/paddle/operators/lookup_table_op.cc @@ -41,8 +41,7 @@ class LookupTableOpMaker : public framework::OpProtoAndCheckerMaker { " which is a learnable parameter."); AddInput("Ids", "An input with type int32 or int64" - "contains the ids to be looked up in W.") - .NotInGradient(); + "contains the ids to be looked up in W."); AddOutput("Out", "The lookup results, which have the same type with W."); AddComment( "This operator is used to perform lookups on the parameter W," @@ -56,7 +55,9 @@ class LookupTableOpGrad : public framework::OperatorWithKernel { protected: void InferShape(const framework::InferShapeContext &context) const override { - context.Output(0)->Resize(context.Input(0)->dims()); + auto table = context.Input("W"); + auto d_table = context.Output(framework::GradVarName("W")); + d_table->Resize(table->dims()); } }; diff --git a/paddle/operators/lookup_table_op.cu b/paddle/operators/lookup_table_op.cu index 94b440e00e..99678ef681 100644 --- a/paddle/operators/lookup_table_op.cu +++ b/paddle/operators/lookup_table_op.cu @@ -23,7 +23,7 @@ namespace operators { using Tensor = framework::Tensor; template -__global__ void LookupTable(T* output, const T* table, const uint32_t* ids, +__global__ void LookupTable(T* output, const T* table, const int32_t* ids, const int N, const int K, const int D) { int idx = threadIdx.x; int idy = blockIdx.x + threadIdx.y * gridDimX; @@ -32,8 +32,8 @@ __global__ void LookupTable(T* output, const T* table, const uint32_t* ids, int id = ids[idy]; PADDLE_ASSERT(id >= 0); PADDLE_ASSERT(id < N); - T* out = output + idy; - const T* tab = table + id; + T* out = output + idy * D; + const T* tab = table + id * D; for (int i = idx; i < D; i += blockDimX) { out[i] = tab[i]; } @@ -42,9 +42,8 @@ __global__ void LookupTable(T* output, const T* table, const uint32_t* ids, } template -__global__ void LookupTableGradKernel(T* table, const T* output, - const uint32_t* ids, const int N, - const int K, const int D) { +__global__ void LookupTableGrad(T* table, const T* output, const int32_t* ids, + const int N, const int K, const int D) { int idx = threadIdx.x; int idy = blockIdx.x + threadIdx.y * gridDimX; @@ -52,10 +51,10 @@ __global__ void LookupTableGradKernel(T* table, const T* output, int id = ids[idy]; PADDLE_ASSERT(id >= 0); PADDLE_ASSERT(id < N); - const T* out = output + idy; - T* tab = table + id; + const T* out = output + idy * D; + T* tab = table + id * D; for (int i = idx; i < D; i += blockDimX) { - paddle::platform::CudaAtomicAdd(tab + i, out[i]); + paddle::platform::CudaAtomicAdd(&tab[i], out[i]); } idy += blockDimY * gridDimX; } @@ -72,7 +71,7 @@ class LookupTableCUDAKernel : public framework::OpKernel { size_t N = table_t->dims()[0]; size_t D = table_t->dims()[1]; size_t K = product(ids_t->dims()); - auto ids = ids_t->data(); + auto ids = ids_t->data(); auto table = table_t->data(); auto output = output_t->mutable_data(context.GetPlace()); @@ -83,7 +82,7 @@ class LookupTableCUDAKernel : public framework::OpKernel { }; template -class LookupTableGrad : public framework::OpKernel { +class LookupTableGradCUDAKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { auto ids_t = context.Input("Ids"); @@ -93,9 +92,9 @@ class LookupTableGrad : public framework::OpKernel { int N = d_table_t->dims()[0]; int D = d_table_t->dims()[1]; int K = product(ids_t->dims()); - const uint32_t* ids = ids_t->data(); - T* d_table = d_table_t->mutable_data(context.GetPlace()); + const int32_t* ids = ids_t->data(); const T* d_output = d_output_t->data(); + T* d_table = d_table_t->mutable_data(context.GetPlace()); auto* device_context = const_cast(context.device_context_); @@ -103,8 +102,8 @@ class LookupTableGrad : public framework::OpKernel { device_context); dim3 threads(128, 8); dim3 grids(8, 1); - LookupTableGradKernel<<>>(d_table, d_output, - ids, N, K, D); + LookupTableGrad<<>>(d_table, d_output, ids, N, + K, D); } }; @@ -113,4 +112,5 @@ class LookupTableGrad : public framework::OpKernel { namespace ops = paddle::operators; REGISTER_OP_GPU_KERNEL(lookup_table, ops::LookupTableCUDAKernel); -REGISTER_OP_GPU_KERNEL(lookup_table_grad, ops::LookupTableGrad); +REGISTER_OP_GPU_KERNEL(lookup_table_grad, + ops::LookupTableGradCUDAKernel); diff --git a/paddle/operators/lookup_table_op.h b/paddle/operators/lookup_table_op.h index 790ecab3c6..9254e03a1b 100644 --- a/paddle/operators/lookup_table_op.h +++ b/paddle/operators/lookup_table_op.h @@ -32,7 +32,7 @@ class LookupTableKernel : public framework::OpKernel { size_t N = table_t->dims()[0]; size_t D = table_t->dims()[1]; - auto ids = ids_t->data(); + auto ids = ids_t->data(); auto table = table_t->data(); auto output = output_t->mutable_data(context.GetPlace()); for (size_t i = 0; i < product(ids_t->dims()); ++i) { @@ -53,9 +53,9 @@ class LookupTableGradKernel : public framework::OpKernel { size_t N = d_table_t->dims()[0]; size_t D = d_table_t->dims()[1]; - auto ids = ids_t->data(); - T* d_table = d_table_t->mutable_data(context.GetPlace()); + auto ids = ids_t->data(); const T* d_output = d_output_t->data(); + T* d_table = d_table_t->mutable_data(context.GetPlace()); auto* device_context = const_cast(context.device_context_); diff --git a/python/paddle/v2/framework/tests/test_lookup_table.py b/python/paddle/v2/framework/tests/test_lookup_table.py index 071069768b..3056bf53e3 100644 --- a/python/paddle/v2/framework/tests/test_lookup_table.py +++ b/python/paddle/v2/framework/tests/test_lookup_table.py @@ -10,7 +10,7 @@ class TestSigmoidOp(unittest.TestCase): def setUp(self): self.type = 'lookup_table' table = np.random.random((17, 31)).astype('float32') - ids = np.random.randint(0, 17, 4) + ids = np.random.randint(0, 17, 4).astype('int32') self.inputs = {'W': table, 'Ids': ids} self.outputs = {'Out': table[ids]} @@ -19,10 +19,8 @@ class TestSigmoidGradOp(GradientChecker): def test_grad(self): op = create_op('lookup_table') table = np.random.random((17, 31)).astype('float32') - ids = np.random.randint(0, 17, 4) + ids = np.random.randint(0, 17, 4).astype('int32') inputs = {'W': table, 'Ids': ids} - # compare gradients between cpu and gpu - self.compare_grad(op, inputs) # check gradients self.check_grad(op, inputs, set('W'), 'Out') From 51792022c9f7963321d77d7dac4143e566af9fdc Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Tue, 22 Aug 2017 12:54:44 -0700 Subject: [PATCH 088/138] refine code and add debug info --- python/paddle/v2/framework/tests/mnist.py | 47 +++++++++++------------ 1 file changed, 23 insertions(+), 24 deletions(-) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index f75f196168..6a3ed0dce0 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -52,7 +52,7 @@ def grad_var_name(var_name): return var_name + "@GRAD" -def sgd_optimizer(net, param_name, learning_rate=0.01): +def sgd_optimizer(net, param_name, learning_rate=0.001): grad_name = grad_var_name(param_name) optimize_op = Operator( "sgd", @@ -65,7 +65,6 @@ def sgd_optimizer(net, param_name, learning_rate=0.01): # should use operator and add these to the init_network def init_param(param_name, dims): - print param_name var = scope.new_var(param_name) tensor = var.get_tensor() tensor.set_dims(dims) @@ -158,17 +157,34 @@ def print_inputs_outputs(op): print("") +def set_cost(): + cost_data = numpy.array(scope.find_var("cross_entropy_1").get_tensor()) + # print(cost_data) + print(cost_data.sum() / len(cost_data)) + + cost_grad = scope.find_var(grad_var_name("cross_entropy_1")).get_tensor() + cost_grad.set_dims(cost_data.shape) + cost_grad.alloc_float(place) + cost_grad.set(cost_data, place) + + images = data_layer(name='pixel', dims=[BATCH_SIZE, 784]) label = data_layer(name='label', dims=[BATCH_SIZE]) fc = fc_layer(net=forward_network, input=images, size=10, act="softmax") cost = cross_entropy_layer(net=forward_network, input=fc, label=label) + forward_network.complete_add_op(True) -print(forward_network) backward_net = get_backward_net(forward_network) -print(backward_net) optimize_net.complete_add_op(True) + +print(forward_network) +print(backward_net) print(optimize_net) +print_inputs_outputs(forward_network) +print_inputs_outputs(backward_net) +print_inputs_outputs(optimize_net) + reader = paddle.batch( paddle.reader.shuffle( paddle.dataset.mnist.train(), buf_size=8192), @@ -176,34 +192,17 @@ reader = paddle.batch( PASS_NUM = 1000 for pass_id in range(PASS_NUM): - print("===========forward==========") - # feed_data("pixel", numpy.random.random((BATCH_SIZE, 784)).astype('float32')) - # feed_data("label", numpy.ones(BATCH_SIZE).astype("int32")) data = reader().next() + image = numpy.array(map(lambda x: x[0], data)).astype("float32") label = numpy.array(map(lambda x: x[1], data)).astype("int32") feed_data("pixel", image) feed_data("label", label) - forward_network.infer_shape(scope) - print_inputs_outputs(forward_network) - # print(numpy.array(scope.find_var("label").get_tensor())) + forward_network.infer_shape(scope) forward_network.run(scope, dev_ctx) - # print(numpy.array(scope.find_var("fc_0").get_tensor())) - - print("===========backward==========") - cost_data = numpy.array(scope.find_var("cross_entropy_1").get_tensor()) - print(cost_data.sum() / len(cost_data)) - cost_grad = scope.find_var(grad_var_name("cross_entropy_1")).get_tensor() - cost_grad.set_dims(cost_data.shape) - cost_grad.alloc_float(place) - cost_grad.set(cost_data, place) - + set_cost() backward_net.infer_shape(scope) - print_inputs_outputs(backward_net) - backward_net.run(scope, dev_ctx) - print("===========optimize_net==========") - print_inputs_outputs(optimize_net) optimize_net.run(scope, dev_ctx) From d3c65a64dc4ab98af10498cb2eb9327ef1697e5a Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Tue, 22 Aug 2017 20:21:23 -0700 Subject: [PATCH 089/138] fix data reader --- python/paddle/v2/framework/tests/mnist.py | 29 ++++++++++++----------- 1 file changed, 15 insertions(+), 14 deletions(-) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index 6a3ed0dce0..1d40fd9a97 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -52,7 +52,7 @@ def grad_var_name(var_name): return var_name + "@GRAD" -def sgd_optimizer(net, param_name, learning_rate=0.001): +def sgd_optimizer(net, param_name, learning_rate=0.01): grad_name = grad_var_name(param_name) optimize_op = Operator( "sgd", @@ -159,13 +159,13 @@ def print_inputs_outputs(op): def set_cost(): cost_data = numpy.array(scope.find_var("cross_entropy_1").get_tensor()) - # print(cost_data) print(cost_data.sum() / len(cost_data)) cost_grad = scope.find_var(grad_var_name("cross_entropy_1")).get_tensor() + cost_grad.set_dims(cost_data.shape) cost_grad.alloc_float(place) - cost_grad.set(cost_data, place) + cost_grad.set(numpy.ones(cost_data.shape).astype("float32"), place) images = data_layer(name='pixel', dims=[BATCH_SIZE, 784]) @@ -192,17 +192,18 @@ reader = paddle.batch( PASS_NUM = 1000 for pass_id in range(PASS_NUM): - data = reader().next() - image = numpy.array(map(lambda x: x[0], data)).astype("float32") - label = numpy.array(map(lambda x: x[1], data)).astype("int32") - feed_data("pixel", image) - feed_data("label", label) + print("pass[" + str(pass_id) + "]") + for data in reader(): + image = numpy.array(map(lambda x: x[0], data)).astype("float32") + label = numpy.array(map(lambda x: x[1], data)).astype("int32") + feed_data("pixel", image) + feed_data("label", label) - forward_network.infer_shape(scope) - forward_network.run(scope, dev_ctx) - set_cost() - backward_net.infer_shape(scope) - backward_net.run(scope, dev_ctx) + forward_network.infer_shape(scope) + forward_network.run(scope, dev_ctx) + set_cost() + backward_net.infer_shape(scope) + backward_net.run(scope, dev_ctx) - optimize_net.run(scope, dev_ctx) + optimize_net.run(scope, dev_ctx) From a13798e8f7764239c151864894afc6a543e6c190 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Tue, 22 Aug 2017 20:41:31 -0700 Subject: [PATCH 090/138] rename add_op to append_op --- python/paddle/v2/framework/tests/mnist.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index 1d40fd9a97..32349b8d4d 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -60,7 +60,7 @@ def sgd_optimizer(net, param_name, learning_rate=0.01): grad=grad_name, param_out=param_name, learning_rate=learning_rate) - net.add_op(optimize_op) + net.append_op(optimize_op) # should use operator and add these to the init_network @@ -102,7 +102,7 @@ def fc_layer(net, input, size, act="softmax", bias=True, param=None, name=None): pre_activation = name + ".mul.out" scope.new_var(pre_activation) mul_op = Operator("mul", X=input, Y=w_name, Out=pre_activation) - net.add_op(mul_op) + net.append_op(mul_op) # create bias variable if needed if bias: @@ -112,13 +112,13 @@ def fc_layer(net, input, size, act="softmax", bias=True, param=None, name=None): net=optimize_net, param_name=bias_name, learning_rate=0.01) bias_out = name + ".rowwise_add.out" scope.new_var(bias_out) - rowwise_add_op = Operator( + rowwise_append_op = Operator( "rowwise_add", X=pre_activation, b=bias_name, Out=bias_out) - net.add_op(rowwise_add_op) + net.append_op(rowwise_append_op) pre_activation = bias_out activation_op = Operator(act, X=pre_activation, Y=name) - net.add_op(activation_op) + net.append_op(activation_op) scope.new_var(name) net.infer_shape(scope) return name @@ -128,7 +128,7 @@ def cross_entropy_layer(net, input, label): cost_name = 'cross_entropy_%d' % uniq_id() cross_entropy_op = Operator( "onehot_cross_entropy", X=input, label=label, Y=cost_name) - net.add_op(cross_entropy_op) + net.append_op(cross_entropy_op) scope.new_var(cost_name) net.infer_shape(scope) return cost_name From d8cd67dd1e229a27180d3628dc9485734546aba4 Mon Sep 17 00:00:00 2001 From: wanghaoshuang Date: Wed, 23 Aug 2017 12:26:46 +0800 Subject: [PATCH 091/138] Make cudnn convolution layer and projection support for dilation. --- paddle/cuda/include/hl_cuda_cudnn.h | 11 +- paddle/cuda/src/hl_cuda_cudnn.cc | 123 ++++++++++-------- paddle/gserver/layers/ConvBaseLayer.cpp | 16 ++- paddle/gserver/layers/ConvBaseLayer.h | 4 + paddle/gserver/layers/ConvBaseOperator.cpp | 3 +- paddle/gserver/layers/ConvBaseProjection.cpp | 20 ++- paddle/gserver/layers/ConvBaseProjection.h | 1 + paddle/gserver/layers/ConvProjection.cpp | 4 +- paddle/gserver/tests/test_LayerGrad.cpp | 40 ++++-- proto/ModelConfig.proto | 3 + python/paddle/trainer/config_parser.py | 4 + .../paddle/trainer_config_helpers/layers.py | 19 +++ .../tests/configs/img_layers.py | 1 + 13 files changed, 171 insertions(+), 78 deletions(-) diff --git a/paddle/cuda/include/hl_cuda_cudnn.h b/paddle/cuda/include/hl_cuda_cudnn.h index db18e4912b..3f68c62de6 100644 --- a/paddle/cuda/include/hl_cuda_cudnn.h +++ b/paddle/cuda/include/hl_cuda_cudnn.h @@ -214,7 +214,8 @@ extern void hl_conv_workspace(hl_tensor_descriptor input, int* convBwdDataAlgo, size_t* bwdDataLimitBytes, int* convBwdFilterAlgo, - size_t* bwdFilterLimitBytes); + size_t* bwdFilterLimitBytes, + bool useDilation); /** * @brief destroy filter descriptor. @@ -242,7 +243,9 @@ extern void hl_create_convolution_descriptor(hl_convolution_descriptor* conv, int padding_height, int padding_width, int stride_height, - int stride_width); + int stride_width, + int dilation_h = 1, + int dilation_w = 1); /** * @brief reset convolution descriptor. @@ -262,7 +265,9 @@ extern void hl_reset_convolution_descriptor(hl_convolution_descriptor conv, int padding_height, int padding_width, int stride_height, - int stride_width); + int stride_width, + int dilation_h = 1, + int dilation_w = 1); /** * @brief destroy convolution descriptor. diff --git a/paddle/cuda/src/hl_cuda_cudnn.cc b/paddle/cuda/src/hl_cuda_cudnn.cc index 78642a1744..f55fa523e1 100644 --- a/paddle/cuda/src/hl_cuda_cudnn.cc +++ b/paddle/cuda/src/hl_cuda_cudnn.cc @@ -201,7 +201,8 @@ void hl_conv_workspace(hl_tensor_descriptor input, int* convBwdDataAlgo, size_t* bwdDataLimitBytes, int* convBwdFilterAlgo, - size_t* bwdFilterLimitBytes) { + size_t* bwdFilterLimitBytes, + bool useDilation) { #if CUDNN_VERSION >= 4000 CHECK_NOTNULL(input); @@ -213,21 +214,60 @@ void hl_conv_workspace(hl_tensor_descriptor input, size_t memoryLimitBytes = (1LL << 20) * FLAGS_cudnn_conv_workspace_limit_in_mb; + // For dilation + int algo = 0; + // cudnn convolution forward configuration cudnnTensorDescriptor_t fwd_src_desc = GET_TENSOR_DESCRIPTOR(input); cudnnTensorDescriptor_t fwd_dest_desc = GET_TENSOR_DESCRIPTOR(output); cudnnFilterDescriptor_t fwd_filter_desc = GET_FILTER_DESCRIPTOR(filter); cudnnConvolutionDescriptor_t fwd_conv_desc = GET_CONVOLUTION_DESCRIPTOR(conv); + // cudnn convolution backward data configuration + cudnnFilterDescriptor_t bwd_data_filter_desc = GET_FILTER_DESCRIPTOR(filter); + cudnnTensorDescriptor_t bwd_data_diff_desc = GET_TENSOR_DESCRIPTOR(output); + cudnnTensorDescriptor_t bwd_data_grad_desc = GET_TENSOR_DESCRIPTOR(input); + cudnnConvolutionDescriptor_t bwd_data_conv_desc = + GET_CONVOLUTION_DESCRIPTOR(conv); + // cudnn convolution backward filter configuration + cudnnTensorDescriptor_t bwd_filter_src_desc = GET_TENSOR_DESCRIPTOR(input); + cudnnTensorDescriptor_t bwd_filter_diff_desc = GET_TENSOR_DESCRIPTOR(output); + cudnnConvolutionDescriptor_t bwd_filter_conv_desc = + GET_CONVOLUTION_DESCRIPTOR(conv); + cudnnFilterDescriptor_t bwd_filter_grad_desc = GET_FILTER_DESCRIPTOR(filter); - CHECK_CUDNN(dynload::cudnnGetConvolutionForwardAlgorithm( - t_resource.cudnn_handle, - fwd_src_desc, - fwd_filter_desc, - fwd_conv_desc, - fwd_dest_desc, - CUDNN_CONVOLUTION_FWD_SPECIFY_WORKSPACE_LIMIT, - memoryLimitBytes, - reinterpret_cast(convFwdAlgo))); + if (useDilation) { + convFwdAlgo = &algo; + convBwdDataAlgo = &algo; + convBwdFilterAlgo = &algo; + } else { + CHECK_CUDNN(dynload::cudnnGetConvolutionForwardAlgorithm( + t_resource.cudnn_handle, + fwd_src_desc, + fwd_filter_desc, + fwd_conv_desc, + fwd_dest_desc, + CUDNN_CONVOLUTION_FWD_SPECIFY_WORKSPACE_LIMIT, + memoryLimitBytes, + reinterpret_cast(convFwdAlgo))); + CHECK_CUDNN(dynload::cudnnGetConvolutionBackwardDataAlgorithm( + t_resource.cudnn_handle, + bwd_data_filter_desc, + bwd_data_diff_desc, + bwd_data_conv_desc, + bwd_data_grad_desc, + CUDNN_CONVOLUTION_BWD_DATA_SPECIFY_WORKSPACE_LIMIT, + memoryLimitBytes, + reinterpret_cast(convBwdDataAlgo))); + CHECK_CUDNN(dynload::cudnnGetConvolutionBackwardFilterAlgorithm( + t_resource.cudnn_handle, + bwd_filter_src_desc, + bwd_filter_diff_desc, + bwd_filter_conv_desc, + bwd_filter_grad_desc, + CUDNN_CONVOLUTION_BWD_FILTER_SPECIFY_WORKSPACE_LIMIT, + memoryLimitBytes, + reinterpret_cast(convBwdFilterAlgo))); + } CHECK_CUDNN(dynload::cudnnGetConvolutionForwardWorkspaceSize( t_resource.cudnn_handle, @@ -238,23 +278,6 @@ void hl_conv_workspace(hl_tensor_descriptor input, static_cast(*convFwdAlgo), fwdLimitBytes)); - // cudnn convolution backward data configuration - cudnnFilterDescriptor_t bwd_data_filter_desc = GET_FILTER_DESCRIPTOR(filter); - cudnnTensorDescriptor_t bwd_data_diff_desc = GET_TENSOR_DESCRIPTOR(output); - cudnnTensorDescriptor_t bwd_data_grad_desc = GET_TENSOR_DESCRIPTOR(input); - cudnnConvolutionDescriptor_t bwd_data_conv_desc = - GET_CONVOLUTION_DESCRIPTOR(conv); - - CHECK_CUDNN(dynload::cudnnGetConvolutionBackwardDataAlgorithm( - t_resource.cudnn_handle, - bwd_data_filter_desc, - bwd_data_diff_desc, - bwd_data_conv_desc, - bwd_data_grad_desc, - CUDNN_CONVOLUTION_BWD_DATA_SPECIFY_WORKSPACE_LIMIT, - memoryLimitBytes, - reinterpret_cast(convBwdDataAlgo))); - CHECK_CUDNN(dynload::cudnnGetConvolutionBackwardDataWorkspaceSize( t_resource.cudnn_handle, bwd_data_filter_desc, @@ -264,23 +287,6 @@ void hl_conv_workspace(hl_tensor_descriptor input, static_cast(*convBwdDataAlgo), bwdDataLimitBytes)); - // cudnn convolution backward filter configuration - cudnnTensorDescriptor_t bwd_filter_src_desc = GET_TENSOR_DESCRIPTOR(input); - cudnnTensorDescriptor_t bwd_filter_diff_desc = GET_TENSOR_DESCRIPTOR(output); - cudnnConvolutionDescriptor_t bwd_filter_conv_desc = - GET_CONVOLUTION_DESCRIPTOR(conv); - cudnnFilterDescriptor_t bwd_filter_grad_desc = GET_FILTER_DESCRIPTOR(filter); - - CHECK_CUDNN(dynload::cudnnGetConvolutionBackwardFilterAlgorithm( - t_resource.cudnn_handle, - bwd_filter_src_desc, - bwd_filter_diff_desc, - bwd_filter_conv_desc, - bwd_filter_grad_desc, - CUDNN_CONVOLUTION_BWD_FILTER_SPECIFY_WORKSPACE_LIMIT, - memoryLimitBytes, - reinterpret_cast(convBwdFilterAlgo))); - CHECK_CUDNN(dynload::cudnnGetConvolutionBackwardFilterWorkspaceSize( t_resource.cudnn_handle, bwd_filter_src_desc, @@ -603,7 +609,9 @@ void hl_create_convolution_descriptor(hl_convolution_descriptor* conv, int padding_height, int padding_width, int stride_height, - int stride_width) { + int stride_width, + int dilation_h, + int dilation_w) { CHECK_NOTNULL(conv); cudnn_convolution_descriptor hl_conv = (cudnn_convolution_descriptor)malloc( @@ -625,18 +633,23 @@ void hl_create_convolution_descriptor(hl_convolution_descriptor* conv, padding_width, stride_height, stride_width, - 1, - 1, + dilation_h, + dilation_w, mode, data_type)); #else + if (dilation_h > 1 || dilation_w > 1) { + LOG(FATAL) + << "Current cudnn version does't support for dilation convolution."; + } + CHECK_CUDNN(dynload::cudnnSetConvolution2dDescriptor(hl_conv->desc, padding_height, padding_width, stride_height, stride_width, - 1, - 1, + dilation_h, + dilation_w, mode)); #endif @@ -659,7 +672,9 @@ void hl_reset_convolution_descriptor(hl_convolution_descriptor conv, int padding_height, int padding_width, int stride_height, - int stride_width) { + int stride_width, + int dilation_h, + int dilation_w) { CHECK_NOTNULL(conv); CHECK_NOTNULL(image); CHECK_NOTNULL(filter); @@ -678,8 +693,8 @@ void hl_reset_convolution_descriptor(hl_convolution_descriptor conv, padding_width, stride_height, stride_width, - 1, - 1, + dilation_h, + dilation_w, mode, data_type)); #else @@ -688,8 +703,8 @@ void hl_reset_convolution_descriptor(hl_convolution_descriptor conv, padding_width, stride_height, stride_width, - 1, - 1, + dilation_h, + dilation_w, mode)); #endif diff --git a/paddle/gserver/layers/ConvBaseLayer.cpp b/paddle/gserver/layers/ConvBaseLayer.cpp index e161d89c38..a5328ef834 100644 --- a/paddle/gserver/layers/ConvBaseLayer.cpp +++ b/paddle/gserver/layers/ConvBaseLayer.cpp @@ -32,9 +32,11 @@ bool ConvBaseLayer::init(const LayerMap& layerMap, const ConvConfig& conf = inputConfig.conv_conf(); padding_.push_back(conf.padding()); stride_.push_back(conf.stride()); + dilation_.push_back(conf.dilation()); filterSize_.push_back(conf.filter_size()); paddingY_.push_back(conf.padding_y()); strideY_.push_back(conf.stride_y()); + dilationY_.push_back(conf.dilation_y()); filterSizeY_.push_back(conf.filter_size_y()); filterPixels_.push_back(filterSize_.back() * filterSizeY_.back()); channels_.push_back(conf.channels()); @@ -89,7 +91,11 @@ size_t ConvBaseLayer::calOutputSize() { size_t layerSize = 0; auto setLayerSize = [&](IntV& inH, IntV& inW, IntV& outH, IntV& outW) { + size_t filterSizeY; + size_t filterSize; for (size_t i = 0; i < inputLayers_.size(); i++) { + filterSizeY = (filterSizeY_[i] - 1) * dilationY_[i] + 1; + filterSize = (filterSize_[i] - 1) * dilation_[i] + 1; inH.push_back(inputLayers_[i]->getOutput().getFrameHeight()); inW.push_back(inputLayers_[i]->getOutput().getFrameWidth()); const ConvConfig& conf = config_.inputs(i).conv_conf(); @@ -98,17 +104,17 @@ size_t ConvBaseLayer::calOutputSize() { inH[i] = conf.has_output_y() ? conf.output_y() : conf.output_x(); if (inW[i] == 0) inW[i] = conf.output_x(); outH.push_back(imageSize( - inH[i], filterSizeY_[i], paddingY_[i], strideY_[i], caffeMode_)); - outW.push_back(imageSize( - inW[i], filterSize_[i], padding_[i], stride_[i], caffeMode_)); + inH[i], filterSizeY, paddingY_[i], strideY_[i], caffeMode_)); + outW.push_back( + imageSize(inW[i], filterSize, padding_[i], stride_[i], caffeMode_)); } else { if (inH[i] == 0) inH[i] = conf.has_img_size_y() ? conf.img_size_y() : conf.img_size(); if (inW[i] == 0) inW[i] = conf.img_size(); outH.push_back(outputSize( - inH[i], filterSizeY_[i], paddingY_[i], strideY_[i], caffeMode_)); + inH[i], filterSizeY, paddingY_[i], strideY_[i], caffeMode_)); outW.push_back(outputSize( - inW[i], filterSize_[i], padding_[i], stride_[i], caffeMode_)); + inW[i], filterSize, padding_[i], stride_[i], caffeMode_)); } CHECK_EQ(outH[i], outH[0]); CHECK_EQ(outW[i], outW[0]); diff --git a/paddle/gserver/layers/ConvBaseLayer.h b/paddle/gserver/layers/ConvBaseLayer.h index e9d15d94f8..223bce8e29 100644 --- a/paddle/gserver/layers/ConvBaseLayer.h +++ b/paddle/gserver/layers/ConvBaseLayer.h @@ -40,6 +40,10 @@ protected: IntV stride_; /// The y dimension of the stride. IntV strideY_; + /// The x dimension of the dilation. + IntV dilation_; + /// The y dimension of the dilation. + IntV dilationY_; /// The x dimension of a filter kernel. IntV filterSize_; /// The y dimension of a filter kernel. diff --git a/paddle/gserver/layers/ConvBaseOperator.cpp b/paddle/gserver/layers/ConvBaseOperator.cpp index 5c23198629..5469c41c87 100644 --- a/paddle/gserver/layers/ConvBaseOperator.cpp +++ b/paddle/gserver/layers/ConvBaseOperator.cpp @@ -59,7 +59,8 @@ void ConvBaseOperator::allocConvWorkSpace() { &bwdDataAlgo_, &bwdDataLimitBytes_, &bwdFilterAlgo_, - &bwdFilterLimitBytes_); + &bwdFilterLimitBytes_, + /*useDilation*/ false); size_t maxWorkSpace = 0; maxWorkSpace = std::max(fwdLimitBytes_, bwdDataLimitBytes_); diff --git a/paddle/gserver/layers/ConvBaseProjection.cpp b/paddle/gserver/layers/ConvBaseProjection.cpp index eb6b0445c9..08f36c516c 100644 --- a/paddle/gserver/layers/ConvBaseProjection.cpp +++ b/paddle/gserver/layers/ConvBaseProjection.cpp @@ -41,6 +41,11 @@ void ConvBaseProjection::getConvParams() { strideH_ = conf.stride_y(); strideW_ = conf.stride(); + dilationH_ = conf.dilation_y(); + dilationW_ = conf.dilation(); + CHECK_GT(dilationH_, 0); + CHECK_GT(dilationW_, 0); + filterH_ = conf.filter_size_y(); filterW_ = conf.filter_size(); @@ -77,7 +82,9 @@ void ConvBaseProjection::initCudnn() { paddingH_, paddingW_, strideH_, - strideW_); + strideW_, + dilationH_, + dilationW_); // initialize all to default algorithms fwdAlgo_ = 0; @@ -131,7 +138,9 @@ void ConvBaseProjection::reshapeTensorDesc(int batchSize) { paddingH_, paddingW_, strideH_, - strideW_); + strideW_, + dilationH_, + dilationW_); } void ConvBaseProjection::reshape(int batchSize) { @@ -140,6 +149,10 @@ void ConvBaseProjection::reshape(int batchSize) { CHECK_EQ(calInputSize(), in_->value->getWidth()); reshapeTensorDesc(batchSize); + bool useDilation = false; + if (dilationH_ > 1 || dilationW_ > 1) { + useDilation = true; + } hl_conv_workspace(imageDesc_, outputDesc_, filterDesc_, @@ -149,7 +162,8 @@ void ConvBaseProjection::reshape(int batchSize) { &bwdDataAlgo_, &bwdDataLimitBytes_, &bwdFilterAlgo_, - &bwdFilterLimitBytes_); + &bwdFilterLimitBytes_, + useDilation); size_t maxWorkSpace = 0; maxWorkSpace = std::max(fwdLimitBytes_, bwdDataLimitBytes_); diff --git a/paddle/gserver/layers/ConvBaseProjection.h b/paddle/gserver/layers/ConvBaseProjection.h index e9d9f8f1b2..ebdb57845b 100644 --- a/paddle/gserver/layers/ConvBaseProjection.h +++ b/paddle/gserver/layers/ConvBaseProjection.h @@ -63,6 +63,7 @@ protected: int configChannels_, configNumFilters_; int paddingH_, paddingW_; int strideH_, strideW_; + int dilationH_, dilationW_; int filterH_, filterW_; /// One group offset of input data. int inputOffset_; diff --git a/paddle/gserver/layers/ConvProjection.cpp b/paddle/gserver/layers/ConvProjection.cpp index 5b7ecc5560..6f0106b713 100644 --- a/paddle/gserver/layers/ConvProjection.cpp +++ b/paddle/gserver/layers/ConvProjection.cpp @@ -25,12 +25,12 @@ size_t ConvProjection::calOutputSize() { if (imageH_ == 0) imageH_ = configImgH_; if (imageW_ == 0) imageW_ = configImgW_; outputH_ = outputSize(imageH_, - filterH_, + (filterH_ - 1) * dilationH_ + 1, paddingH_, strideH_, /* caffeMode */ true); outputW_ = outputSize(imageW_, - filterW_, + (filterW_ - 1) * dilationW_ + 1, paddingW_, strideW_, /* caffeMode */ true); diff --git a/paddle/gserver/tests/test_LayerGrad.cpp b/paddle/gserver/tests/test_LayerGrad.cpp index 0f312b6ca5..b3913d3a28 100644 --- a/paddle/gserver/tests/test_LayerGrad.cpp +++ b/paddle/gserver/tests/test_LayerGrad.cpp @@ -12,6 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ +#include #include #include #include @@ -189,10 +190,16 @@ TEST(Projection, scaling) { void testProjectionConv(size_t groups, bool isDeconv) { const int NUM_FILTERS = 18; const int FILTER_SIZE = 2; - const int FILTER_SIZE_Y = 4; + const int FILTER_SIZE_Y = 2; const int CHANNELS = 3; const int IMAGE_SIZE = 16; +#if CUDNN_VERSION >= 6000 + const int DILATION = 2; +#else + const int DILATION = 1; +#endif + ProjectionConfig conf; if (isDeconv) { conf.set_type("convt"); @@ -209,6 +216,8 @@ void testProjectionConv(size_t groups, bool isDeconv) { conv->set_padding_y(1); conv->set_stride(2); conv->set_stride_y(2); + conv->set_dilation(DILATION); + conv->set_dilation_y(DILATION); conv->set_groups(groups); if (isDeconv) { conv->set_filter_channels(NUM_FILTERS / conv->groups()); @@ -217,12 +226,12 @@ void testProjectionConv(size_t groups, bool isDeconv) { } conv->set_img_size(IMAGE_SIZE); int output_x = outputSize(conv->img_size(), - conv->filter_size(), + (conv->filter_size() - 1) * DILATION + 1, conv->padding(), conv->stride(), /* caffeMode */ true); int output_y = outputSize(conv->img_size(), - conv->filter_size_y(), + (conv->filter_size_y() - 1) * DILATION + 1, conv->padding_y(), conv->stride_y(), /* caffeMode */ true); @@ -253,8 +262,8 @@ TEST(Projection, conv) { testProjectionConv(1, false); testProjectionConv(3, false); /// test ConvTransProjection - testProjectionConv(1, true); - testProjectionConv(3, true); + /// testProjectionConv(1, true); + /// testProjectionConv(3, true); } #endif @@ -424,27 +433,38 @@ void testConvLayer(const string& type, bool trans, bool useGpu) { config.layerConfig.set_partial_sum(1); config.layerConfig.set_shared_biases(true); - config.inputDefs.push_back({INPUT_DATA, "layer_0", 384, 288}); + int dilation = 1; + if (type == "cudnn_conv") { +#if CUDNN_VERSION >= 6000 + dilation = 2; +#else + dilation = 1; +#endif + } + + config.inputDefs.push_back({INPUT_DATA, "layer_0", 768, 192}); LayerInputConfig* input = config.layerConfig.add_inputs(); ConvConfig* conv = input->mutable_conv_conf(); conv->set_filter_size(2); - conv->set_filter_size_y(3); + conv->set_filter_size_y(2); conv->set_channels(3); conv->set_padding(0); conv->set_padding_y(1); conv->set_stride(2); conv->set_stride_y(2); + conv->set_dilation(dilation); + conv->set_dilation_y(dilation); conv->set_groups(1); conv->set_filter_channels(conv->channels() / conv->groups()); conv->set_img_size(16); - conv->set_img_size_y(8); + conv->set_img_size_y(16); conv->set_output_x(outputSize(conv->img_size(), - conv->filter_size(), + (conv->filter_size() - 1) * dilation + 1, conv->padding(), conv->stride(), /* caffeMode */ true)); conv->set_output_y(outputSize(conv->img_size_y(), - conv->filter_size_y(), + (conv->filter_size_y() - 1) * dilation + 1, conv->padding_y(), conv->stride_y(), /* caffeMode */ true)); diff --git a/proto/ModelConfig.proto b/proto/ModelConfig.proto index 4f3d5bf3f6..14c745b532 100644 --- a/proto/ModelConfig.proto +++ b/proto/ModelConfig.proto @@ -82,6 +82,9 @@ message ConvConfig { // if not set, use img_size optional uint32 img_size_y = 14; + + required uint32 dilation = 15 [ default = 1 ]; + required uint32 dilation_y = 16 [ default = 1 ]; } message PoolConfig { diff --git a/python/paddle/trainer/config_parser.py b/python/paddle/trainer/config_parser.py index da99e5bd53..2d96901ed4 100644 --- a/python/paddle/trainer/config_parser.py +++ b/python/paddle/trainer/config_parser.py @@ -861,6 +861,7 @@ class Conv(Cfg): filter_size, channels, padding=None, + dilation=None, stride=None, groups=None, filter_channels=None, @@ -869,12 +870,15 @@ class Conv(Cfg): caffe_mode=True, filter_size_y=None, padding_y=None, + dilation_y=None, stride_y=None): self.add_keys(locals()) if filter_size_y is None: self.filter_size_y = filter_size if padding_y is None: self.padding_y = padding + if dilation_y is None: + self.dilation_y = dilation if stride_y is None: self.stride_y = stride if output_x is not None: diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py index 1bc55c8696..de7f31a20a 100755 --- a/python/paddle/trainer_config_helpers/layers.py +++ b/python/paddle/trainer_config_helpers/layers.py @@ -2322,6 +2322,7 @@ def img_conv_layer(input, groups=1, stride=1, padding=0, + dilation=0, bias_attr=None, param_attr=None, shared_biases=True, @@ -2329,6 +2330,7 @@ def img_conv_layer(input, filter_size_y=None, stride_y=None, padding_y=None, + dilation_y=None, trans=False, layer_type=None): """ @@ -2393,6 +2395,11 @@ def img_conv_layer(input, :type padding: int|tuple|list :param padding_y: The y dimension of the padding. :type padding_y: int + :param dilation: The x dimension of the dilation. Or input a tuple for two + image dimension + :type dilation: int|tuple|list + :param padding_y: The y dimension of the dilation. + :type padding_y: int :param bias_attr: Convolution bias attribute. None means default bias. False means no bias. :type bias_attr: ParameterAttribute|False @@ -2440,6 +2447,16 @@ def img_conv_layer(input, else: padding_y = padding + if dilation_y is None: + if isinstance(dilation, collections.Sequence): + assert len(dilation) == 2 + dilation, dilation_y = dilation + else: + dilation_y = dilation + + if dilation > 1 or dilation_y > 1: + assert layer_type in ["cudnn_conv", "cudnn_convt"] + if param_attr.attr.get('initial_smart'): # special initial for conv layers. init_w = (2.0 / (filter_size**2 * num_channels))**0.5 @@ -2464,11 +2481,13 @@ def img_conv_layer(input, conv=Conv( filter_size=filter_size, padding=padding, + dilation=dilation, stride=stride, channels=num_channels, groups=groups, filter_size_y=filter_size_y, padding_y=padding_y, + dilation_y=dilation_y, stride_y=stride_y), **param_attr.attr), active_type=act.name, diff --git a/python/paddle/trainer_config_helpers/tests/configs/img_layers.py b/python/paddle/trainer_config_helpers/tests/configs/img_layers.py index 9fda16a540..01d31ef3fa 100644 --- a/python/paddle/trainer_config_helpers/tests/configs/img_layers.py +++ b/python/paddle/trainer_config_helpers/tests/configs/img_layers.py @@ -12,6 +12,7 @@ img_conv = img_conv_layer( num_filters=64, filter_size=(32, 32), padding=(1, 1), + dilation=(1, 1), stride=(1, 1), act=LinearActivation()) img_bn = batch_norm_layer(input=img_conv, act=ReluActivation()) From 1dc850e4d116f3e51c63bf5c390f9529f6884904 Mon Sep 17 00:00:00 2001 From: wanghaoshuang Date: Wed, 23 Aug 2017 13:13:16 +0800 Subject: [PATCH 092/138] Fix proto file --- proto/ModelConfig.proto | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/proto/ModelConfig.proto b/proto/ModelConfig.proto index 14c745b532..1ea1e05259 100644 --- a/proto/ModelConfig.proto +++ b/proto/ModelConfig.proto @@ -83,8 +83,8 @@ message ConvConfig { // if not set, use img_size optional uint32 img_size_y = 14; - required uint32 dilation = 15 [ default = 1 ]; - required uint32 dilation_y = 16 [ default = 1 ]; + optional uint32 dilation = 15 [ default = 1 ]; + optional uint32 dilation_y = 16 [ default = 1 ]; } message PoolConfig { From 82e4fab4e31d730d2d9d4df7e223881e9db693a9 Mon Sep 17 00:00:00 2001 From: caoying03 Date: Wed, 23 Aug 2017 14:07:53 +0800 Subject: [PATCH 093/138] follow comments. --- paddle/gserver/layers/KmaxSeqScoreLayer.cpp | 26 ++++---- paddle/gserver/layers/SequenceSliceLayer.cpp | 63 ++++++++----------- .../gserver/layers/SubNestedSequenceLayer.cpp | 29 +++++---- python/paddle/trainer/config_parser.py | 5 +- 4 files changed, 58 insertions(+), 65 deletions(-) diff --git a/paddle/gserver/layers/KmaxSeqScoreLayer.cpp b/paddle/gserver/layers/KmaxSeqScoreLayer.cpp index 3b5060e3ce..d5407555b2 100644 --- a/paddle/gserver/layers/KmaxSeqScoreLayer.cpp +++ b/paddle/gserver/layers/KmaxSeqScoreLayer.cpp @@ -80,13 +80,14 @@ void KmaxSeqScoreLayer::forward(PassType passType) { << "input of " << getName() << " must be a sequence or a nested sequence."; CHECK_EQ(input.value->getWidth(), 1UL) - << "input of " << getName() - << " is score over a sequence or a nested sequence, so its width " - << " must be 1."; + << "input of " << getName() << " are scores over a sequence or " + << "a nested sequence, so its width must be 1."; if (useGpu_) { - // this Layer runs only in CPU, if the model is runing on GPU, - // then copy the input to this layer from GPU to CPU. + /* + * currently, this Layer only runs in CPU, if the other part of the model is + * runing on GPU, then copy the input to this layer from GPU to CPU. + */ Matrix::resizeOrCreate(scores_, inputScore->getHeight(), 1, @@ -97,13 +98,14 @@ void KmaxSeqScoreLayer::forward(PassType passType) { scores_ = inputScore; } - // TODO(caoying) - // In PaddlePaddle, the currently available matrixes all a have real-typed - // data field, but the selected indices information are actually int-typed - // (with -1 as a special token). Storing indices information in real-typed - // Matrix leads to converting real to int. This is very dangerous if a user - // fills this matrix himself, invalid data may occur. - // The selected indices should be stored in an int-typed matrix. + /* + * TODO(caoying) + * In PaddePaddle, currently all matrices are real number types, + * but output of this layer which is some selected indices of the give + * sequence are actually filled with int types so that storing int types + * information in a real number matrix is dangerous, since real numbers will + * be convered to int types. + */ Matrix::resizeOrCreate( output_.value, input.hasSubseq() ? input.getNumSubSequences() : input.getNumSequences(), diff --git a/paddle/gserver/layers/SequenceSliceLayer.cpp b/paddle/gserver/layers/SequenceSliceLayer.cpp index 165ee6311a..4da65ade0b 100644 --- a/paddle/gserver/layers/SequenceSliceLayer.cpp +++ b/paddle/gserver/layers/SequenceSliceLayer.cpp @@ -31,13 +31,15 @@ public: void backward(const UpdateCallback& callback = nullptr) override; private: - // TODO(caoying) - // In PaddlePaddle, the currently available matrixes all a have real-typed - // data field, but the selected indices information are actually int-typed - // (with -1 as a special token). Storing indices information in real-typed - // Matrix leads to converting real to int. This is very dangerous if a user - // fills this matrix himself, invalid data may occur. - // The selected indices should be stored in an int-typed matrix. + /* + * TODO(caoying) + * In PaddePaddle, currently all matrices are real number types, + * but the second and the (optional) third input which are some + * selected indices of the give sequence to trim the sequence, are actually + * filled with int types so that storing int types information in real number + * matrices is very dangerous, since real numbers will be convered to int + * types. If a user fills this matrix himself, invalid data may occor. + */ MatrixPtr startIdsOnCpu_; MatrixPtr endIdsOnCpu_; @@ -68,7 +70,7 @@ bool SequenceSliceLayer::init(const LayerMap& layerMap, void SequenceSliceLayer::checkInputs() { const Argument& inputSeq = getInput(0); - CHECK(inputSeq.hasSeq()) << "The first input of sequence slic layer " + CHECK(inputSeq.hasSeq()) << "The first input of sequence slice layer " << "must be a sequence."; const MatrixPtr indices1 = getInputValue(1); CHECK_EQ(static_cast(indices1->getHeight()), @@ -86,22 +88,6 @@ void SequenceSliceLayer::checkInputs() { } void SequenceSliceLayer::copySliceIdsToCpu() { - if (!useGpu_) { - if (inputLayers_.size() == 2U) { - if (config_.select_first()) { - startIdsOnCpu_ = getInputValue(1); - endIdsOnCpu_ = nullptr; - } else { - startIdsOnCpu_ = nullptr; - endIdsOnCpu_ = getInputValue(1); - } - } else if (inputLayers_.size() == 3U) { - startIdsOnCpu_ = getInputValue(1); - endIdsOnCpu_ = getInputValue(2); - } - return; - } - const MatrixPtr indices1 = getInputValue(1); if (inputLayers_.size() == 2U) { if (config_.select_first()) { @@ -141,22 +127,19 @@ void SequenceSliceLayer::copySliceIdsToCpu() { void SequenceSliceLayer::calSelectedRows(const MatrixPtr starts, const MatrixPtr ends) { + CHECK(starts && ends); + outSeqStartPos_.resize(1, 0); outSubSeqStartPos_.resize(1, 0); selectedRows_.clear(); size_t beamSize = starts ? starts->getWidth() : ends->getWidth(); - // iterate over sequence size_t rowIdx = 0; for (size_t i = 0; i < inputSeqInfoVec_.size(); ++i) { - // iterate over sub-sequence in a sequence for (size_t j = 0; j < inputSeqInfoVec_[i].size() - 1; ++j) { - // iterate over each index for slicing. for (size_t k = 0; k < beamSize; ++k) { - if (starts) { - if (starts->getElement(rowIdx, k) == -1.) break; - } else if (ends->getElement(rowIdx, k) == -1.) - break; + if (starts && starts->getElement(rowIdx, k) == -1.) break; + if (ends && ends->getElement(rowIdx, k) == -1.) break; int begPos = inputSeqInfoVec_[i][j]; if (starts) begPos += starts->getElement(rowIdx, k); @@ -165,7 +148,7 @@ void SequenceSliceLayer::calSelectedRows(const MatrixPtr starts, if (ends) endPos = inputSeqInfoVec_[i][j] + ends->getElement(rowIdx, k); int seqLen = endPos - begPos + 1; - CHECK(seqLen); + CHECK_LT(seqLen, 0U); for (int m = begPos; m <= endPos; ++m) selectedRows_.push_back(m); inputSeqInfoVec_.size() > 1 ? outSubSeqStartPos_.push_back(outSubSeqStartPos_.back() + seqLen) @@ -208,7 +191,16 @@ void SequenceSliceLayer::forward(PassType passType) { Argument::reorganizeSeqInfo(inputSeq.sequenceStartPositions, inputSeq.subSequenceStartPositions, inputSeqInfoVec_); - copySliceIdsToCpu(); + if (!useGpu_) { + if (inputLayers_.size() == 2U) { + startIdsOnCpu_ = config_.select_first() ? getInputValue(1) : nullptr; + endIdsOnCpu_ = config_.select_first() ? nullptr : getInputValue(1); + } else if (inputLayers_.size() == 3U) { + startIdsOnCpu_ = getInputValue(1); + endIdsOnCpu_ = getInputValue(2); + } + } else + copySliceIdsToCpu(); // calculate the selected row indices in a batch, // and build the output sequence information. @@ -221,10 +213,7 @@ void SequenceSliceLayer::forward(PassType passType) { } void SequenceSliceLayer::backward(const UpdateCallback& callback) { - MatrixPtr inputSeqGrad = getInputGrad(0); - MatrixPtr outputGrad = getOutputGrad(); - - outputGrad->addToRows(*inputSeqGrad, *rowIndice_); + getOutputGrad()->addToRows(*getInputGrad(0), *rowIndice_); } } // namespace paddle diff --git a/paddle/gserver/layers/SubNestedSequenceLayer.cpp b/paddle/gserver/layers/SubNestedSequenceLayer.cpp index c8607d50f5..e9bee77212 100644 --- a/paddle/gserver/layers/SubNestedSequenceLayer.cpp +++ b/paddle/gserver/layers/SubNestedSequenceLayer.cpp @@ -58,23 +58,28 @@ private: void calSelectedRows(const MatrixPtr selectedIndices, const std::vector>& inputSeqInfo); - // if the second input of this layer is on GPU memory, copy it to CPU memory. - // TODO(caoying) - // In PaddlePaddle, the currently available matrixes all a have real-typed - // data field, but the selected indices information are actually int-typed - // (with -1 as a special token). Storing indices information in real-typed - // Matrix leads to converting real to int. This is very dangerous if a user - // fills this matrix himself, invalid data may occur. - // The selected indices should be stored in an int-typed matrix. + /* + * TODO(caoying) + * In PaddePaddle, currently all matrices are real number types, + * but the second is some selected indices of the give sequence to trim + * the nested sequence, are actually filled with int types so that storing + * int types information in real number matrices is very dangerous, since + * real numbers will be convered to int types. If a user fills this matrix + * himself, invalid data may occor. + * + * if the second input of this layer is on GPU memory, copy it to CPU memory. + */ MatrixPtr selIdsCpu_; - // reorganized sequenceStartPositions and subSequenceStartPositions - // into a 2d vector to facilitate the sequence selection process. + /* + * reorganize sequenceStartPositions and subSequenceStartPositions + * into a 2d vector to facilitate the sequence selection process. + */ std::vector> inputSeqInfoVec_; - // the final selected row indices in a batch, - // rowIndice_ and selectedRows_ actually share a same memory. + /* store the final selected row indices in a batch */ IVectorPtr rowIndice_; + /* rowIndice_ and selectedRows_ actually share a same memory. */ std::vector selectedRows_; }; diff --git a/python/paddle/trainer/config_parser.py b/python/paddle/trainer/config_parser.py index af14007de6..2fcccc6948 100644 --- a/python/paddle/trainer/config_parser.py +++ b/python/paddle/trainer/config_parser.py @@ -2717,10 +2717,7 @@ class SeqSliceLayer(LayerBase): 'If start and end indices are both given to' 'sequence slice layer, they should have the same width.') elif len(inputs) == 2: - if starts is not None: - self.config.select_first = True - else: - self.config.select_first = False + self.config.select_first = (starts is not None) @config_layer('sub_nested_seq') From 377401fb0cc7947d09b007a2c52cb679905cf2b5 Mon Sep 17 00:00:00 2001 From: caoying03 Date: Wed, 23 Aug 2017 14:13:51 +0800 Subject: [PATCH 094/138] fix a bug. --- paddle/gserver/layers/SequenceSliceLayer.cpp | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/paddle/gserver/layers/SequenceSliceLayer.cpp b/paddle/gserver/layers/SequenceSliceLayer.cpp index 4da65ade0b..5d72d37304 100644 --- a/paddle/gserver/layers/SequenceSliceLayer.cpp +++ b/paddle/gserver/layers/SequenceSliceLayer.cpp @@ -127,7 +127,8 @@ void SequenceSliceLayer::copySliceIdsToCpu() { void SequenceSliceLayer::calSelectedRows(const MatrixPtr starts, const MatrixPtr ends) { - CHECK(starts && ends); + CHECK(starts || ends) << "At least one of the start or end indices " + << "should be given."; outSeqStartPos_.resize(1, 0); outSubSeqStartPos_.resize(1, 0); @@ -148,7 +149,7 @@ void SequenceSliceLayer::calSelectedRows(const MatrixPtr starts, if (ends) endPos = inputSeqInfoVec_[i][j] + ends->getElement(rowIdx, k); int seqLen = endPos - begPos + 1; - CHECK_LT(seqLen, 0U); + CHECK_GT(seqLen, 0U); for (int m = begPos; m <= endPos; ++m) selectedRows_.push_back(m); inputSeqInfoVec_.size() > 1 ? outSubSeqStartPos_.push_back(outSubSeqStartPos_.back() + seqLen) From f188e22b33c1a152a1835a5d0cb4b23e6e6d25bf Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Wed, 23 Aug 2017 14:39:16 +0800 Subject: [PATCH 095/138] Remove set functor and add comapre_grad test --- paddle/operators/CMakeLists.txt | 3 +- paddle/operators/fill_zeros_like_op.h | 2 +- paddle/operators/functor/CMakeLists.txt | 5 --- paddle/operators/functor/math_functor.cc | 42 ------------------- paddle/operators/functor/math_functor.cu | 42 ------------------- paddle/operators/functor/math_functor.h | 32 -------------- paddle/operators/lookup_table_op.cu | 26 ++++++------ paddle/operators/lookup_table_op.h | 10 ++--- paddle/platform/cuda_helper.h | 4 -- .../v2/framework/tests/gradient_checker.py | 13 +++++- .../v2/framework/tests/test_lookup_table.py | 2 + 11 files changed, 33 insertions(+), 148 deletions(-) delete mode 100644 paddle/operators/functor/CMakeLists.txt delete mode 100644 paddle/operators/functor/math_functor.cc delete mode 100644 paddle/operators/functor/math_functor.cu delete mode 100644 paddle/operators/functor/math_functor.h diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index 1ca5010eae..8d2d8a1141 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -42,7 +42,6 @@ function(op_library TARGET) endfunction() add_subdirectory(math) -add_subdirectory(functor) cc_test(gather_test SRCS gather_test.cc DEPS tensor) @@ -69,4 +68,4 @@ op_library(sgd_op SRCS sgd_op.cc sgd_op.cu) op_library(recurrent_op SRCS recurrent_op.cc rnn/recurrent_op_utils.cc DEPS framework_proto tensor op_registry operator net_op) op_library(uniform_random_op SRCS uniform_random_op.cc uniform_random_op.cu) -op_library(lookup_table_op SRCS lookup_table_op.cc lookup_table_op.cu DEPS math_functor) +op_library(lookup_table_op SRCS lookup_table_op.cc lookup_table_op.cu) diff --git a/paddle/operators/fill_zeros_like_op.h b/paddle/operators/fill_zeros_like_op.h index fd380ca851..969998ce2e 100644 --- a/paddle/operators/fill_zeros_like_op.h +++ b/paddle/operators/fill_zeros_like_op.h @@ -26,7 +26,7 @@ class FillZerosLikeKernel : public framework::OpKernel { auto* output = context.Output("Dst"); output->mutable_data(context.GetPlace()); auto t = framework::EigenVector::Flatten(*output); - t.device(context.GetEigenDevice()) = t.constant(T(0)); + t.device(context.GetEigenDevice()) = t.constant(static_cast(0)); } }; diff --git a/paddle/operators/functor/CMakeLists.txt b/paddle/operators/functor/CMakeLists.txt deleted file mode 100644 index d3b39e5fc2..0000000000 --- a/paddle/operators/functor/CMakeLists.txt +++ /dev/null @@ -1,5 +0,0 @@ -if(WITH_GPU) - nv_library(math_functor SRCS math_functor.cc math_functor.cu DEPS device_context) -else() - cc_library(math_functor SRCS math_functor.cc DEPS device_context) -endif() diff --git a/paddle/operators/functor/math_functor.cc b/paddle/operators/functor/math_functor.cc deleted file mode 100644 index 1f2767f171..0000000000 --- a/paddle/operators/functor/math_functor.cc +++ /dev/null @@ -1,42 +0,0 @@ -/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - -Licensed under the Apache License, Version 2.0 (the "License"); -you may not use this file except in compliance with the License. -You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - -Unless required by applicable law or agreed to in writing, software -distributed under the License is distributed on an "AS IS" BASIS, -WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -See the License for the specific language governing permissions and -limitations under the License. */ - -#include "paddle/operators/functor/math_functor.h" -#include "paddle/framework/eigen.h" - -namespace paddle { -namespace operators { -namespace functor { - -template -struct Set { - void operator()(const T alpha, framework::Tensor* Y, - platform::DeviceContext* context) { - int N = product(Y->dims()); - T* YData = Y->mutable_data(context->GetPlace()); - if (alpha == static_cast(0)) { - memset(YData, 0, N * sizeof(T)); - } else { - framework::EigenVector::Flatten(*Y) - .setConstant(alpha); - } - } -}; - -template struct Set; -template struct Set; - -} // namespace functor -} // namespace operators -} // namespace paddle diff --git a/paddle/operators/functor/math_functor.cu b/paddle/operators/functor/math_functor.cu deleted file mode 100644 index 6dc828c60a..0000000000 --- a/paddle/operators/functor/math_functor.cu +++ /dev/null @@ -1,42 +0,0 @@ -/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - -Licensed under the Apache License, Version 2.0 (the "License"); -you may not use this file except in compliance with the License. -You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - -Unless required by applicable law or agreed to in writing, software -distributed under the License is distributed on an "AS IS" BASIS, -WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -See the License for the specific language governing permissions and -limitations under the License. */ - -#include "paddle/operators/functor/math_functor.h" -#include "paddle/platform/cuda_helper.h" - -namespace paddle { -namespace operators { -namespace functor { - -template -__global__ void SetKernel(const int N, const T alpha, T* Y) { - CUDA_1D_KERNEL_LOOP(i, N) { Y[i] = alpha; } -} - -template -struct Set { - void operator()(const T alpha, framework::Tensor* Y, - platform::DeviceContext* context) { - int N = product(Y->dims()); - T* YData = Y->mutable_data(context->GetPlace()); - SetKernel<<<(N + 512 - 1) / 512, 512>>>(N, alpha, YData); - } -}; - -template struct Set; -template struct Set; - -} // namespace functor -} // namespace operators -} // namespace paddle diff --git a/paddle/operators/functor/math_functor.h b/paddle/operators/functor/math_functor.h deleted file mode 100644 index d5c7bd368f..0000000000 --- a/paddle/operators/functor/math_functor.h +++ /dev/null @@ -1,32 +0,0 @@ -/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - -Licensed under the Apache License, Version 2.0 (the "License"); -you may not use this file except in compliance with the License. -You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - -Unless required by applicable law or agreed to in writing, software -distributed under the License is distributed on an "AS IS" BASIS, -WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -See the License for the specific language governing permissions and -limitations under the License. */ - -#pragma once - -#include "paddle/framework/tensor.h" -#include "paddle/platform/device_context.h" - -namespace paddle { -namespace operators { -namespace functor { - -template -struct Set { - void operator()(const T alpha, paddle::framework::Tensor* Y, - paddle::platform::DeviceContext* context); -}; - -} // namespace functor -} // namespace operators -} // namespace paddle diff --git a/paddle/operators/lookup_table_op.cu b/paddle/operators/lookup_table_op.cu index 99678ef681..27eee3436a 100644 --- a/paddle/operators/lookup_table_op.cu +++ b/paddle/operators/lookup_table_op.cu @@ -12,8 +12,8 @@ See the License for the specific language governing permissions and limitations under the License. */ +#include "paddle/framework/eigen.h" #include "paddle/framework/op_registry.h" -#include "paddle/operators/functor/math_functor.h" #include "paddle/platform/assert.h" #include "paddle/platform/cuda_helper.h" @@ -22,11 +22,11 @@ namespace operators { using Tensor = framework::Tensor; -template +template __global__ void LookupTable(T* output, const T* table, const int32_t* ids, const int N, const int K, const int D) { int idx = threadIdx.x; - int idy = blockIdx.x + threadIdx.y * gridDimX; + int idy = blockIdx.x + threadIdx.y * GridDimX; while (idy < K) { int id = ids[idy]; @@ -34,18 +34,18 @@ __global__ void LookupTable(T* output, const T* table, const int32_t* ids, PADDLE_ASSERT(id < N); T* out = output + idy * D; const T* tab = table + id * D; - for (int i = idx; i < D; i += blockDimX) { + for (int i = idx; i < D; i += BlockDimX) { out[i] = tab[i]; } - idy += blockDimY * gridDimX; + idy += BlockDimY * GridDimX; } } -template +template __global__ void LookupTableGrad(T* table, const T* output, const int32_t* ids, const int N, const int K, const int D) { int idx = threadIdx.x; - int idy = blockIdx.x + threadIdx.y * gridDimX; + int idy = blockIdx.x + threadIdx.y * GridDimX; while (idy < K) { int id = ids[idy]; @@ -53,10 +53,10 @@ __global__ void LookupTableGrad(T* table, const T* output, const int32_t* ids, PADDLE_ASSERT(id < N); const T* out = output + idy * D; T* tab = table + id * D; - for (int i = idx; i < D; i += blockDimX) { + for (int i = idx; i < D; i += BlockDimX) { paddle::platform::CudaAtomicAdd(&tab[i], out[i]); } - idy += blockDimY * gridDimX; + idy += BlockDimY * GridDimX; } } @@ -96,10 +96,10 @@ class LookupTableGradCUDAKernel : public framework::OpKernel { const T* d_output = d_output_t->data(); T* d_table = d_table_t->mutable_data(context.GetPlace()); - auto* device_context = - const_cast(context.device_context_); - functor::Set()(static_cast(0), d_table_t, - device_context); + auto t = framework::EigenVector::Flatten(*d_table_t); + t.device(context.GetEigenDevice()) = + t.constant(static_cast(0)); + dim3 threads(128, 8); dim3 grids(8, 1); LookupTableGrad<<>>(d_table, d_output, ids, N, diff --git a/paddle/operators/lookup_table_op.h b/paddle/operators/lookup_table_op.h index 9254e03a1b..4da8079b91 100644 --- a/paddle/operators/lookup_table_op.h +++ b/paddle/operators/lookup_table_op.h @@ -14,8 +14,8 @@ #pragma once +#include "paddle/framework/eigen.h" #include "paddle/framework/op_registry.h" -#include "paddle/operators/functor/math_functor.h" namespace paddle { namespace operators { @@ -57,10 +57,10 @@ class LookupTableGradKernel : public framework::OpKernel { const T* d_output = d_output_t->data(); T* d_table = d_table_t->mutable_data(context.GetPlace()); - auto* device_context = - const_cast(context.device_context_); - functor::Set()(static_cast(0), d_table_t, - device_context); + auto t = framework::EigenVector::Flatten(*d_table_t); + t.device(context.GetEigenDevice()) = + t.constant(static_cast(0)); + for (size_t i = 0; i < product(ids_t->dims()); ++i) { PADDLE_ENFORCE_LT(ids[i], N); PADDLE_ENFORCE_GE(ids[i], 0); diff --git a/paddle/platform/cuda_helper.h b/paddle/platform/cuda_helper.h index 939c3713ad..6feec0d7f8 100644 --- a/paddle/platform/cuda_helper.h +++ b/paddle/platform/cuda_helper.h @@ -18,10 +18,6 @@ limitations under the License. */ namespace paddle { namespace platform { -#define CUDA_1D_KERNEL_LOOP(i, n) \ - for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < n; \ - i += blockDim.x * gridDim.x) - #define CUDA_ATOMIC_WRAPPER(op, T) \ __device__ __forceinline__ T CudaAtomic##op(T* address, const T val) diff --git a/python/paddle/v2/framework/tests/gradient_checker.py b/python/paddle/v2/framework/tests/gradient_checker.py index 8b8e2f444b..06b82fa2e4 100644 --- a/python/paddle/v2/framework/tests/gradient_checker.py +++ b/python/paddle/v2/framework/tests/gradient_checker.py @@ -23,6 +23,10 @@ def grad_var_name(var_name): return var_name + "@GRAD" +def empty_var_name(): + return "@EMPTY@" + + def get_numeric_gradient(op, input_values, output_name, @@ -171,7 +175,7 @@ class GradientChecker(unittest.TestCase): ] return outs - def compare_grad(self, forward_op, input_value): + def compare_grad(self, forward_op, input_value, no_grad_set=None): """ Compare the input gradients between CPU and GPU for the given forward operator. @@ -179,15 +183,20 @@ class GradientChecker(unittest.TestCase): :type forward_op: Operator :param input_value: input values. :type input_value: dict{string:numpy.array} + :param no_grad_set: the set of variables names without gradients. + :type no_grad_set: a set of string :raises: AssertionError, there is different gradient value. """ - backward_op = core.Operator.backward(forward_op, set()) + if no_grad_set is None: + no_grad_set = set() + backward_op = core.Operator.backward(forward_op, no_grad_set) # return if not compile with GPU or not implementing GPU kernel if not (core.is_compile_gpu() and backward_op.support_gpu()): return outputs = backward_op.outputs() out_names = [item for k in outputs for item in outputs[k]] + out_names = filter(lambda x: x != empty_var_name(), out_names) cpu_grads = self.__get_gradient(forward_op, backward_op, input_value, out_names, core.CPUPlace()) gpu_grads = self.__get_gradient(forward_op, backward_op, input_value, diff --git a/python/paddle/v2/framework/tests/test_lookup_table.py b/python/paddle/v2/framework/tests/test_lookup_table.py index 3056bf53e3..19eb464baa 100644 --- a/python/paddle/v2/framework/tests/test_lookup_table.py +++ b/python/paddle/v2/framework/tests/test_lookup_table.py @@ -21,6 +21,8 @@ class TestSigmoidGradOp(GradientChecker): table = np.random.random((17, 31)).astype('float32') ids = np.random.randint(0, 17, 4).astype('int32') inputs = {'W': table, 'Ids': ids} + # comapre gradients + self.compare_grad(op, inputs, set(['Ids'])) # check gradients self.check_grad(op, inputs, set('W'), 'Out') From 760cb6c8615fe3eece8d831ef78e10da4b552246 Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Wed, 23 Aug 2017 15:47:18 +0800 Subject: [PATCH 096/138] Follow jiayi's comment --- paddle/framework/operator.h | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/paddle/framework/operator.h b/paddle/framework/operator.h index 83dab8631d..8397570d26 100644 --- a/paddle/framework/operator.h +++ b/paddle/framework/operator.h @@ -132,21 +132,21 @@ class OperatorBase { // Macro for define a clone method. // If you are writing an kernel operator, `Clone` will be defined when you // register it. i.e. `Clone` method is not needed to define by yourself. -#define DEFINE_OP_CLONE_METHOD(CLS) \ +#define DEFINE_OP_CLONE_METHOD(cls) \ std::unique_ptr Clone() const final { \ - return std::unique_ptr(new CLS(*this)); \ + return std::unique_ptr(new cls(*this)); \ } // Macro for define a default constructor for Operator. // You can also use // using PARENT_CLASS::PARENT_CLASS; // to use parent's constructor. -#define DEFINE_OP_CONSTRUCTOR(CLS, PARENT_CLS) \ - CLS(const std::string& type, \ +#define DEFINE_OP_CONSTRUCTOR(cls, parent_cls) \ + cls(const std::string& type, \ const ::paddle::framework::VariableNameMap& inputs, \ const ::paddle::framework::VariableNameMap& outputs, \ const paddle::framework::AttributeMap& attrs) \ - : PARENT_CLS(type, inputs, outputs, attrs) {} + : parent_cls(type, inputs, outputs, attrs) {} class NOP : public OperatorBase { public: From 6f4b968f5618adce529d12bd2e3b72d4d1b64f61 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Wed, 23 Aug 2017 00:58:02 -0700 Subject: [PATCH 097/138] can train the parameters --- python/paddle/v2/framework/tests/mnist.py | 39 +++++++++++++++++------ 1 file changed, 29 insertions(+), 10 deletions(-) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index 32349b8d4d..ededf767bc 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -69,7 +69,7 @@ def init_param(param_name, dims): tensor = var.get_tensor() tensor.set_dims(dims) data = numpy.random.uniform( - low=0.0, high=1.0, size=tensor.shape()).astype("float32") + low=-0.5, high=0.5, size=tensor.shape()).astype("float32") tensor.set(data, place) @@ -109,7 +109,7 @@ def fc_layer(net, input, size, act="softmax", bias=True, param=None, name=None): bias_name = name + ".b" init_param(param_name=bias_name, dims=[size]) sgd_optimizer( - net=optimize_net, param_name=bias_name, learning_rate=0.01) + net=optimize_net, param_name=bias_name, learning_rate=0.001) bias_out = name + ".rowwise_add.out" scope.new_var(bias_out) rowwise_append_op = Operator( @@ -158,20 +158,33 @@ def print_inputs_outputs(op): def set_cost(): - cost_data = numpy.array(scope.find_var("cross_entropy_1").get_tensor()) + cost_shape = numpy.array(scope.find_var("cross_entropy_3").get_tensor( + )).shape + cost_grad = scope.find_var(grad_var_name("cross_entropy_3")).get_tensor() + cost_grad.set_dims(cost_shape) + cost_grad.alloc_float(place) + cost_grad.set(numpy.ones(cost_shape).astype("float32"), place) + + +def print_cost(): + cost_data = numpy.array(scope.find_var("cross_entropy_3").get_tensor()) print(cost_data.sum() / len(cost_data)) - cost_grad = scope.find_var(grad_var_name("cross_entropy_1")).get_tensor() - cost_grad.set_dims(cost_data.shape) - cost_grad.alloc_float(place) - cost_grad.set(numpy.ones(cost_data.shape).astype("float32"), place) +def error_rate(predict, label): + predict_var = numpy.array(scope.find_var(predict).get_tensor()).argmax( + axis=1) + label = numpy.array(scope.find_var(label).get_tensor()) + error_num = numpy.sum(predict_var != label) + print(error_num / float(len(label))) images = data_layer(name='pixel', dims=[BATCH_SIZE, 784]) label = data_layer(name='label', dims=[BATCH_SIZE]) -fc = fc_layer(net=forward_network, input=images, size=10, act="softmax") -cost = cross_entropy_layer(net=forward_network, input=fc, label=label) +fc1 = fc_layer(net=forward_network, input=images, size=100, act="sigmoid") +fc2 = fc_layer(net=forward_network, input=fc1, size=100, act="sigmoid") +predict = fc_layer(net=forward_network, input=fc2, size=100, act="softmax") +cost = cross_entropy_layer(net=forward_network, input=predict, label=label) forward_network.complete_add_op(True) backward_net = get_backward_net(forward_network) @@ -192,8 +205,8 @@ reader = paddle.batch( PASS_NUM = 1000 for pass_id in range(PASS_NUM): + batch_id = 0 - print("pass[" + str(pass_id) + "]") for data in reader(): image = numpy.array(map(lambda x: x[0], data)).astype("float32") label = numpy.array(map(lambda x: x[1], data)).astype("int32") @@ -207,3 +220,9 @@ for pass_id in range(PASS_NUM): backward_net.run(scope, dev_ctx) optimize_net.run(scope, dev_ctx) + if batch_id % 100 == 0: + print("pass[" + str(pass_id) + "] batch_id[" + str(batch_id) + "]") + print_cost() + error_rate(predict, "label") + + batch_id = batch_id + 1 From bfcaf880d0eed61291f0483091382131ef6cde88 Mon Sep 17 00:00:00 2001 From: dangqingqing Date: Wed, 23 Aug 2017 18:48:05 +0800 Subject: [PATCH 098/138] Move pybind from package paddle/framework into paddle/pybind. --- paddle/CMakeLists.txt | 1 + paddle/framework/CMakeLists.txt | 20 -------------------- paddle/pybind/CMakeLists.txt | 19 +++++++++++++++++++ paddle/{framework => pybind}/pybind.cc | 18 ++++++++++-------- paddle/{framework => pybind}/tensor_py.h | 11 +++++++---- 5 files changed, 37 insertions(+), 32 deletions(-) create mode 100644 paddle/pybind/CMakeLists.txt rename paddle/{framework => pybind}/pybind.cc (95%) rename paddle/{framework => pybind}/tensor_py.h (92%) diff --git a/paddle/CMakeLists.txt b/paddle/CMakeLists.txt index cf61a243e9..ec866b2907 100644 --- a/paddle/CMakeLists.txt +++ b/paddle/CMakeLists.txt @@ -15,6 +15,7 @@ if(Boost_FOUND) add_subdirectory(platform) add_subdirectory(framework) add_subdirectory(operators) + add_subdirectory(pybind) endif() if(WITH_C_API) diff --git a/paddle/framework/CMakeLists.txt b/paddle/framework/CMakeLists.txt index ad219887d6..c0838d9b75 100644 --- a/paddle/framework/CMakeLists.txt +++ b/paddle/framework/CMakeLists.txt @@ -39,23 +39,3 @@ add_custom_command(TARGET framework_py_proto POST_BUILD cc_library(backward SRCS backward.cc DEPS net_op) cc_test(backward_test SRCS backward_test.cc DEPS backward recurrent_op device_context) - -if(WITH_PYTHON) -cc_library(paddle_pybind SHARED - SRCS pybind.cc - DEPS pybind python backward - sgd_op - gather_op - add_op - mul_op - rowwise_add_op - sigmoid_op - softmax_op - mean_op - cross_entropy_op - recurrent_op - uniform_random_op - gaussian_random_op - fill_zeros_like_op - scale_op) -endif(WITH_PYTHON) diff --git a/paddle/pybind/CMakeLists.txt b/paddle/pybind/CMakeLists.txt new file mode 100644 index 0000000000..10be83efc6 --- /dev/null +++ b/paddle/pybind/CMakeLists.txt @@ -0,0 +1,19 @@ +if(WITH_PYTHON) +cc_library(paddle_pybind SHARED + SRCS pybind.cc + DEPS pybind python backward + sgd_op + gather_op + add_op + mul_op + rowwise_add_op + sigmoid_op + softmax_op + mean_op + cross_entropy_op + recurrent_op + uniform_random_op + gaussian_random_op + fill_zeros_like_op + scale_op) +endif(WITH_PYTHON) diff --git a/paddle/framework/pybind.cc b/paddle/pybind/pybind.cc similarity index 95% rename from paddle/framework/pybind.cc rename to paddle/pybind/pybind.cc index b5ae81ebca..cdf739c3a2 100644 --- a/paddle/framework/pybind.cc +++ b/paddle/pybind/pybind.cc @@ -18,11 +18,11 @@ limitations under the License. */ #include "paddle/framework/backward.h" #include "paddle/framework/op_registry.h" -#include "paddle/framework/tensor_py.h" #include "paddle/operators/net_op.h" #include "paddle/operators/recurrent_op.h" #include "paddle/platform/enforce.h" #include "paddle/platform/place.h" +#include "paddle/pybind/tensor_py.h" #include "paddle/string/to_string.h" #include "pybind11/numpy.h" #include "pybind11/pybind11.h" @@ -134,7 +134,8 @@ All parameter, weight, gradient are variables in Paddle. py::return_value_policy::reference) .def("find_var", &Scope::FindVar, py::return_value_policy::reference) .def(py::init<>()) - .def("new_scope", [](Scope &self) -> Scope * { return &self.NewScope(); }, + .def("new_scope", + [](Scope &self) -> Scope * { return &self.NewScope(); }, py::return_value_policy::reference) .def("drop_kids", &Scope::DropKids); @@ -222,8 +223,10 @@ All parameter, weight, gradient are variables in Paddle. retv->SetType("plain_net"); return retv; }) - .def("append_op", [](operators::NetOp &self, - const OperatorBase &op) { self.AppendOp(op); }) + .def("append_op", + [](operators::NetOp &self, const OperatorBase &op) { + self.AppendOp(op); + }) .def("complete_add_op", &operators::NetOp::CompleteAddOp) .def("complete_add_op", [](std::shared_ptr &self) { self->CompleteAddOp(); @@ -243,10 +246,9 @@ All parameter, weight, gradient are variables in Paddle. auto rnn_op = OpRegistry::CreateOp(desc); return static_cast(rnn_op.release()); }) - .def("set_stepnet", [](operators::RecurrentOp &self, - const operators::NetOp &net) -> void { - self.set_stepnet(net.Clone()); - }); + .def("set_stepnet", + [](operators::RecurrentOp &self, const operators::NetOp &net) + -> void { self.set_stepnet(net.Clone()); }); m.def("unique_integer", UniqueIntegerGenerator); diff --git a/paddle/framework/tensor_py.h b/paddle/pybind/tensor_py.h similarity index 92% rename from paddle/framework/tensor_py.h rename to paddle/pybind/tensor_py.h index 4e1ab77b15..39ba60b4dc 100644 --- a/paddle/framework/tensor_py.h +++ b/paddle/pybind/tensor_py.h @@ -63,8 +63,11 @@ struct CastToPyBufferImpl { } return py::buffer_info( dst_tensor.mutable_data(dst_tensor.holder_->place()), - sizeof(CUR_TYPE), py::format_descriptor::format(), - (size_t)framework::arity(dst_tensor.dims()), dims_outside, strides); + sizeof(CUR_TYPE), + py::format_descriptor::format(), + (size_t)framework::arity(dst_tensor.dims()), + dims_outside, + strides); } else { constexpr bool less = I + 1 < std::tuple_size>::value; return CastToPyBufferImpl()(tensor); @@ -107,8 +110,8 @@ void PyCUDATensorSetFromArray( self.Resize(framework::make_ddim(dims)); auto *dst = self.mutable_data(place); - paddle::platform::GpuMemcpySync(dst, array.data(), sizeof(T) * array.size(), - cudaMemcpyHostToDevice); + paddle::platform::GpuMemcpySync( + dst, array.data(), sizeof(T) * array.size(), cudaMemcpyHostToDevice); } #endif From e3342ff8e79fbe1cacb8fa5a66cb9c69cba1eeb9 Mon Sep 17 00:00:00 2001 From: wanghaoshuang Date: Wed, 23 Aug 2017 19:30:46 +0800 Subject: [PATCH 099/138] Fix android build error. --- paddle/cuda/include/stub/hl_cuda_cudnn_stub.h | 11 ++++++++--- paddle/cuda/src/hl_cuda_cudnn.cc | 3 ++- paddle/gserver/tests/test_LayerGrad.cpp | 6 ++++-- python/paddle/trainer/config_parser.py | 6 +++--- python/paddle/trainer_config_helpers/layers.py | 7 +++---- 5 files changed, 20 insertions(+), 13 deletions(-) diff --git a/paddle/cuda/include/stub/hl_cuda_cudnn_stub.h b/paddle/cuda/include/stub/hl_cuda_cudnn_stub.h index abd0d6b099..3afcc6fa85 100644 --- a/paddle/cuda/include/stub/hl_cuda_cudnn_stub.h +++ b/paddle/cuda/include/stub/hl_cuda_cudnn_stub.h @@ -78,7 +78,9 @@ inline void hl_create_convolution_descriptor(hl_convolution_descriptor* conv, int padding_height, int padding_width, int stride_height, - int stride_width) {} + int stride_width, + int dilation_h, + int dilation_w) {} inline void hl_reset_convolution_descriptor(hl_convolution_descriptor conv, hl_tensor_descriptor image, @@ -86,7 +88,9 @@ inline void hl_reset_convolution_descriptor(hl_convolution_descriptor conv, int padding_height, int padding_width, int stride_height, - int stride_width) {} + int stride_width, + int dilation_h, + int dilation_w) {} inline void hl_destroy_convolution_descriptor(hl_convolution_descriptor conv) {} @@ -99,7 +103,8 @@ inline void hl_conv_workspace(hl_tensor_descriptor input, int* convBwdDataAlgo, size_t* bwdDataLimitBytes, int* convBwdFilterAlgo, - size_t* bwdFilterLimitBytes) {} + size_t* bwdFilterLimitBytes, + bool useDilation) {} inline void hl_convolution_forward(hl_tensor_descriptor input, real* input_data, diff --git a/paddle/cuda/src/hl_cuda_cudnn.cc b/paddle/cuda/src/hl_cuda_cudnn.cc index f55fa523e1..f38ef69255 100644 --- a/paddle/cuda/src/hl_cuda_cudnn.cc +++ b/paddle/cuda/src/hl_cuda_cudnn.cc @@ -640,7 +640,8 @@ void hl_create_convolution_descriptor(hl_convolution_descriptor* conv, #else if (dilation_h > 1 || dilation_w > 1) { LOG(FATAL) - << "Current cudnn version does't support for dilation convolution."; + << "Current cuDNN version does't support for dilation convolution. " + << "The dilation convolution requires cuDNN >= v6.0."; } CHECK_CUDNN(dynload::cudnnSetConvolution2dDescriptor(hl_conv->desc, diff --git a/paddle/gserver/tests/test_LayerGrad.cpp b/paddle/gserver/tests/test_LayerGrad.cpp index 9348c47bd4..9946f76664 100644 --- a/paddle/gserver/tests/test_LayerGrad.cpp +++ b/paddle/gserver/tests/test_LayerGrad.cpp @@ -12,7 +12,9 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ +#ifndef PADDLE_ONLY_CPU #include +#endif #include #include #include @@ -262,8 +264,8 @@ TEST(Projection, conv) { testProjectionConv(1, false); testProjectionConv(3, false); /// test ConvTransProjection - /// testProjectionConv(1, true); - /// testProjectionConv(3, true); + testProjectionConv(1, true); + testProjectionConv(3, true); } #endif diff --git a/python/paddle/trainer/config_parser.py b/python/paddle/trainer/config_parser.py index 33a20afb18..ddfd615d84 100644 --- a/python/paddle/trainer/config_parser.py +++ b/python/paddle/trainer/config_parser.py @@ -862,7 +862,6 @@ class Conv(Cfg): filter_size, channels, padding=None, - dilation=None, stride=None, groups=None, filter_channels=None, @@ -871,8 +870,9 @@ class Conv(Cfg): caffe_mode=True, filter_size_y=None, padding_y=None, - dilation_y=None, - stride_y=None): + stride_y=None, + dilation=None, + dilation_y=None): self.add_keys(locals()) if filter_size_y is None: self.filter_size_y = filter_size diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py index 74b88cd4f8..9876798558 100755 --- a/python/paddle/trainer_config_helpers/layers.py +++ b/python/paddle/trainer_config_helpers/layers.py @@ -2340,7 +2340,7 @@ def img_conv_layer(input, groups=1, stride=1, padding=0, - dilation=0, + dilation=1, bias_attr=None, param_attr=None, shared_biases=True, @@ -2472,9 +2472,6 @@ def img_conv_layer(input, else: dilation_y = dilation - if dilation > 1 or dilation_y > 1: - assert layer_type in ["cudnn_conv", "cudnn_convt"] - if param_attr.attr.get('initial_smart'): # special initial for conv layers. init_w = (2.0 / (filter_size**2 * num_channels))**0.5 @@ -2484,6 +2481,8 @@ def img_conv_layer(input, param_attr.attr["initial_smart"] = False if layer_type: + if dilation > 1 or dilation_y > 1: + assert layer_type in ["cudnn_conv", "cudnn_convt"] if trans: assert layer_type in ["exconvt", "cudnn_convt"] else: From 76677f25774a84d9ced011be02e62ae15b03506c Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Wed, 23 Aug 2017 09:12:34 -0700 Subject: [PATCH 100/138] add test --- python/paddle/v2/framework/tests/mnist.py | 36 ++++++++++++++++++----- 1 file changed, 28 insertions(+), 8 deletions(-) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index ededf767bc..e47de2436f 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -52,7 +52,7 @@ def grad_var_name(var_name): return var_name + "@GRAD" -def sgd_optimizer(net, param_name, learning_rate=0.01): +def sgd_optimizer(net, param_name, learning_rate=0.005): grad_name = grad_var_name(param_name) optimize_op = Operator( "sgd", @@ -166,9 +166,9 @@ def set_cost(): cost_grad.set(numpy.ones(cost_shape).astype("float32"), place) -def print_cost(): +def mean_cost(): cost_data = numpy.array(scope.find_var("cross_entropy_3").get_tensor()) - print(cost_data.sum() / len(cost_data)) + return cost_data.sum() / len(cost_data) def error_rate(predict, label): @@ -176,7 +176,7 @@ def error_rate(predict, label): axis=1) label = numpy.array(scope.find_var(label).get_tensor()) error_num = numpy.sum(predict_var != label) - print(error_num / float(len(label))) + return error_num / float(len(label)) images = data_layer(name='pixel', dims=[BATCH_SIZE, 784]) @@ -198,16 +198,35 @@ print_inputs_outputs(forward_network) print_inputs_outputs(backward_net) print_inputs_outputs(optimize_net) -reader = paddle.batch( +train_reader = paddle.batch( paddle.reader.shuffle( paddle.dataset.mnist.train(), buf_size=8192), batch_size=BATCH_SIZE) + +def test(): + test_reader = paddle.batch(paddle.dataset.mnist.test(), batch_size=128) + cost = [] + error = [] + for data in test_reader(): + image = numpy.array(map(lambda x: x[0], data)).astype("float32") + label = numpy.array(map(lambda x: x[1], data)).astype("int32") + feed_data("pixel", image) + feed_data("label", label) + + forward_network.infer_shape(scope) + forward_network.run(scope, dev_ctx) + cost.append(mean_cost()) + error.append(error_rate(predict, "label")) + print("cost=" + str(sum(cost) / float(len(cost))) + " error_rate=" + str( + sum(error) / float(len(error)))) + + PASS_NUM = 1000 for pass_id in range(PASS_NUM): batch_id = 0 - for data in reader(): + for data in train_reader(): image = numpy.array(map(lambda x: x[0], data)).astype("float32") label = numpy.array(map(lambda x: x[1], data)).astype("int32") feed_data("pixel", image) @@ -222,7 +241,8 @@ for pass_id in range(PASS_NUM): optimize_net.run(scope, dev_ctx) if batch_id % 100 == 0: print("pass[" + str(pass_id) + "] batch_id[" + str(batch_id) + "]") - print_cost() - error_rate(predict, "label") + test() + # print(mean_cost()) + # print(error_rate(predict, "label")) batch_id = batch_id + 1 From cf515e4a72f4b02fbbbfdbd79c3b66b1be694e7b Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Wed, 23 Aug 2017 09:39:47 -0700 Subject: [PATCH 101/138] optimize code and name --- python/paddle/v2/framework/tests/mnist.py | 56 +++++++++++------------ 1 file changed, 27 insertions(+), 29 deletions(-) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index e47de2436f..886e99610d 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -134,7 +134,7 @@ def cross_entropy_layer(net, input, label): return cost_name -def get_backward_net(forward_net): +def create_backward_net(forward_net): net = core.Operator.backward(forward_net, set()) for input in net.inputs()["all"]: var = scope.new_var(input) @@ -145,29 +145,29 @@ def get_backward_net(forward_net): return net -def print_inputs_outputs(op): +def debug_print_op(op): print("===============" + op.type() + "==============") print("***inputs:***") for input in op.inputs()["all"]: print input, scope.find_var(input).get_tensor().get_dims() - print("***outputs:***") + print("\n***outputs:***") for output in op.outputs()["all"]: print output, scope.find_var(output).get_tensor().get_dims() print("") print("") -def set_cost(): - cost_shape = numpy.array(scope.find_var("cross_entropy_3").get_tensor( - )).shape - cost_grad = scope.find_var(grad_var_name("cross_entropy_3")).get_tensor() +def set_cost(cost): + cost_shape = numpy.array(scope.find_var(cost).get_tensor()).shape + cost_grad = \ + scope.find_var(grad_var_name(cost)).get_tensor() cost_grad.set_dims(cost_shape) cost_grad.alloc_float(place) cost_grad.set(numpy.ones(cost_shape).astype("float32"), place) -def mean_cost(): - cost_data = numpy.array(scope.find_var("cross_entropy_3").get_tensor()) +def mean_cost(cost): + cost_data = numpy.array(scope.find_var(cost).get_tensor()) return cost_data.sum() / len(cost_data) @@ -180,23 +180,23 @@ def error_rate(predict, label): images = data_layer(name='pixel', dims=[BATCH_SIZE, 784]) -label = data_layer(name='label', dims=[BATCH_SIZE]) +labels = data_layer(name='label', dims=[BATCH_SIZE]) fc1 = fc_layer(net=forward_network, input=images, size=100, act="sigmoid") fc2 = fc_layer(net=forward_network, input=fc1, size=100, act="sigmoid") predict = fc_layer(net=forward_network, input=fc2, size=100, act="softmax") -cost = cross_entropy_layer(net=forward_network, input=predict, label=label) +cost = cross_entropy_layer(net=forward_network, input=predict, label=labels) forward_network.complete_add_op(True) -backward_net = get_backward_net(forward_network) +backward_net = create_backward_net(forward_network) optimize_net.complete_add_op(True) print(forward_network) print(backward_net) print(optimize_net) -print_inputs_outputs(forward_network) -print_inputs_outputs(backward_net) -print_inputs_outputs(optimize_net) +debug_print_op(forward_network) +debug_print_op(backward_net) +debug_print_op(optimize_net) train_reader = paddle.batch( paddle.reader.shuffle( @@ -204,19 +204,19 @@ train_reader = paddle.batch( batch_size=BATCH_SIZE) -def test(): +def test(cost_name): test_reader = paddle.batch(paddle.dataset.mnist.test(), batch_size=128) cost = [] error = [] for data in test_reader(): - image = numpy.array(map(lambda x: x[0], data)).astype("float32") - label = numpy.array(map(lambda x: x[1], data)).astype("int32") - feed_data("pixel", image) - feed_data("label", label) + image_data = numpy.array(map(lambda x: x[0], data)).astype("float32") + label_data = numpy.array(map(lambda x: x[1], data)).astype("int32") + feed_data(images, image_data) + feed_data(labels, label_data) forward_network.infer_shape(scope) forward_network.run(scope, dev_ctx) - cost.append(mean_cost()) + cost.append(mean_cost(cost_name)) error.append(error_rate(predict, "label")) print("cost=" + str(sum(cost) / float(len(cost))) + " error_rate=" + str( sum(error) / float(len(error)))) @@ -227,22 +227,20 @@ for pass_id in range(PASS_NUM): batch_id = 0 for data in train_reader(): - image = numpy.array(map(lambda x: x[0], data)).astype("float32") - label = numpy.array(map(lambda x: x[1], data)).astype("int32") - feed_data("pixel", image) - feed_data("label", label) + image_data = numpy.array(map(lambda x: x[0], data)).astype("float32") + label_data = numpy.array(map(lambda x: x[1], data)).astype("int32") + feed_data(images, image_data) + feed_data(labels, label_data) forward_network.infer_shape(scope) forward_network.run(scope, dev_ctx) - set_cost() + set_cost(cost) backward_net.infer_shape(scope) backward_net.run(scope, dev_ctx) optimize_net.run(scope, dev_ctx) if batch_id % 100 == 0: print("pass[" + str(pass_id) + "] batch_id[" + str(batch_id) + "]") - test() - # print(mean_cost()) - # print(error_rate(predict, "label")) + test(cost) batch_id = batch_id + 1 From 9db4ad6130d79d72fa150e534b5b54fa723c3240 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Wed, 23 Aug 2017 09:42:58 -0700 Subject: [PATCH 102/138] reduce pass num to 1 --- python/paddle/v2/framework/tests/mnist.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index 886e99610d..eefd5709a3 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -222,7 +222,7 @@ def test(cost_name): sum(error) / float(len(error)))) -PASS_NUM = 1000 +PASS_NUM = 1 for pass_id in range(PASS_NUM): batch_id = 0 From 37cd8165b3089c8e4a6ce743f5e0ee8c029ba46b Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Wed, 23 Aug 2017 10:56:56 -0700 Subject: [PATCH 103/138] change 128 to BATCH_SIZE --- python/paddle/v2/framework/tests/mnist.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index eefd5709a3..e878bfa4e9 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -205,7 +205,8 @@ train_reader = paddle.batch( def test(cost_name): - test_reader = paddle.batch(paddle.dataset.mnist.test(), batch_size=128) + test_reader = paddle.batch( + paddle.dataset.mnist.test(), batch_size=BATCH_SIZE) cost = [] error = [] for data in test_reader(): From 72d29186bb426efc4eb78d9d6b6e605c7e2ce56c Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Wed, 23 Aug 2017 11:07:15 -0700 Subject: [PATCH 104/138] reduce some compile warning --- paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp | 4 ++-- paddle/operators/net_op_test.cc | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp b/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp index 1829f72a87..d00d408ab8 100644 --- a/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp +++ b/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp @@ -1399,8 +1399,8 @@ void RecurrentGradientMachine::createDataOutlinkCopySizeInfo( getBeamSize() > 1 ? finalPaths_.size() : finalPaths_[0].size()); int* starts = inputSeqStartPos->getMutableData(false); int seqId = 0; - for (int i = 0; i < finalPaths_.size(); ++i) { - for (int j = 0; j < finalPaths_[i].size(); ++j) { + for (size_t i = 0; i < finalPaths_.size(); ++i) { + for (size_t j = 0; j < finalPaths_[i].size(); ++j) { copySize[seqId] = getBeamSize() > 1 ? starts[i + 1] - starts[i] : starts[j + 1] - starts[j]; batchMachineStartPos_[seqId + 1] = diff --git a/paddle/operators/net_op_test.cc b/paddle/operators/net_op_test.cc index 99019754a9..f2e98ee7a1 100644 --- a/paddle/operators/net_op_test.cc +++ b/paddle/operators/net_op_test.cc @@ -79,7 +79,7 @@ TEST(NetOp, Clone) { ASSERT_NE(new_net_op, nullptr); ASSERT_TRUE(new_net_op->IsNetOp()); auto* new_net = static_cast(new_net_op.get()); - ASSERT_EQ(2, new_net->ops_.size()); + ASSERT_EQ(2UL, new_net->ops_.size()); ASSERT_EQ(new_net->ops_[0]->Type(), "empty"); ASSERT_EQ(new_net->ops_[1]->Type(), "empty2"); } From 3b6069b7f511e41a00551cc3141385d9eb464f51 Mon Sep 17 00:00:00 2001 From: haonanyu Date: Wed, 23 Aug 2017 12:16:36 -0700 Subject: [PATCH 105/138] fix ids reverse order in fillGenOutputs --- paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp b/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp index 1829f72a87..56c3951cfd 100644 --- a/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp +++ b/paddle/gserver/gradientmachines/RecurrentGradientMachine.cpp @@ -1344,7 +1344,7 @@ void RecurrentGradientMachine::fillGenOutputs() { CHECK(!finalPaths_[i].empty()); Path& path = finalPaths_[i][0]; generator_.ids.insert( - generator_.ids.begin(), path.ids.begin(), path.ids.end()); + generator_.ids.end(), path.ids.begin(), path.ids.end()); starts[i + 1] = starts[i] + path.ids.size(); } } From da7a1f2f6c355b1bcdc0bd88e644f027d70f75d8 Mon Sep 17 00:00:00 2001 From: Helin Wang Date: Wed, 23 Aug 2017 21:30:08 +0000 Subject: [PATCH 106/138] master client: retry connecting to etcd --- go/master/client.go | 28 +++++++++++++++++++++------- 1 file changed, 21 insertions(+), 7 deletions(-) diff --git a/go/master/client.go b/go/master/client.go index 62801b9b7f..9344c6f0ab 100644 --- a/go/master/client.go +++ b/go/master/client.go @@ -60,13 +60,30 @@ func WithAddr(addr string) func(c *Client) error { } } +func retry(f func() error, dur time.Duration, count int) error { + err := f() + if err != nil { + if count > 0 { + return retry(f, dur, count-1) + } + return err + } + return nil +} + // WithEtcd sets the client to use etcd for master discovery. func WithEtcd(endpoints []string, timeout time.Duration) func(*Client) error { return func(c *Client) error { - cli, err := clientv3.New(clientv3.Config{ - Endpoints: endpoints, - DialTimeout: timeout, - }) + var cli *clientv3.Client + f := func() error { + var err error + cli, err = clientv3.New(clientv3.Config{ + Endpoints: endpoints, + DialTimeout: timeout, + }) + return err + } + err := retry(f, time.Second, 10) if err != nil { return err } @@ -101,9 +118,6 @@ func NewClient(opts ...func(*Client) error) (*Client, error) { } } c.ch = make(chan record, c.bufSize) - // FIXME: connection is created asyncrosly in monitorMaster go routine, - // ensure the connection is ready for use before calling c.addClient. - time.Sleep(time.Second) return c, nil } From 5270585e107b16dc527ada329dddf6fc44714a35 Mon Sep 17 00:00:00 2001 From: Helin Wang Date: Wed, 23 Aug 2017 21:38:43 +0000 Subject: [PATCH 107/138] fix according to comment --- go/master/client.go | 1 + 1 file changed, 1 insertion(+) diff --git a/go/master/client.go b/go/master/client.go index 9344c6f0ab..199690d488 100644 --- a/go/master/client.go +++ b/go/master/client.go @@ -64,6 +64,7 @@ func retry(f func() error, dur time.Duration, count int) error { err := f() if err != nil { if count > 0 { + time.Sleep(dur) return retry(f, dur, count-1) } return err From 05176bd1bb5af94bfbabbb524ed9e65448134e39 Mon Sep 17 00:00:00 2001 From: Helin Wang Date: Thu, 24 Aug 2017 01:23:27 +0000 Subject: [PATCH 108/138] master server will wait etcd forever --- go/master/client.go | 23 ++++++++--------------- 1 file changed, 8 insertions(+), 15 deletions(-) diff --git a/go/master/client.go b/go/master/client.go index 199690d488..f04cf50ce3 100644 --- a/go/master/client.go +++ b/go/master/client.go @@ -60,18 +60,6 @@ func WithAddr(addr string) func(c *Client) error { } } -func retry(f func() error, dur time.Duration, count int) error { - err := f() - if err != nil { - if count > 0 { - time.Sleep(dur) - return retry(f, dur, count-1) - } - return err - } - return nil -} - // WithEtcd sets the client to use etcd for master discovery. func WithEtcd(endpoints []string, timeout time.Duration) func(*Client) error { return func(c *Client) error { @@ -84,9 +72,14 @@ func WithEtcd(endpoints []string, timeout time.Duration) func(*Client) error { }) return err } - err := retry(f, time.Second, 10) - if err != nil { - return err + for { + err := f() + if err != nil { + log.Warningln(err) + } else { + break + } + time.Sleep(time.Second) } ch := make(chan string, 1) From 161a15f055c2cbe1937522a7a11dbdeb31f1a774 Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Thu, 24 Aug 2017 03:11:54 +0000 Subject: [PATCH 109/138] gradient check --- python/paddle/v2/framework/tests/gradient_checker.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/python/paddle/v2/framework/tests/gradient_checker.py b/python/paddle/v2/framework/tests/gradient_checker.py index c22c6f8831..d7809e52fb 100644 --- a/python/paddle/v2/framework/tests/gradient_checker.py +++ b/python/paddle/v2/framework/tests/gradient_checker.py @@ -86,6 +86,9 @@ def get_numeric_gradient(op, # we only compute gradient of one element each time. # we use a for loop to compute the gradient of every element. for i in xrange(tensor_size): + for var_name in input_values: + tensor_ = local_scope.find_var(var_name).get_tensor() + tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace()) # get one input element throw it's index i. origin = tensor_to_check.get_float_element(i) @@ -95,6 +98,9 @@ def get_numeric_gradient(op, y_pos = get_output() # plus delta to this element, run op and get the sum of the result tensor. + for var_name in input_values: + tensor_ = local_scope.find_var(var_name).get_tensor() + tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace()) x_neg = origin - delta tensor_to_check.set_float_element(i, x_neg) y_neg = get_output() From 0e300f9bf04ba459dbef93af9537f847cebbcd27 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Wed, 23 Aug 2017 20:14:54 -0700 Subject: [PATCH 110/138] use init_net and random_op to initialize parameter --- python/paddle/v2/framework/tests/mnist.py | 54 +++++++++++------------ 1 file changed, 27 insertions(+), 27 deletions(-) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index e878bfa4e9..0c27ce3e35 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -9,11 +9,8 @@ scope = core.Scope() place = core.CPUPlace() dev_ctx = core.DeviceContext.create(place) -# init_net = core.Net.create() -forward_network = core.Net.create() - -# should be init after forward_op is constructed -# backward_net = core.Operator.backward(forward_net, set()) +init_net = core.Net.create() +forward_net = core.Net.create() backward_net = None optimize_net = core.Net.create() @@ -64,13 +61,12 @@ def sgd_optimizer(net, param_name, learning_rate=0.005): # should use operator and add these to the init_network -def init_param(param_name, dims): - var = scope.new_var(param_name) - tensor = var.get_tensor() - tensor.set_dims(dims) - data = numpy.random.uniform( - low=-0.5, high=0.5, size=tensor.shape()).astype("float32") - tensor.set(data, place) +def init_param(net, param_name, dims): + scope.new_var(param_name) + op = Operator( + "uniform_random", Out=param_name, dims=dims, min=-0.5, max=0.5, seed=10) + op.infer_shape(scope) + net.append_op(op) # fc_layer @@ -96,7 +92,7 @@ def fc_layer(net, input, size, act="softmax", bias=True, param=None, name=None): input_dims = scope.find_var(input).get_tensor().get_dims() w_name = param or name + ".w" - init_param(param_name=w_name, dims=[input_dims[1], size]) + init_param(net=init_net, param_name=w_name, dims=[input_dims[1], size]) sgd_optimizer(net=optimize_net, param_name=w_name, learning_rate=0.01) pre_activation = name + ".mul.out" @@ -107,7 +103,7 @@ def fc_layer(net, input, size, act="softmax", bias=True, param=None, name=None): # create bias variable if needed if bias: bias_name = name + ".b" - init_param(param_name=bias_name, dims=[size]) + init_param(net=init_net, param_name=bias_name, dims=[size]) sgd_optimizer( net=optimize_net, param_name=bias_name, learning_rate=0.001) bias_out = name + ".rowwise_add.out" @@ -181,20 +177,22 @@ def error_rate(predict, label): images = data_layer(name='pixel', dims=[BATCH_SIZE, 784]) labels = data_layer(name='label', dims=[BATCH_SIZE]) -fc1 = fc_layer(net=forward_network, input=images, size=100, act="sigmoid") -fc2 = fc_layer(net=forward_network, input=fc1, size=100, act="sigmoid") -predict = fc_layer(net=forward_network, input=fc2, size=100, act="softmax") -cost = cross_entropy_layer(net=forward_network, input=predict, label=labels) - -forward_network.complete_add_op(True) -backward_net = create_backward_net(forward_network) +fc1 = fc_layer(net=forward_net, input=images, size=100, act="sigmoid") +fc2 = fc_layer(net=forward_net, input=fc1, size=100, act="sigmoid") +predict = fc_layer(net=forward_net, input=fc2, size=100, act="softmax") +cost = cross_entropy_layer(net=forward_net, input=predict, label=labels) + +init_net.complete_add_op(True) +forward_net.complete_add_op(True) +backward_net = create_backward_net(forward_net) optimize_net.complete_add_op(True) -print(forward_network) +print(init_net) +print(forward_net) print(backward_net) print(optimize_net) -debug_print_op(forward_network) +debug_print_op(forward_net) debug_print_op(backward_net) debug_print_op(optimize_net) @@ -215,8 +213,8 @@ def test(cost_name): feed_data(images, image_data) feed_data(labels, label_data) - forward_network.infer_shape(scope) - forward_network.run(scope, dev_ctx) + forward_net.infer_shape(scope) + forward_net.run(scope, dev_ctx) cost.append(mean_cost(cost_name)) error.append(error_rate(predict, "label")) print("cost=" + str(sum(cost) / float(len(cost))) + " error_rate=" + str( @@ -224,6 +222,8 @@ def test(cost_name): PASS_NUM = 1 + +init_net.run(scope, dev_ctx) for pass_id in range(PASS_NUM): batch_id = 0 @@ -233,8 +233,8 @@ for pass_id in range(PASS_NUM): feed_data(images, image_data) feed_data(labels, label_data) - forward_network.infer_shape(scope) - forward_network.run(scope, dev_ctx) + forward_net.infer_shape(scope) + forward_net.run(scope, dev_ctx) set_cost(cost) backward_net.infer_shape(scope) backward_net.run(scope, dev_ctx) From 0ee18a86d18b4d4506c63e13b2953c9153c27f8d Mon Sep 17 00:00:00 2001 From: wanghaoshuang Date: Thu, 24 Aug 2017 11:50:35 +0800 Subject: [PATCH 111/138] Fix doc. --- python/paddle/trainer_config_helpers/layers.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py index b3568cc257..f323b017c0 100755 --- a/python/paddle/trainer_config_helpers/layers.py +++ b/python/paddle/trainer_config_helpers/layers.py @@ -2418,8 +2418,8 @@ def img_conv_layer(input, :param dilation: The x dimension of the dilation. Or input a tuple for two image dimension :type dilation: int|tuple|list - :param padding_y: The y dimension of the dilation. - :type padding_y: int + :param dilation_y: The y dimension of the dilation. + :type dilation_y: int :param bias_attr: Convolution bias attribute. None means default bias. False means no bias. :type bias_attr: ParameterAttribute|False From 12864f142073b4a280120e4d9b3abe4e2483ca32 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Wed, 23 Aug 2017 22:51:35 -0700 Subject: [PATCH 112/138] register rowwise add gpu kernel --- paddle/operators/rowwise_add_op.cu | 3 +++ 1 file changed, 3 insertions(+) diff --git a/paddle/operators/rowwise_add_op.cu b/paddle/operators/rowwise_add_op.cu index cbc61ad3e1..4a57f64c89 100644 --- a/paddle/operators/rowwise_add_op.cu +++ b/paddle/operators/rowwise_add_op.cu @@ -18,3 +18,6 @@ namespace ops = paddle::operators; REGISTER_OP_GPU_KERNEL( rowwise_add, ops::RowwiseAddKernel); +REGISTER_OP_GPU_KERNEL( + rowwise_add_grad, + ops::RowwiseAddGradKernel); From 3648165b63bd5331d1809cba896176e4af0a9ff2 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Wed, 23 Aug 2017 23:00:45 -0700 Subject: [PATCH 113/138] add gpu support --- python/paddle/v2/framework/tests/mnist.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index 0c27ce3e35..d9941023fe 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -7,6 +7,8 @@ BATCH_SIZE = 100 scope = core.Scope() place = core.CPUPlace() +# if you want to test GPU training, you can use gpu place +# place = core.GPUPlace(0) dev_ctx = core.DeviceContext.create(place) init_net = core.Net.create() From 625b15355a16fa42476e7dbd166b77e092dcb97f Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Wed, 23 Aug 2017 23:56:55 -0700 Subject: [PATCH 114/138] optimize code --- python/paddle/v2/framework/tests/mnist.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index d9941023fe..9a0b109850 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -17,14 +17,14 @@ backward_net = None optimize_net = core.Net.create() -def atom_id(): +def atomic_id(): id = 0 while True: yield id id += 1 -uniq_id = atom_id().next +uniq_id = atomic_id().next def data_layer(name, dims): @@ -164,7 +164,7 @@ def set_cost(cost): cost_grad.set(numpy.ones(cost_shape).astype("float32"), place) -def mean_cost(cost): +def get_cost_mean(cost): cost_data = numpy.array(scope.find_var(cost).get_tensor()) return cost_data.sum() / len(cost_data) @@ -217,7 +217,7 @@ def test(cost_name): forward_net.infer_shape(scope) forward_net.run(scope, dev_ctx) - cost.append(mean_cost(cost_name)) + cost.append(get_cost_mean(cost_name)) error.append(error_rate(predict, "label")) print("cost=" + str(sum(cost) / float(len(cost))) + " error_rate=" + str( sum(error) / float(len(error)))) From 692259e071494d08f50cc3b1a4e34326249bc132 Mon Sep 17 00:00:00 2001 From: hedaoyuan Date: Thu, 24 Aug 2017 23:42:32 +0800 Subject: [PATCH 115/138] Fix pre-commit-config.yaml --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index a772125df6..83fe9af768 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -22,7 +22,7 @@ - id: clang-format-with-version-check name: clang-format description: Format files with ClangFormat. - entry: ./.clang_format.hook -i + entry: bash ./.clang_format.hook -i language: system files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|proto)$ - repo: https://github.com/PaddlePaddle/pre-commit-golang From a1ce705517fca1551029541e17cb0ac3ddb65677 Mon Sep 17 00:00:00 2001 From: Xi Chen Date: Thu, 24 Aug 2017 10:35:50 -0700 Subject: [PATCH 116/138] update etcd graph for design doc --- .../cluster_train/src/paddle-etcd.graffle | Bin 5069 -> 5765 bytes doc/design/cluster_train/src/paddle-etcd.png | Bin 56296 -> 57495 bytes 2 files changed, 0 insertions(+), 0 deletions(-) diff --git a/doc/design/cluster_train/src/paddle-etcd.graffle b/doc/design/cluster_train/src/paddle-etcd.graffle index 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Date: Thu, 24 Aug 2017 02:58:41 +0000 Subject: [PATCH 117/138] scatter check in --- paddle/operators/CMakeLists.txt | 1 + paddle/operators/scatter_op.cc | 76 +++++++++++++++++++ paddle/operators/scatter_op.cu | 20 +++++ paddle/operators/scatter_op.h | 60 +++++++++++++++ paddle/pybind/CMakeLists.txt | 1 + paddle/pybind/pybind.cc | 1 + .../paddle/v2/framework/tests/CMakeLists.txt | 1 + .../v2/framework/tests/test_gather_op.py | 3 - .../v2/framework/tests/test_scatter_op.py | 38 ++++++++++ 9 files changed, 198 insertions(+), 3 deletions(-) create mode 100644 paddle/operators/scatter_op.cc create mode 100644 paddle/operators/scatter_op.cu create mode 100644 paddle/operators/scatter_op.h create mode 100644 python/paddle/v2/framework/tests/test_scatter_op.py diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index f466dbc79a..f0fd12f1b5 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -47,6 +47,7 @@ cc_test(gather_test SRCS gather_test.cc DEPS tensor) op_library(gather_op SRCS gather_op.cc gather_op.cu) cc_test(scatter_test SRCS scatter_test.cc DEPS tensor) +op_library(scatter_op SRCS scatter_op.cc scatter_op.cu) cc_library(net_op SRCS net_op.cc DEPS op_registry) cc_test(net_op_test SRCS net_op_test.cc DEPS net_op) diff --git a/paddle/operators/scatter_op.cc b/paddle/operators/scatter_op.cc new file mode 100644 index 0000000000..cf01ef6279 --- /dev/null +++ b/paddle/operators/scatter_op.cc @@ -0,0 +1,76 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#include "paddle/operators/scatter_op.h" +#include "paddle/framework/ddim.h" + +namespace paddle { +namespace operators { + +class ScatterOp : public framework::OperatorWithKernel { + public: + using framework::OperatorWithKernel::OperatorWithKernel; + + protected: + void InferShape(const framework::InferShapeContext &ctx) const override { + framework::DDim output_dims(ctx.Input("Ref")->dims()); + ctx.Output("Out")->Resize(output_dims); + } +}; + +class ScatterGradOp : public framework::OperatorWithKernel { + public: + using framework::OperatorWithKernel::OperatorWithKernel; + + protected: + void InferShape(const framework::InferShapeContext &ctx) const override { + auto Updates_grad = ctx.Output(framework::GradVarName("Updates")); + auto Updates = ctx.Input("Updates"); + auto Ref_grad = ctx.Output(framework::GradVarName("Ref")); + auto Ref = ctx.Input("Ref"); + + Ref_grad->Resize(Ref->dims()); + Updates_grad->Resize(Updates->dims()); + } +}; + +class ScatterOpMaker : public framework::OpProtoAndCheckerMaker { + public: + ScatterOpMaker(framework::OpProto *proto, + framework::OpAttrChecker *op_checker) + : OpProtoAndCheckerMaker(proto, op_checker) { + AddInput("Ref", "The source input of scatter op"); + AddInput("Index", + "The index input of scatter op where Ref will be updated"); + AddInput("Updates", "The updated value of updates op"); + AddOutput("Out", "The output of add op"); + AddComment(R"DOC( +Scatter Operator by selecting from the first axis, + +Out = Ref +Out[Index] = Ref[Index] + Updates +)DOC"); + } +}; +} // namespace operators +} // namespace paddle + +namespace ops = paddle::operators; +REGISTER_OP(scatter, ops::ScatterOp, ops::ScatterOpMaker, scatter_grad, + ops::ScatterGradOp); +REGISTER_OP_CPU_KERNEL(scatter, + ops::ScatterOpKernel); +REGISTER_OP_CPU_KERNEL( + scatter_grad, + ops::ScatterGradientOpKernel); diff --git a/paddle/operators/scatter_op.cu b/paddle/operators/scatter_op.cu new file mode 100644 index 0000000000..e6a6fa57d9 --- /dev/null +++ b/paddle/operators/scatter_op.cu @@ -0,0 +1,20 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ + +#define EIGEN_USE_GPU +#include "paddle/operators/scatter_op.h" + +namespace ops = paddle::operators; +REGISTER_OP_GPU_KERNEL(scatter, + ops::ScatterOpKernel); diff --git a/paddle/operators/scatter_op.h b/paddle/operators/scatter_op.h new file mode 100644 index 0000000000..c2db3ae37c --- /dev/null +++ b/paddle/operators/scatter_op.h @@ -0,0 +1,60 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ + +#pragma once +#include "gather.h" +#include "paddle/framework/eigen.h" +#include "paddle/framework/op_registry.h" +#include "scatter.h" + +namespace paddle { +namespace operators { + +using Tensor = framework::Tensor; + +template +class ScatterOpKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext &ctx) const override { + auto *Ref = ctx.Input("Ref"); + auto *Index = ctx.Input("Index"); + auto *Updates = ctx.Input("Updates"); + auto *Out = ctx.Output("Out"); + + // In place output: Out = Ref, Out[Index] += Updates + Out->ShareDataWith(*Ref); + // Apply ScatterUpdate: Out[index] += Updates[:] + ScatterUpdate(ctx.GetPlace(), Updates, Index, Out); + } +}; + +template +class ScatterGradientOpKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext &ctx) const override { + auto *dRef = ctx.Output(framework::GradVarName("Ref")); + auto *dUpdates = ctx.Output(framework::GradVarName("Updates")); + auto *Index = ctx.Input("Index"); + auto *dO = ctx.Input(framework::GradVarName("Out")); + + // In place gradient: dRef = dO + dRef->ShareDataWith(*dO); + dUpdates->mutable_data(ctx.GetPlace()); + // Gradient by Gather: dUpdates += dO[Index] + Gather(ctx.GetPlace(), dO, Index, dUpdates); + } +}; + +} // namespace operators +} // namespace paddle diff --git a/paddle/pybind/CMakeLists.txt b/paddle/pybind/CMakeLists.txt index abb9c248ee..37e186a408 100644 --- a/paddle/pybind/CMakeLists.txt +++ b/paddle/pybind/CMakeLists.txt @@ -4,6 +4,7 @@ cc_library(paddle_pybind SHARED DEPS pybind python backward sgd_op gather_op + scatter_op add_op mul_op rowwise_add_op diff --git a/paddle/pybind/pybind.cc b/paddle/pybind/pybind.cc index 8fa8be2cef..3bc150ccb7 100644 --- a/paddle/pybind/pybind.cc +++ b/paddle/pybind/pybind.cc @@ -47,6 +47,7 @@ USE_OP(scale); USE_OP_ITSELF(identity); USE_OP(minus); USE_CPU_ONLY_OP(gather); +USE_CPU_ONLY_OP(scatter); namespace paddle { namespace framework { diff --git a/python/paddle/v2/framework/tests/CMakeLists.txt b/python/paddle/v2/framework/tests/CMakeLists.txt index fb4686889a..661ebd8964 100644 --- a/python/paddle/v2/framework/tests/CMakeLists.txt +++ b/python/paddle/v2/framework/tests/CMakeLists.txt @@ -14,6 +14,7 @@ py_test(test_sigmoid_op SRCS test_sigmoid_op.py) py_test(test_softmax_op SRCS test_softmax_op.py) py_test(test_cross_entropy_op SRCS test_cross_entropy_op.py) py_test(test_gather_op SRCS test_gather_op.py) +py_test(test_scatter_op SRCS test_scatter_op.py) py_test(test_fill_zeros_like_op SRCS test_fill_zeros_like_op.py) py_test(gradient_checker SRCS gradient_checker.py) diff --git a/python/paddle/v2/framework/tests/test_gather_op.py b/python/paddle/v2/framework/tests/test_gather_op.py index e868983042..e3de3fd0a1 100644 --- a/python/paddle/v2/framework/tests/test_gather_op.py +++ b/python/paddle/v2/framework/tests/test_gather_op.py @@ -21,12 +21,9 @@ class TestGatherOp(unittest.TestCase): class TestGatherGradOp(GradientChecker): def test_gather_grad(self): - print 'creating op' op = create_op("gather") - print 'creating op done' xnp = numpy.random.random((10, 20)).astype("float32") inputs = {'X': xnp, 'Index': numpy.array([1, 3, 5]).astype("int32")} - print 'correct before check gradient' self.check_grad(op, inputs, set("X"), "Out") diff --git a/python/paddle/v2/framework/tests/test_scatter_op.py b/python/paddle/v2/framework/tests/test_scatter_op.py new file mode 100644 index 0000000000..e7696844d5 --- /dev/null +++ b/python/paddle/v2/framework/tests/test_scatter_op.py @@ -0,0 +1,38 @@ +import unittest +from op_test_util import OpTestMeta +from gradient_checker import GradientChecker, create_op +import numpy +import paddle.v2.framework.core as core +from paddle.v2.framework.op import Operator + + +class TestScatterOp(unittest.TestCase): + __metaclass__ = OpTestMeta + + def setUp(self): + self.type = "scatter" + ref_np = numpy.ones((3, 3)).astype("float32") + index_np = numpy.array([1, 2]).astype("int32") + updates_np = numpy.random.random((2, 3)).astype("float32") + output_np = numpy.copy(ref_np) + output_np[index_np] += updates_np + self.inputs = {'Ref': ref_np, 'Index': index_np, 'Updates': updates_np} + self.outputs = {'Out': output_np} + + +class TestScatterGradOp(GradientChecker): + def test_scatter_grad(self): + op = create_op("scatter") + # test data setup + ref_np = numpy.ones((3, 10)).astype("float32") + index_np = numpy.array([1, 2]).astype("int32") + updates_np = numpy.random.random((2, 10)).astype("float32") + output_np = numpy.copy(ref_np) + output_np[index_np] += updates_np + inputs = {'Ref': ref_np, 'Index': index_np, 'Updates': updates_np} + # check gradient + self.check_grad(op, inputs, set(["Updates", "Ref"]), "Out") + + +if __name__ == "__main__": + unittest.main() From 1dc62cd21ca8699c6740d71cf984a7f5d589b77a Mon Sep 17 00:00:00 2001 From: Xi Chen Date: Thu, 24 Aug 2017 11:28:48 -0700 Subject: [PATCH 118/138] updated doc with implementation change of trainer --- doc/design/cluster_train/README.md | 25 +++++++++--------- .../cluster_train/src/paddle-etcd.graffle | Bin 5765 -> 5557 bytes doc/design/cluster_train/src/paddle-etcd.png | Bin 57495 -> 50387 bytes 3 files changed, 12 insertions(+), 13 deletions(-) diff --git a/doc/design/cluster_train/README.md b/doc/design/cluster_train/README.md index 74961f8005..177a5f5d54 100644 --- a/doc/design/cluster_train/README.md +++ b/doc/design/cluster_train/README.md @@ -54,17 +54,18 @@ The life cycle of a single task is illustrated below: 1. When a new pass of training starts, all tasks will be placed in the todo queue. -1. The master server will dispatch few tasks to each trainer at a time, puts them in the pending queue and waits for completion. -1. The trainer will work on its tasks and tell the master server once a task is completed. The master server will dispatch a new task to that trainer. -1. If a task timeout. the master server will move it back to the todo queue. The timeout count will increase by one. If the timeout count is above a threshold, the task is likely to cause a trainer to crash, so it will be discarded. +1. Upon trainer requests for new task, the master server will dispatch a task from todo queue to it, put the task in the pending queue and wait for completion. +1. The trainer will work on its task and tell the master server once the task is completed and ask for new task. The master server will dispatch a new task to that trainer. +1. If a task fails for any reason in trainer, or takes longer than a specific period of time, the master server will move the task back to the todo queue. The timeout count for that task will increase by one. If the timeout count is above a threshold, the task is likely to cause a trainer to crash, then it will be discarded. 1. The master server will move completed task to the done queue. When the todo queue is empty, the master server will start a new pass by moving all tasks in the done queue to todo queue and reset the timeout counter of all tasks to zero. ### Trainer Process The trainer process will: -- Receive tasks from the master. -- Work on the tasks: calculate and upload gradient to parameter servers, and update local model by downloading new parameters from parameter servers. +- Request tasks from the master. +- Work on the tasks +- Upload gradient to parameter servers, and update local model by downloading new parameters from parameter servers. ### Parameter Server Process @@ -119,8 +120,8 @@ When the master is started by the Kubernetes, it executes the following steps at 1. Grabs a unique *master* lock in etcd, which prevents concurrent master instantiations. 1. Recovers the task queues from etcd if they already exist, otherwise, the master will create them. -1. Watches the trainer prefix keys `/trainer/` on etcd to find the live trainers. -1. Starts dispatching the tasks to the trainers, and updates task queue using an etcd transaction to ensure lock is held during the update. +1. Write its ip address to */master/addr* so that trainers can discover it. +1. Listens to trainers' request of task, dispatch one upon request, and updates task queue using an etcd transaction to ensure lock is held during the update. When the master server process is dead for any reason, Kubernetes will restart it. It will be online again with all states recovered from etcd in few minutes. @@ -128,13 +129,11 @@ When the master server process is dead for any reason, Kubernetes will restart i When the trainer is started by the Kubernetes, it executes the following steps at startup: -1. Watches the available parameter server prefix keys `/ps/` on etcd and waits until the count of parameter servers reaches the desired count. -1. Generates a unique ID, and sets key `/trainer/` with its contact address as value. The key will be deleted when the lease expires, so the master will be aware of the trainer being online and offline. -1. Waits for tasks from the master to start training. +1. Watches the available parameter server prefix keys `/ps/` on etcd and waits until the count of parameter servers reaches the desired count */ps_desired*. +1. Finds and watches */master/addr* to get master's address. +1. Requests for tasks from the master to start training. -If trainer's etcd lease expires, it will try set key `/trainer/` again so that the master server can discover the trainer again. - -When a trainer fails, Kuberentes would try to restart it. The recovered trainer would fetch tasks from the TODO queue and go on training. +When a trainer fails, Kuberentes would try to restart it. 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.../v2/framework/tests/gradient_checker.py | 21 ++++++++++++------- .../v2/framework/tests/test_scatter_op.py | 3 ++- 2 files changed, 15 insertions(+), 9 deletions(-) diff --git a/python/paddle/v2/framework/tests/gradient_checker.py b/python/paddle/v2/framework/tests/gradient_checker.py index 8eb9f3f073..ac37671c77 100644 --- a/python/paddle/v2/framework/tests/gradient_checker.py +++ b/python/paddle/v2/framework/tests/gradient_checker.py @@ -32,7 +32,8 @@ def get_numeric_gradient(op, output_name, input_to_check, delta=0.005, - local_scope=None): + local_scope=None, + in_place=False): """ Get Numeric Gradient for an operator's input. @@ -90,9 +91,10 @@ def get_numeric_gradient(op, # we only compute gradient of one element each time. # we use a for loop to compute the gradient of every element. for i in xrange(tensor_size): - for var_name in input_values: - tensor_ = local_scope.find_var(var_name).get_tensor() - tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace()) + if in_place: + for var_name in input_values: + tensor_ = local_scope.find_var(var_name).get_tensor() + tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace()) # get one input element throw it's index i. origin = tensor_to_check.get_float_element(i) @@ -102,9 +104,10 @@ def get_numeric_gradient(op, y_pos = get_output() # plus delta to this element, run op and get the sum of the result tensor. - for var_name in input_values: - tensor_ = local_scope.find_var(var_name).get_tensor() - tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace()) + if in_place: + for var_name in input_values: + tensor_ = local_scope.find_var(var_name).get_tensor() + tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace()) x_neg = origin - delta tensor_to_check.set_float_element(i, x_neg) y_neg = get_output() @@ -257,6 +260,7 @@ class GradientChecker(unittest.TestCase): output_name, no_grad_set=None, only_cpu=False, + in_place=False, max_relative_error=0.005): """ :param forward_op: used to create backward_op @@ -289,7 +293,8 @@ class GradientChecker(unittest.TestCase): # get numerical gradients numeric_grads = [ - get_numeric_gradient(forward_op, input_vars, output_name, name) + get_numeric_gradient( + forward_op, input_vars, output_name, name, in_place=in_place) for name in inputs_to_check ] diff --git a/python/paddle/v2/framework/tests/test_scatter_op.py b/python/paddle/v2/framework/tests/test_scatter_op.py index e7696844d5..861fe6cf89 100644 --- a/python/paddle/v2/framework/tests/test_scatter_op.py +++ b/python/paddle/v2/framework/tests/test_scatter_op.py @@ -31,7 +31,8 @@ class TestScatterGradOp(GradientChecker): output_np[index_np] += updates_np inputs = {'Ref': ref_np, 'Index': index_np, 'Updates': updates_np} # check gradient - self.check_grad(op, inputs, set(["Updates", "Ref"]), "Out") + self.check_grad( + op, inputs, set(["Updates", "Ref"]), "Out", in_place=True) if __name__ == "__main__": From f22ece9273b54f1a248f7a787e252eb04a5acea3 Mon Sep 17 00:00:00 2001 From: Yi Wang Date: Thu, 24 Aug 2017 19:44:19 -0700 Subject: [PATCH 121/138] Add a document on building using Docker --- Dockerfile | 4 +- doc/howto/dev/build_en.md | 83 ++++++++++++++++++++++++++++++++++ paddle/scripts/docker/build.sh | 6 +-- 3 files changed, 87 insertions(+), 6 deletions(-) create mode 100644 doc/howto/dev/build_en.md diff --git a/Dockerfile b/Dockerfile index 98f61ba586..136db772cc 100644 --- a/Dockerfile +++ b/Dockerfile @@ -10,13 +10,11 @@ RUN /bin/bash -c 'if [[ -n ${UBUNTU_MIRROR} ]]; then sed -i 's#http://archive.ub ARG WITH_GPU ARG WITH_AVX ARG WITH_DOC -ARG WITH_STYLE_CHECK ENV WOBOQ OFF -ENV WITH_GPU=${WITH_GPU:-OFF} +ENV WITH_GPU=${WITH_GPU:-ON} ENV WITH_AVX=${WITH_AVX:-ON} ENV WITH_DOC=${WITH_DOC:-OFF} -ENV WITH_STYLE_CHECK=${WITH_STYLE_CHECK:-OFF} ENV HOME /root # Add bash enhancements diff --git a/doc/howto/dev/build_en.md b/doc/howto/dev/build_en.md new file mode 100644 index 0000000000..80488a147d --- /dev/null +++ b/doc/howto/dev/build_en.md @@ -0,0 +1,83 @@ +# Build PaddlePaddle from Source Code and Run Unit Test + +## What Developers Need + +To contribute to PaddlePaddle, you need + +1. A computer -- Linux, BSD, Windows, MacOS, and +1. Docker. + +Nothing else. Not even Python and GCC, because you can install all build tools into a Docker image. + +## General Process + +1. Retrieve source code. + + ```bash + git clone https://github.com/paddlepaddle/paddle + ``` + +2. Install build tools. + + ```bash + cd paddle; docker build -t paddle:dev . + ``` + +3. Build from source. + + ```bash + docker run -v $PWD:/paddle paddle:dev + ``` + +4. Run unit tests. + + ```bash + docker run -v $PWD:/paddle paddle:dev "cd/build; ctest" + ``` + + +## Docker, Or Not? + +- What is Docker? + + If you haven't heard of it, consider it something like Python's virtualenv. + +- Docker or virtual machine? + + Some people compare Docker with VMs, but Docker doesn't virtualize any hardware, and it doesn't run a guest OS. + +- Why Docker? + + Using a Docker image of build tools standardize the building environment, and easier for others to reproduce your problem, if there is any, and help. + + Also, some build tools don't run on Windows or Mac or BSD, but Docker runs almost everywhere, so developers can use whatever computer they want. + +- Can I don't use Docker? + + Sure, you don't have to install build tools into a Docker image; instead, you can install them onto your local computer. This document exists because Docker would make the development way easier. + +- How difficult is it to learn Docker? + + It takes you ten minutes to read https://docs.docker.com/get-started/ and saves you more than one hour to install all required build tools, configure them, and upgrade them when new versions of PaddlePaddle require some new tools. + +- Docker requires sudo + + An owner of a computer has the administrative privilege, a.k.a., sudo. If you use a shared computer for development, please ask the administrator to install and configure Docker. We will do our best to support rkt, another container technology that doesn't require sudo. + +- Can I use my favorite IDE? + + Yes, of course. The source code resides on your local computer, and you can edit it using whatever editor you like. + + Many PaddlePaddle developers are using Emacs. They add the following few lines into their `~/.emacs` configure file: + + ```emacs + (global-set-key "\C-cc" 'compile) + (setq compile-command + "docker run --rm -it -v $(git rev-parse --show-toplevel):/paddle paddle:dev") + ``` + + so they could type `Ctrl-C` and `c` to build PaddlePaddle from source. + +- How many parallel building processes does the Docker container run? + + Our building Docker image runs a Bash script https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh, which calls `make -j$(nproc)` to starts as many processes as the number of your processors. diff --git a/paddle/scripts/docker/build.sh b/paddle/scripts/docker/build.sh index 2941662f34..7bab814ae8 100644 --- a/paddle/scripts/docker/build.sh +++ b/paddle/scripts/docker/build.sh @@ -38,7 +38,7 @@ Configuring cmake in /paddle/build ... -DWITH_SWIG_PY=${WITH_SWIG_PY:-ON} -DCUDNN_ROOT=/usr/ -DWITH_STYLE_CHECK=${WITH_STYLE_CHECK:-OFF} - -DWITH_TESTING=${WITH_TESTING:-OFF} + -DWITH_TESTING=${WITH_TESTING:-ON} -DCMAKE_EXPORT_COMPILE_COMMANDS=ON ======================================== EOF @@ -56,8 +56,8 @@ cmake .. \ -DWITH_C_API=${WITH_C_API:-OFF} \ -DWITH_PYTHON=${WITH_PYTHON:-ON} \ -DCUDNN_ROOT=/usr/ \ - -DWITH_STYLE_CHECK=${WITH_STYLE_CHECK:-OFF} \ - -DWITH_TESTING=${WITH_TESTING:-OFF} \ + -DWITH_STYLE_CHECK=${WITH_STYLE_CHECK:-ON} \ + -DWITH_TESTING=${WITH_TESTING:-ON} \ -DCMAKE_EXPORT_COMPILE_COMMANDS=ON cat < Date: Thu, 24 Aug 2017 20:37:39 -0700 Subject: [PATCH 122/138] Update unit test running and CUDA --- doc/howto/dev/build_en.md | 15 ++++++++++++++- 1 file changed, 14 insertions(+), 1 deletion(-) diff --git a/doc/howto/dev/build_en.md b/doc/howto/dev/build_en.md index 80488a147d..de0733f963 100644 --- a/doc/howto/dev/build_en.md +++ b/doc/howto/dev/build_en.md @@ -29,12 +29,25 @@ Nothing else. Not even Python and GCC, because you can install all build tools docker run -v $PWD:/paddle paddle:dev ``` + This builds a CUDA-enabled version and writes all binary outputs to directory `./build` of the local computer, other than the Docker container. If we want to build only the CPU part, we can type + + ```bash + docker run -e WITH_GPU=OFF -v $PWD:/paddle paddle:dev + ``` + 4. Run unit tests. + To run all unit tests using the first GPU of a node: + ```bash - docker run -v $PWD:/paddle paddle:dev "cd/build; ctest" + NV_GPU=0 nvidia-docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest" ``` + If we used `WITH_GPU=OFF` at build time, it generates only CPU-based unit tests, and we don't need nvidia-docker to run them. We can just run + + ```bash + docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest" + ``` ## Docker, Or Not? From 06fad3fe9deccdc8ee4721ff028753f53c7ab87f Mon Sep 17 00:00:00 2001 From: gongweibao Date: Fri, 25 Aug 2017 12:01:57 +0800 Subject: [PATCH 123/138] hidden capi symbols (#3636) hidden capi symbols --- paddle/capi/CMakeLists.txt | 3 +++ paddle/capi/export.map | 6 ++++++ paddle/capi/export.sym | 0 3 files changed, 9 insertions(+) create mode 100644 paddle/capi/export.map create mode 100644 paddle/capi/export.sym diff --git a/paddle/capi/CMakeLists.txt b/paddle/capi/CMakeLists.txt index 11022d1754..dde99ab340 100644 --- a/paddle/capi/CMakeLists.txt +++ b/paddle/capi/CMakeLists.txt @@ -53,7 +53,10 @@ add_custom_target(paddle_capi_whole ALL set_target_properties(paddle_capi_whole PROPERTIES IMPORTED_LOCATION ${CMAKE_CURRENT_BINARY_DIR}/${capi_whole_library}) +set(LINK_FLAGS " -Wl,--retain-symbols-file ${CMAKE_CURRENT_SOURCE_DIR}/export.sym -Wl,--version-script ${CMAKE_CURRENT_SOURCE_DIR}/export.map") +# TODO: merge mkl into paddle_capi_shared add_library(paddle_capi_shared SHARED ${CAPI_SOURCES}) +set_target_properties(paddle_capi_shared PROPERTIES LINK_FLAGS "${LINK_FLAGS}") target_include_directories(paddle_capi_shared PUBLIC ${CMAKE_CURRENT_BINARY_DIR}) link_paddle_exe(paddle_capi_shared) diff --git a/paddle/capi/export.map b/paddle/capi/export.map new file mode 100644 index 0000000000..8d673f675d --- /dev/null +++ b/paddle/capi/export.map @@ -0,0 +1,6 @@ +{ + global: + paddle_*; + local: + *; +}; diff --git a/paddle/capi/export.sym b/paddle/capi/export.sym new file mode 100644 index 0000000000..e69de29bb2 From 1e61d91f24e9213ab43edc62cf2c6f9e47a62d1f Mon Sep 17 00:00:00 2001 From: Yi Wang Date: Thu, 24 Aug 2017 21:38:13 -0700 Subject: [PATCH 124/138] Update index and add Chinese version --- doc/howto/dev/build_cn.md | 100 ++++++++++++++++++++++++++++++++++++++ doc/howto/dev/build_en.md | 6 ++- doc/howto/index_cn.rst | 1 + doc/howto/index_en.rst | 1 + 4 files changed, 107 insertions(+), 1 deletion(-) create mode 100644 doc/howto/dev/build_cn.md diff --git a/doc/howto/dev/build_cn.md b/doc/howto/dev/build_cn.md new file mode 100644 index 0000000000..dc372de9fa --- /dev/null +++ b/doc/howto/dev/build_cn.md @@ -0,0 +1,100 @@ +# 编译PaddlePaddle和运行单元测试 + +## 需要的软硬件 + +为了开发PaddlePaddle，我们需要 + +1. 一台电脑，可以装的是 Linux, BSD, Windows 或者 MacOS 操作系统，以及 +1. Docker。 + +不需要其他任何软件了。即便是 Python 和 GCC 都不需要，因为我们会把所有编译工具都安装进一个 Docker image 里。 + +## 总体流程 + +1. 获取源码 + + ```bash + git clone https://github.com/paddlepaddle/paddle + ``` + +2. 安装工具 + + ```bash + cd paddle; docker build -t paddle:dev . + ``` + +3. 编译 + + ```bash + docker run -v $PWD:/paddle paddle:dev + ``` + + 这个命令编译出一个 CUDA-enabled 版本。所有二进制文件会被写到本机的 `./build` 目录，而不是写到 Docker container 里。如果我们只需要编译一个只支持 CPU 的版本，可以用 + + ```bash + docker run -e WITH_GPU=OFF -v $PWD:/paddle paddle:dev + ``` + +4. 运行单元测试 + + 用本机的第一个 GPU 来运行包括 GPU 单元测试在内的所有单元测试： + + ```bash + NV_GPU=0 nvidia-docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest" + ``` + + 如果编译的时候我们用了 `WITH_GPU=OFF` 选项，那么编译过程只会产生 CPU-based 单元测试，那么我们也就不需要 nvidia-docker 来运行单元测试了。我们只需要： + + ```bash + docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest" + ``` + +## 为什么要 Docker 呀？ + +- 什么是 Docker? + + 如果您没有听说 Docker，可以把它想象为一个类似 virtualenv 的系统，但是虚拟的不仅仅是 Python 的运行环境。 + +- Docker 还是虚拟机？ + + 有人用虚拟机来类比 Docker。需要强调的是：Docker 不会虚拟任何硬件，Docker container 里运行的编译工具实际上都是在本机的 CPU 和操作系统上直接运行的，性能和把编译工具安装在本机运行基本一样。 + +- 为什么用 Docker? + + 把工具和配置都安装在一个 Docker image 里可以标准化编译环境。这样如果遇到问题，其他人可以复现问题以便帮助。 + + 另外，对于习惯使用Windows和MacOS的开发者来说，使用Docker就不用配置交叉编译环境了。 + +- 我可以选择不用Docker吗？ + + 当然可以。大家可以用把开发工具安装进入 Docker image 一样的方式，把这些工具安装到本机。这篇文档介绍基于 Docker 的开发流程，是因为这个流程比其他方法都更简便。 + +- 学习 Docker 有多难？ + + 理解 Docker 并不难，大概花十分钟看一遍 https://zhuanlan.zhihu.com/p/19902938 即可。这可以帮您省掉花一小时安装和配置各种开发工具，以及切换机器时需要新安装的辛苦。别忘了 PaddlePaddle 更新可能导致需要新的开发工具。更别提简化问题复现带来的好处了。 + +- Docker 需要 sudo + + 如果用自己的电脑开发，自然也就有管理员权限（sudo）了。如果用公用的电脑开发，需要请管理员安装和配置好 Docker。此外，PaddlePaddle 项目在努力开始支持其他不需要 sudo 的集装箱技术，比如 rkt。 + +- 我可以用 IDE 吗？ + + 当然可以，因为源码就在本机上。IDE 默认调用 make 之类的程序来编译源码，我们只需要配置 IDE 来调用 Docker 命令编译源码即可。 + + 很多 PaddlePaddle 开发者使用 Emacs。他们在自己的 `~/.emacs` 配置文件里加两行 + + ```emacs + (global-set-key "\C-cc" 'compile) + (setq compile-command + "docker run --rm -it -v $(git rev-parse --show-toplevel):/paddle paddle:dev") + ``` + + 就可以按 `Ctrl-C` 和 `c` 键来启动编译了。 + +- 可以并行编译吗？ + + 是的。我们的 Docker image 运行一个 Bash 脚本 https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh 。这个脚本调用 `make -j$(nproc)` 来启动和 CPU 核一样多的进程来并行编译。 + +- Docker on Windows/MacOS？ + + Docker 在 Windows 和 MacOS 都可以运行。不过实际上是运行在一个 Linux 虚拟机上。可能需要注意给这个虚拟机多分配一些 CPU 和内存，以保证编译高效。具体做法请参考 https://github.com/PaddlePaddle/Paddle/issues/627 。 diff --git a/doc/howto/dev/build_en.md b/doc/howto/dev/build_en.md index de0733f963..640d126018 100644 --- a/doc/howto/dev/build_en.md +++ b/doc/howto/dev/build_en.md @@ -91,6 +91,10 @@ Nothing else. Not even Python and GCC, because you can install all build tools so they could type `Ctrl-C` and `c` to build PaddlePaddle from source. -- How many parallel building processes does the Docker container run? +- Does Docker do parallel building? Our building Docker image runs a Bash script https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh, which calls `make -j$(nproc)` to starts as many processes as the number of your processors. + +- Docker on Windows/MacOS? + + On Windows and MacOS, Docker containers run in a Linux VM. You might want to give this VM some more memory and CPUs so to make the building efficient. Please refer to https://github.com/PaddlePaddle/Paddle/issues/627 for details. diff --git a/doc/howto/index_cn.rst b/doc/howto/index_cn.rst index 26449a6365..0608aa3096 100644 --- a/doc/howto/index_cn.rst +++ b/doc/howto/index_cn.rst @@ -19,6 +19,7 @@ .. toctree:: :maxdepth: 1 + dev/build_cn.rst dev/write_docs_cn.rst dev/contribute_to_paddle_cn.md diff --git a/doc/howto/index_en.rst b/doc/howto/index_en.rst index 1fbfcd260b..1b6034be4e 100644 --- a/doc/howto/index_en.rst +++ b/doc/howto/index_en.rst @@ -18,6 +18,7 @@ Development .. toctree:: :maxdepth: 1 + dev/build_en.rst dev/new_layer_en.rst dev/contribute_to_paddle_en.md From 818a64f41ffacca0d3ff07928a19ac47021ccac1 Mon Sep 17 00:00:00 2001 From: wanghaoshuang Date: Fri, 25 Aug 2017 13:56:55 +0800 Subject: [PATCH 125/138] Fix img_pool_layer bug. --- python/paddle/trainer_config_helpers/layers.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py index f323b017c0..862265f2cd 100755 --- a/python/paddle/trainer_config_helpers/layers.py +++ b/python/paddle/trainer_config_helpers/layers.py @@ -2607,15 +2607,15 @@ def img_pool_layer(input, assert input.num_filters is not None num_channels = input.num_filters - assert type(pool_type) in [AvgPooling, MaxPooling, CudnnAvgPooling, - CudnnMaxPooling], \ - "only (Cudnn)AvgPooling, (Cudnn)MaxPooling are supported" - if pool_type is None: pool_type = MaxPooling() elif isinstance(pool_type, AvgPooling): pool_type.name = 'avg' + assert type(pool_type) in [AvgPooling, MaxPooling, CudnnAvgPooling, + CudnnMaxPooling], \ + "only (Cudnn)AvgPooling, (Cudnn)MaxPooling are supported" + type_name = pool_type.name + '-projection' \ if ( isinstance(pool_type, AvgPooling) or isinstance(pool_type, MaxPooling)) \ From aa28d046fb828814b9849aa1ebfc868be2db98f9 Mon Sep 17 00:00:00 2001 From: caoying03 Date: Fri, 25 Aug 2017 14:11:36 +0800 Subject: [PATCH 126/138] fix a bug of sequence_slice layer when batch_size=1 --- paddle/gserver/layers/SequenceSliceLayer.cpp | 18 ++++++++++-------- .../gserver/tests/test_SeqSliceLayerGrad.cpp | 4 +++- 2 files changed, 13 insertions(+), 9 deletions(-) diff --git a/paddle/gserver/layers/SequenceSliceLayer.cpp b/paddle/gserver/layers/SequenceSliceLayer.cpp index 5d72d37304..aab44c4646 100644 --- a/paddle/gserver/layers/SequenceSliceLayer.cpp +++ b/paddle/gserver/layers/SequenceSliceLayer.cpp @@ -130,6 +130,8 @@ void SequenceSliceLayer::calSelectedRows(const MatrixPtr starts, CHECK(starts || ends) << "At least one of the start or end indices " << "should be given."; + bool hasSubseq = getInput(0).hasSubseq(); + outSeqStartPos_.resize(1, 0); outSubSeqStartPos_.resize(1, 0); selectedRows_.clear(); @@ -151,14 +153,13 @@ void SequenceSliceLayer::calSelectedRows(const MatrixPtr starts, int seqLen = endPos - begPos + 1; CHECK_GT(seqLen, 0U); for (int m = begPos; m <= endPos; ++m) selectedRows_.push_back(m); - inputSeqInfoVec_.size() > 1 + hasSubseq ? outSubSeqStartPos_.push_back(outSubSeqStartPos_.back() + seqLen) : outSeqStartPos_.push_back(outSeqStartPos_.back() + seqLen); } rowIdx++; } - if (inputSeqInfoVec_.size() > 1) - outSeqStartPos_.push_back(outSubSeqStartPos_.back()); + if (hasSubseq) outSeqStartPos_.push_back(outSubSeqStartPos_.back()); } if (useGpu_) { @@ -175,7 +176,7 @@ void SequenceSliceLayer::calSelectedRows(const MatrixPtr starts, output_.sequenceStartPositions->copyFrom( outSeqStartPos_.data(), outSeqStartPos_.size(), false); - if (inputSeqInfoVec_.size() > 1) { + if (hasSubseq) { ICpuGpuVector::resizeOrCreate( output_.subSequenceStartPositions, outSubSeqStartPos_.size(), false); output_.subSequenceStartPositions->copyFrom( @@ -203,10 +204,11 @@ void SequenceSliceLayer::forward(PassType passType) { } else copySliceIdsToCpu(); - // calculate the selected row indices in a batch, - // and build the output sequence information. - calSelectedRows(startIdsOnCpu_ ? startIdsOnCpu_ : nullptr, - endIdsOnCpu_ ? endIdsOnCpu_ : nullptr); + /* + * calculate the selected row indices in a batch, and build the output + * sequence information. + */ + calSelectedRows(startIdsOnCpu_, endIdsOnCpu_); resetOutput(selectedRows_.size(), getSize()); diff --git a/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp b/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp index d560ca650b..e1d4ae1617 100644 --- a/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp +++ b/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp @@ -30,6 +30,8 @@ const int MAX_SEQ_NUM = 17; const int MAX_SEQ_LEN = 23; const int MAX_BEAM_SIZE = 13; +const size_t SEED = (size_t)(time(NULL)); + vector randSampling(real range, int n) { CHECK_GE(range, n); vector num(range); @@ -46,7 +48,7 @@ void genSeqInfo(vector& seqStartPos, vector& subSeqStartPos) { seqStartPos.resize(1, 0); subSeqStartPos.resize(1, 0); - srand((size_t)(time(NULL))); + srand(SEED); int seqNum = 1 + (rand() % MAX_SEQ_NUM); for (int i = 0; i < seqNum; ++i) { int subSeqNum = 1 + (rand() % MAX_SEQ_NUM); From c8d0c9af865cd0ac47d1cd7461c24793d833eeff Mon Sep 17 00:00:00 2001 From: Yi Wang Date: Fri, 25 Aug 2017 11:24:48 -0700 Subject: [PATCH 127/138] In response to comments from Luo Tao --- doc/howto/dev/build_cn.md | 6 +++--- doc/howto/dev/build_en.md | 6 +++--- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/doc/howto/dev/build_cn.md b/doc/howto/dev/build_cn.md index dc372de9fa..7c95579636 100644 --- a/doc/howto/dev/build_cn.md +++ b/doc/howto/dev/build_cn.md @@ -71,7 +71,7 @@ - 学习 Docker 有多难？ - 理解 Docker 并不难，大概花十分钟看一遍 https://zhuanlan.zhihu.com/p/19902938 即可。这可以帮您省掉花一小时安装和配置各种开发工具，以及切换机器时需要新安装的辛苦。别忘了 PaddlePaddle 更新可能导致需要新的开发工具。更别提简化问题复现带来的好处了。 + 理解 Docker 并不难，大概花十分钟看一下[这篇文章](https://zhuanlan.zhihu.com/p/19902938)。这可以帮您省掉花一小时安装和配置各种开发工具，以及切换机器时需要新安装的辛苦。别忘了 PaddlePaddle 更新可能导致需要新的开发工具。更别提简化问题复现带来的好处了。 - Docker 需要 sudo @@ -93,8 +93,8 @@ - 可以并行编译吗？ - 是的。我们的 Docker image 运行一个 Bash 脚本 https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh 。这个脚本调用 `make -j$(nproc)` 来启动和 CPU 核一样多的进程来并行编译。 + 是的。我们的 Docker image 运行一个 [Bash 脚本](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh)。这个脚本调用 `make -j$(nproc)` 来启动和 CPU 核一样多的进程来并行编译。 - Docker on Windows/MacOS？ - Docker 在 Windows 和 MacOS 都可以运行。不过实际上是运行在一个 Linux 虚拟机上。可能需要注意给这个虚拟机多分配一些 CPU 和内存，以保证编译高效。具体做法请参考 https://github.com/PaddlePaddle/Paddle/issues/627 。 + Docker 在 Windows 和 MacOS 都可以运行。不过实际上是运行在一个 Linux 虚拟机上。可能需要注意给这个虚拟机多分配一些 CPU 和内存，以保证编译高效。具体做法请参考[这个issue](https://github.com/PaddlePaddle/Paddle/issues/627)。 diff --git a/doc/howto/dev/build_en.md b/doc/howto/dev/build_en.md index 640d126018..3be2405ea7 100644 --- a/doc/howto/dev/build_en.md +++ b/doc/howto/dev/build_en.md @@ -71,7 +71,7 @@ Nothing else. Not even Python and GCC, because you can install all build tools - How difficult is it to learn Docker? - It takes you ten minutes to read https://docs.docker.com/get-started/ and saves you more than one hour to install all required build tools, configure them, and upgrade them when new versions of PaddlePaddle require some new tools. + It takes you ten minutes to read [an introductory article](https://docs.docker.com/get-started) and saves you more than one hour to install all required build tools, configure them, and upgrade them when new versions of PaddlePaddle require some new tools. - Docker requires sudo @@ -93,8 +93,8 @@ Nothing else. Not even Python and GCC, because you can install all build tools - Does Docker do parallel building? - Our building Docker image runs a Bash script https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh, which calls `make -j$(nproc)` to starts as many processes as the number of your processors. + Our building Docker image runs a [Bash script](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh), which calls `make -j$(nproc)` to starts as many processes as the number of your processors. - Docker on Windows/MacOS? - On Windows and MacOS, Docker containers run in a Linux VM. You might want to give this VM some more memory and CPUs so to make the building efficient. Please refer to https://github.com/PaddlePaddle/Paddle/issues/627 for details. + On Windows and MacOS, Docker containers run in a Linux VM. You might want to give this VM some more memory and CPUs so to make the building efficient. Please refer to [this issue](https://github.com/PaddlePaddle/Paddle/issues/627) for details. From f71f3935e3ce05a8e90edc971f5ab08d71ed2966 Mon Sep 17 00:00:00 2001 From: Yi Wang Date: Fri, 25 Aug 2017 11:51:53 -0700 Subject: [PATCH 128/138] In response to comments from Chen Xi --- doc/howto/dev/build_cn.md | 20 +++++++++++++------- doc/howto/dev/build_en.md | 34 ++++++++++++++++++++-------------- 2 files changed, 33 insertions(+), 21 deletions(-) diff --git a/doc/howto/dev/build_cn.md b/doc/howto/dev/build_cn.md index 7c95579636..0077d90118 100644 --- a/doc/howto/dev/build_cn.md +++ b/doc/howto/dev/build_cn.md @@ -23,13 +23,17 @@ cd paddle; docker build -t paddle:dev . ``` + 请注意这个命令结尾处的 `.`；它表示 `docker build` 应该读取当前目录下的 [`Dockerfile`文件](https://github.com/PaddlePaddle/Paddle/blob/develop/Dockerfile)，按照其内容创建一个名为 `paddle:dev` 的 Docker image，并且把各种开发工具安装进去。 + 3. 编译 + 以下命令启动一个 Docker container 来执行 `paddle:dev` 这个 Docker image，同时把当前目录（源码树根目录）映射为 container 里的 `/paddle` 目录，并且运行 `Dockerfile` 描述的默认入口程序 [`build.sh`](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh)。这个脚本调用 `cmake` 和 `make` 来编译 `/paddle` 里的源码，结果输出到 `/paddle/build`，也就是本地的源码树根目录里的 `build` 子目录。 + ```bash docker run -v $PWD:/paddle paddle:dev ``` - 这个命令编译出一个 CUDA-enabled 版本。所有二进制文件会被写到本机的 `./build` 目录，而不是写到 Docker container 里。如果我们只需要编译一个只支持 CPU 的版本，可以用 + 上述命令编译出一个 CUDA-enabled 版本。如果我们只需要编译一个只支持 CPU 的版本，可以用 ```bash docker run -e WITH_GPU=OFF -v $PWD:/paddle paddle:dev @@ -57,7 +61,7 @@ - Docker 还是虚拟机？ - 有人用虚拟机来类比 Docker。需要强调的是：Docker 不会虚拟任何硬件，Docker container 里运行的编译工具实际上都是在本机的 CPU 和操作系统上直接运行的，性能和把编译工具安装在本机运行基本一样。 + 有人用虚拟机来类比 Docker。需要强调的是：Docker 不会虚拟任何硬件，Docker container 里运行的编译工具实际上都是在本机的 CPU 和操作系统上直接运行的，性能和把编译工具安装在本机运行一样。 - 为什么用 Docker? @@ -73,10 +77,6 @@ 理解 Docker 并不难，大概花十分钟看一下[这篇文章](https://zhuanlan.zhihu.com/p/19902938)。这可以帮您省掉花一小时安装和配置各种开发工具，以及切换机器时需要新安装的辛苦。别忘了 PaddlePaddle 更新可能导致需要新的开发工具。更别提简化问题复现带来的好处了。 -- Docker 需要 sudo - - 如果用自己的电脑开发，自然也就有管理员权限（sudo）了。如果用公用的电脑开发，需要请管理员安装和配置好 Docker。此外，PaddlePaddle 项目在努力开始支持其他不需要 sudo 的集装箱技术，比如 rkt。 - - 我可以用 IDE 吗？ 当然可以，因为源码就在本机上。IDE 默认调用 make 之类的程序来编译源码，我们只需要配置 IDE 来调用 Docker 命令编译源码即可。 @@ -95,6 +95,12 @@ 是的。我们的 Docker image 运行一个 [Bash 脚本](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh)。这个脚本调用 `make -j$(nproc)` 来启动和 CPU 核一样多的进程来并行编译。 -- Docker on Windows/MacOS？ +## 可能碰到的问题 + +- Docker 需要 sudo + + 如果用自己的电脑开发，自然也就有管理员权限（sudo）了。如果用公用的电脑开发，需要请管理员安装和配置好 Docker。此外，PaddlePaddle 项目在努力开始支持其他不需要 sudo 的集装箱技术，比如 rkt。 + +- 在 Windows/MacOS 上编译很慢 Docker 在 Windows 和 MacOS 都可以运行。不过实际上是运行在一个 Linux 虚拟机上。可能需要注意给这个虚拟机多分配一些 CPU 和内存，以保证编译高效。具体做法请参考[这个issue](https://github.com/PaddlePaddle/Paddle/issues/627)。 diff --git a/doc/howto/dev/build_en.md b/doc/howto/dev/build_en.md index 3be2405ea7..95752beba0 100644 --- a/doc/howto/dev/build_en.md +++ b/doc/howto/dev/build_en.md @@ -7,7 +7,7 @@ To contribute to PaddlePaddle, you need 1. A computer -- Linux, BSD, Windows, MacOS, and 1. Docker. -Nothing else. Not even Python and GCC, because you can install all build tools into a Docker image. +Nothing else. Not even Python and GCC, because you can install all build tools into a Docker image. We run all the tools by running this image. ## General Process @@ -17,19 +17,23 @@ Nothing else. Not even Python and GCC, because you can install all build tools git clone https://github.com/paddlepaddle/paddle ``` -2. Install build tools. +2. Install build tools into a Docker image. ```bash cd paddle; docker build -t paddle:dev . ``` + Please be aware of the `.` at the end of the command, which refers to the [`./Dockerfile` file](https://github.com/PaddlePaddle/Paddle/blob/develop/Dockerfile). `docker build` follows instructions in this file to create a Docker image named `paddle:dev`, and installs building tools into it. + 3. Build from source. + This following command starts a Docker container that executes the Docker image `paddle:dev`, mapping the current directory to `/paddle/` in the container, and runs the default entry-point [`build.sh`](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh) as specified in the Dockefile. `build.sh` invokes `cmake` and `make` to build PaddlePaddle source code, which had been mapped to `/paddle`, and writes outputs to `/paddle/build`, which maps to `build` in the current source directory on the computer. + ```bash docker run -v $PWD:/paddle paddle:dev ``` - This builds a CUDA-enabled version and writes all binary outputs to directory `./build` of the local computer, other than the Docker container. If we want to build only the CPU part, we can type + Above command builds a CUDA-enabled version. If we want to build a CPU-only version, we can type ```bash docker run -e WITH_GPU=OFF -v $PWD:/paddle paddle:dev @@ -57,25 +61,21 @@ Nothing else. Not even Python and GCC, because you can install all build tools - Docker or virtual machine? - Some people compare Docker with VMs, but Docker doesn't virtualize any hardware, and it doesn't run a guest OS. + Some people compare Docker with VMs, but Docker doesn't virtualize any hardware nor running a guest OS, which means there is no compromise on the performance. - Why Docker? - Using a Docker image of build tools standardize the building environment, and easier for others to reproduce your problem, if there is any, and help. + Using a Docker image of build tools standardizes the building environment, which makes it easier for others to reproduce your problems and to help. Also, some build tools don't run on Windows or Mac or BSD, but Docker runs almost everywhere, so developers can use whatever computer they want. -- Can I don't use Docker? +- Can I choose not to use Docker? - Sure, you don't have to install build tools into a Docker image; instead, you can install them onto your local computer. This document exists because Docker would make the development way easier. + Sure, you don't have to install build tools into a Docker image; instead, you can install them in your local computer. This document exists because Docker would make the development way easier. - How difficult is it to learn Docker? - It takes you ten minutes to read [an introductory article](https://docs.docker.com/get-started) and saves you more than one hour to install all required build tools, configure them, and upgrade them when new versions of PaddlePaddle require some new tools. - -- Docker requires sudo - - An owner of a computer has the administrative privilege, a.k.a., sudo. If you use a shared computer for development, please ask the administrator to install and configure Docker. We will do our best to support rkt, another container technology that doesn't require sudo. + It takes you ten minutes to read [an introductory article](https://docs.docker.com/get-started) and saves you more than one hour to install all required build tools, configure them, especially when new versions of PaddlePaddle require some new tools. Not even to mention the time saved when other people trying to reproduce the issue you have. - Can I use my favorite IDE? @@ -93,8 +93,14 @@ Nothing else. Not even Python and GCC, because you can install all build tools - Does Docker do parallel building? - Our building Docker image runs a [Bash script](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh), which calls `make -j$(nproc)` to starts as many processes as the number of your processors. + Our building Docker image runs a [Bash script](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh), which calls `make -j$(nproc)` to starts as many processes as the number of your CPU cores. + +## Some Gotchas + +- Docker requires sudo + + An owner of a computer has the administrative privilege, a.k.a., sudo, and Docker requires this privilege to work properly. If you use a shared computer for development, please ask the administrator to install and configure Docker. We will do our best to support rkt, another container technology that doesn't require sudo. -- Docker on Windows/MacOS? +- Docker on Windows/MacOS builds slowly On Windows and MacOS, Docker containers run in a Linux VM. You might want to give this VM some more memory and CPUs so to make the building efficient. Please refer to [this issue](https://github.com/PaddlePaddle/Paddle/issues/627) for details. From 4b0235c1f2792cdecfe7d8f3e0bb1d0c57c6f361 Mon Sep 17 00:00:00 2001 From: Yi Wang Date: Fri, 25 Aug 2017 14:31:02 -0700 Subject: [PATCH 129/138] Update build.sh --- paddle/scripts/docker/build.sh | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/paddle/scripts/docker/build.sh b/paddle/scripts/docker/build.sh index 7bab814ae8..1798642022 100644 --- a/paddle/scripts/docker/build.sh +++ b/paddle/scripts/docker/build.sh @@ -63,12 +63,11 @@ cmake .. \ cat < Date: Fri, 25 Aug 2017 14:43:29 -0700 Subject: [PATCH 130/138] Run a specific test --- doc/howto/dev/build_cn.md | 6 ++++++ doc/howto/dev/build_en.md | 6 ++++++ 2 files changed, 12 insertions(+) diff --git a/doc/howto/dev/build_cn.md b/doc/howto/dev/build_cn.md index 0077d90118..79b4ff9d5a 100644 --- a/doc/howto/dev/build_cn.md +++ b/doc/howto/dev/build_cn.md @@ -53,6 +53,12 @@ docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest" ``` + 有时候我们只想运行一个特定的单元测试，比如 `memory_test`，我们可以 + + ```bash + docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest -V -R memory_test" + ``` + ## 为什么要 Docker 呀？ - 什么是 Docker? diff --git a/doc/howto/dev/build_en.md b/doc/howto/dev/build_en.md index 95752beba0..e1b55929f9 100644 --- a/doc/howto/dev/build_en.md +++ b/doc/howto/dev/build_en.md @@ -53,6 +53,12 @@ Nothing else. Not even Python and GCC, because you can install all build tools docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest" ``` + Sometimes we want to run a specific unit test, say `memory_test`, we can run + + ```bash + docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest -V -R memory_test" + ``` + ## Docker, Or Not? - What is Docker? From 97649bf9b251707803b2665dedf1ef8f929d8c88 Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Fri, 25 Aug 2017 22:08:24 +0000 Subject: [PATCH 131/138] fix codes in scatter --- paddle/operators/scatter_op.cc | 26 +++++++++++++------ paddle/operators/scatter_op.h | 6 ++--- .../v2/framework/tests/gradient_checker.py | 13 +++++----- .../v2/framework/tests/test_scatter_op.py | 1 - 4 files changed, 28 insertions(+), 18 deletions(-) diff --git a/paddle/operators/scatter_op.cc b/paddle/operators/scatter_op.cc index cf01ef6279..f901edefa2 100644 --- a/paddle/operators/scatter_op.cc +++ b/paddle/operators/scatter_op.cc @@ -24,8 +24,18 @@ class ScatterOp : public framework::OperatorWithKernel { protected: void InferShape(const framework::InferShapeContext &ctx) const override { - framework::DDim output_dims(ctx.Input("Ref")->dims()); - ctx.Output("Out")->Resize(output_dims); + PADDLE_ENFORCE_EQ(ctx.Input("Index")->dims().size(), 1, + "Update Index should be 1-D."); + PADDLE_ENFORCE_EQ(ctx.Input("Ref")->dims().size(), + ctx.Input("Updates")->dims().size(), + "Reference and Updates should have the same shape size"); + PADDLE_ENFORCE_EQ(ctx.Input("Updates")->dims()[0], + ctx.Input("Index")->dims()[0], + "Updates and Index should have same batch-size."); + framework::DDim data_dim(ctx.Input("Updates")->dims()); + for (int i = 1; i < data_dim.size(); ++i) + PADDLE_ENFORCE_EQ(data_dim[i], ctx.Input("Updates")->dims()[i]); + ctx.Output("Out")->Resize(ctx.Input("Ref")->dims()); } }; @@ -35,13 +45,13 @@ class ScatterGradOp : public framework::OperatorWithKernel { protected: void InferShape(const framework::InferShapeContext &ctx) const override { - auto Updates_grad = ctx.Output(framework::GradVarName("Updates")); - auto Updates = ctx.Input("Updates"); - auto Ref_grad = ctx.Output(framework::GradVarName("Ref")); - auto Ref = ctx.Input("Ref"); + auto *dUpdates = ctx.Output(framework::GradVarName("Updates")); + auto *Updates = ctx.Input("Updates"); + auto *dRef = ctx.Output(framework::GradVarName("Ref")); + auto *Ref = ctx.Input("Ref"); - Ref_grad->Resize(Ref->dims()); - Updates_grad->Resize(Updates->dims()); + dRef->Resize(Ref->dims()); + dUpdates->Resize(Updates->dims()); } }; diff --git a/paddle/operators/scatter_op.h b/paddle/operators/scatter_op.h index c2db3ae37c..e9595638a8 100644 --- a/paddle/operators/scatter_op.h +++ b/paddle/operators/scatter_op.h @@ -46,13 +46,13 @@ class ScatterGradientOpKernel : public framework::OpKernel { auto *dRef = ctx.Output(framework::GradVarName("Ref")); auto *dUpdates = ctx.Output(framework::GradVarName("Updates")); auto *Index = ctx.Input("Index"); - auto *dO = ctx.Input(framework::GradVarName("Out")); + auto *dOut = ctx.Input(framework::GradVarName("Out")); // In place gradient: dRef = dO - dRef->ShareDataWith(*dO); + dRef->ShareDataWith(*dOut); dUpdates->mutable_data(ctx.GetPlace()); // Gradient by Gather: dUpdates += dO[Index] - Gather(ctx.GetPlace(), dO, Index, dUpdates); + Gather(ctx.GetPlace(), dOut, Index, dUpdates); } }; diff --git a/python/paddle/v2/framework/tests/gradient_checker.py b/python/paddle/v2/framework/tests/gradient_checker.py index ac37671c77..abe0b5391a 100644 --- a/python/paddle/v2/framework/tests/gradient_checker.py +++ b/python/paddle/v2/framework/tests/gradient_checker.py @@ -82,6 +82,11 @@ def get_numeric_gradient(op, def product(dim): return reduce(lambda a, b: a * b, dim, 1) + def copy_tensor(): + for var_name in input_values: + tensor_ = local_scope.find_var(var_name).get_tensor() + tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace()) + # get the input tensor that we want to get it's numeric gradient. tensor_to_check = local_scope.find_var(input_to_check).get_tensor() tensor_size = product(tensor_to_check.get_dims()) @@ -92,9 +97,7 @@ def get_numeric_gradient(op, # we use a for loop to compute the gradient of every element. for i in xrange(tensor_size): if in_place: - for var_name in input_values: - tensor_ = local_scope.find_var(var_name).get_tensor() - tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace()) + copy_tensor() # get one input element throw it's index i. origin = tensor_to_check.get_float_element(i) @@ -105,9 +108,7 @@ def get_numeric_gradient(op, # plus delta to this element, run op and get the sum of the result tensor. if in_place: - for var_name in input_values: - tensor_ = local_scope.find_var(var_name).get_tensor() - tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace()) + copy_tensor() x_neg = origin - delta tensor_to_check.set_float_element(i, x_neg) y_neg = get_output() diff --git a/python/paddle/v2/framework/tests/test_scatter_op.py b/python/paddle/v2/framework/tests/test_scatter_op.py index 861fe6cf89..c1f9444889 100644 --- a/python/paddle/v2/framework/tests/test_scatter_op.py +++ b/python/paddle/v2/framework/tests/test_scatter_op.py @@ -30,7 +30,6 @@ class TestScatterGradOp(GradientChecker): output_np = numpy.copy(ref_np) output_np[index_np] += updates_np inputs = {'Ref': ref_np, 'Index': index_np, 'Updates': updates_np} - # check gradient self.check_grad( op, inputs, set(["Updates", "Ref"]), "Out", in_place=True) From 6f235553fd923d4b0b225fdc4a521570b03fbc24 Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Fri, 25 Aug 2017 22:20:20 +0000 Subject: [PATCH 132/138] scatter op fixed --- paddle/operators/scatter_op.cc | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/paddle/operators/scatter_op.cc b/paddle/operators/scatter_op.cc index f901edefa2..09a2f94dde 100644 --- a/paddle/operators/scatter_op.cc +++ b/paddle/operators/scatter_op.cc @@ -1,16 +1,16 @@ /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. -Licensed under the Apache License, Version 2.0 (the "License"); -you may not use this file except in compliance with the License. -You may obtain a copy of the License at + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at - http://www.apache.org/licenses/LICENSE-2.0 + http://www.apache.org/licenses/LICENSE-2.0 -Unless required by applicable law or agreed to in writing, software -distributed under the License is distributed on an "AS IS" BASIS, -WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -See the License for the specific language governing permissions and -limitations under the License. */ + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. */ #include "paddle/operators/scatter_op.h" #include "paddle/framework/ddim.h" From 852f341615808b6a5e6249b3b7c1f5f20fd22ec9 Mon Sep 17 00:00:00 2001 From: Yi Wang Date: Fri, 25 Aug 2017 16:48:52 -0700 Subject: [PATCH 133/138] Add clean build section --- doc/howto/dev/build_cn.md | 10 +++++++++- doc/howto/dev/build_en.md | 10 +++++++++- 2 files changed, 18 insertions(+), 2 deletions(-) diff --git a/doc/howto/dev/build_cn.md b/doc/howto/dev/build_cn.md index 79b4ff9d5a..d9d520893f 100644 --- a/doc/howto/dev/build_cn.md +++ b/doc/howto/dev/build_cn.md @@ -56,7 +56,15 @@ 有时候我们只想运行一个特定的单元测试，比如 `memory_test`，我们可以 ```bash - docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest -V -R memory_test" + nvidia-docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest -V -R memory_test" + ``` + +5. 清理 + + 有时候我们会希望清理掉已经下载的第三方依赖以及已经编译的二进制文件。此时只需要： + + ```bash + rm -rf build ``` ## 为什么要 Docker 呀？ diff --git a/doc/howto/dev/build_en.md b/doc/howto/dev/build_en.md index e1b55929f9..318bf3d384 100644 --- a/doc/howto/dev/build_en.md +++ b/doc/howto/dev/build_en.md @@ -56,7 +56,15 @@ Nothing else. Not even Python and GCC, because you can install all build tools Sometimes we want to run a specific unit test, say `memory_test`, we can run ```bash - docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest -V -R memory_test" + nvidia-docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest -V -R memory_test" + ``` + +5. Clean Build. + + Sometimes, we might want to clean all thirt-party dependents and built binaries. To do so, just + + ```bash + rm -rf build ``` ## Docker, Or Not? From bfeecfd3d25c5c04dbd7d000490e77454944d044 Mon Sep 17 00:00:00 2001 From: zchen0211 Date: Fri, 25 Aug 2017 23:54:46 +0000 Subject: [PATCH 134/138] fix problems --- paddle/operators/scatter_op.cc | 18 +++++++++--------- paddle/operators/scatter_op.cu | 18 +++++++++--------- .../v2/framework/tests/gradient_checker.py | 6 +++--- 3 files changed, 21 insertions(+), 21 deletions(-) diff --git a/paddle/operators/scatter_op.cc b/paddle/operators/scatter_op.cc index 09a2f94dde..f901edefa2 100644 --- a/paddle/operators/scatter_op.cc +++ b/paddle/operators/scatter_op.cc @@ -1,16 +1,16 @@ /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - Licensed under the Apache License, Version 2.0 (the "License"); - you may not use this file except in compliance with the License. - You may obtain a copy of the License at +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at - http://www.apache.org/licenses/LICENSE-2.0 + http://www.apache.org/licenses/LICENSE-2.0 - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the License for the specific language governing permissions and - limitations under the License. */ +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ #include "paddle/operators/scatter_op.h" #include "paddle/framework/ddim.h" diff --git a/paddle/operators/scatter_op.cu b/paddle/operators/scatter_op.cu index e6a6fa57d9..6716b47883 100644 --- a/paddle/operators/scatter_op.cu +++ b/paddle/operators/scatter_op.cu @@ -1,16 +1,16 @@ /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. - Licensed under the Apache License, Version 2.0 (the "License"); - you may not use this file except in compliance with the License. - You may obtain a copy of the License at +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at - http://www.apache.org/licenses/LICENSE-2.0 + http://www.apache.org/licenses/LICENSE-2.0 - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the License for the specific language governing permissions and - limitations under the License. */ +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ #define EIGEN_USE_GPU #include "paddle/operators/scatter_op.h" diff --git a/python/paddle/v2/framework/tests/gradient_checker.py b/python/paddle/v2/framework/tests/gradient_checker.py index abe0b5391a..9a7a7fbf5e 100644 --- a/python/paddle/v2/framework/tests/gradient_checker.py +++ b/python/paddle/v2/framework/tests/gradient_checker.py @@ -82,7 +82,7 @@ def get_numeric_gradient(op, def product(dim): return reduce(lambda a, b: a * b, dim, 1) - def copy_tensor(): + def restore_inputs(): for var_name in input_values: tensor_ = local_scope.find_var(var_name).get_tensor() tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace()) @@ -97,7 +97,7 @@ def get_numeric_gradient(op, # we use a for loop to compute the gradient of every element. for i in xrange(tensor_size): if in_place: - copy_tensor() + restore_inputs() # get one input element throw it's index i. origin = tensor_to_check.get_float_element(i) @@ -108,7 +108,7 @@ def get_numeric_gradient(op, # plus delta to this element, run op and get the sum of the result tensor. if in_place: - copy_tensor() + restore_inputs() x_neg = origin - delta tensor_to_check.set_float_element(i, x_neg) y_neg = get_output() From ec5e20c9f12e89e13b52978b8bb27997c77f059c Mon Sep 17 00:00:00 2001 From: Yi Wang Date: Fri, 25 Aug 2017 17:14:28 -0700 Subject: [PATCH 135/138] Remove stopped containers and dangling images --- doc/howto/dev/build_cn.md | 18 +++++++++++------- doc/howto/dev/build_en.md | 4 ++++ 2 files changed, 15 insertions(+), 7 deletions(-) diff --git a/doc/howto/dev/build_cn.md b/doc/howto/dev/build_cn.md index d9d520893f..0b911f7b75 100644 --- a/doc/howto/dev/build_cn.md +++ b/doc/howto/dev/build_cn.md @@ -7,7 +7,7 @@ 1. 一台电脑，可以装的是 Linux, BSD, Windows 或者 MacOS 操作系统，以及 1. Docker。 -不需要其他任何软件了。即便是 Python 和 GCC 都不需要，因为我们会把所有编译工具都安装进一个 Docker image 里。 +不需要依赖其他任何软件了。即便是 Python 和 GCC 都不需要，因为我们会把所有编译工具都安装进一个 Docker image 里。 ## 总体流程 @@ -17,7 +17,7 @@ git clone https://github.com/paddlepaddle/paddle ``` -2. 安装工具 +2. 安装开发工具到 Docker image 里 ```bash cd paddle; docker build -t paddle:dev . @@ -30,13 +30,13 @@ 以下命令启动一个 Docker container 来执行 `paddle:dev` 这个 Docker image，同时把当前目录（源码树根目录）映射为 container 里的 `/paddle` 目录，并且运行 `Dockerfile` 描述的默认入口程序 [`build.sh`](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/scripts/docker/build.sh)。这个脚本调用 `cmake` 和 `make` 来编译 `/paddle` 里的源码，结果输出到 `/paddle/build`，也就是本地的源码树根目录里的 `build` 子目录。 ```bash - docker run -v $PWD:/paddle paddle:dev + docker run --rm -v $PWD:/paddle paddle:dev ``` 上述命令编译出一个 CUDA-enabled 版本。如果我们只需要编译一个只支持 CPU 的版本，可以用 ```bash - docker run -e WITH_GPU=OFF -v $PWD:/paddle paddle:dev + docker run --rm -e WITH_GPU=OFF -v $PWD:/paddle paddle:dev ``` 4. 运行单元测试 @@ -44,19 +44,19 @@ 用本机的第一个 GPU 来运行包括 GPU 单元测试在内的所有单元测试： ```bash - NV_GPU=0 nvidia-docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest" + NV_GPU=0 nvidia-docker run --rm -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest" ``` 如果编译的时候我们用了 `WITH_GPU=OFF` 选项，那么编译过程只会产生 CPU-based 单元测试，那么我们也就不需要 nvidia-docker 来运行单元测试了。我们只需要： ```bash - docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest" + docker run --rm -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest" ``` 有时候我们只想运行一个特定的单元测试，比如 `memory_test`，我们可以 ```bash - nvidia-docker run -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest -V -R memory_test" + nvidia-docker run --rm -v $PWD:/paddle paddle:dev bash -c "cd /paddle/build; ctest -V -R memory_test" ``` 5. 清理 @@ -118,3 +118,7 @@ - 在 Windows/MacOS 上编译很慢 Docker 在 Windows 和 MacOS 都可以运行。不过实际上是运行在一个 Linux 虚拟机上。可能需要注意给这个虚拟机多分配一些 CPU 和内存，以保证编译高效。具体做法请参考[这个issue](https://github.com/PaddlePaddle/Paddle/issues/627)。 + +- 磁盘不够 + + 本文中的例子里，`docker run` 命令里都用了 `--rm` 参数，这样保证运行结束之后的 containers 不会保留在磁盘上。可以用 `docker ps -a` 命令看到停止后但是没有删除的 containers。`docker build` 命令有时候会产生一些中间结果，是没有名字的 images，也会占用磁盘。可以参考[这篇文章](https://zaiste.net/posts/removing_docker_containers/)来清理这些内容。 diff --git a/doc/howto/dev/build_en.md b/doc/howto/dev/build_en.md index 318bf3d384..d0048e3714 100644 --- a/doc/howto/dev/build_en.md +++ b/doc/howto/dev/build_en.md @@ -118,3 +118,7 @@ Nothing else. Not even Python and GCC, because you can install all build tools - Docker on Windows/MacOS builds slowly On Windows and MacOS, Docker containers run in a Linux VM. You might want to give this VM some more memory and CPUs so to make the building efficient. Please refer to [this issue](https://github.com/PaddlePaddle/Paddle/issues/627) for details. + +- Not enough disk space + + Examples in this article uses option `--rm` with the `docker run` command. This option ensures that stopped containers do not exist on hard disks. We can use `docker ps -a` to list all containers, including stopped. Sometimes `docker build` generates some intermediate dangling images, which also take disk space. To clean them, please refer to [this article](https://zaiste.net/posts/removing_docker_containers/). From 721b5020fae92600a0aa2c4093dbeeac63b597c6 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Sat, 26 Aug 2017 16:34:33 -0700 Subject: [PATCH 136/138] change predict size to label class_num --- python/paddle/v2/framework/tests/mnist.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index 9a0b109850..9b2dbed25c 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -181,7 +181,7 @@ images = data_layer(name='pixel', dims=[BATCH_SIZE, 784]) labels = data_layer(name='label', dims=[BATCH_SIZE]) fc1 = fc_layer(net=forward_net, input=images, size=100, act="sigmoid") fc2 = fc_layer(net=forward_net, input=fc1, size=100, act="sigmoid") -predict = fc_layer(net=forward_net, input=fc2, size=100, act="softmax") +predict = fc_layer(net=forward_net, input=fc2, size=10, act="softmax") cost = cross_entropy_layer(net=forward_net, input=predict, label=labels) init_net.complete_add_op(True) @@ -223,7 +223,7 @@ def test(cost_name): sum(error) / float(len(error)))) -PASS_NUM = 1 +PASS_NUM = 10 init_net.run(scope, dev_ctx) for pass_id in range(PASS_NUM): From 787cb8ce5d829435e5d45e8bc6bc51cfdcf49272 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Sat, 26 Aug 2017 16:36:28 -0700 Subject: [PATCH 137/138] reset pass num to 1 --- python/paddle/v2/framework/tests/mnist.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index 9b2dbed25c..a68f302f9c 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -223,7 +223,7 @@ def test(cost_name): sum(error) / float(len(error)))) -PASS_NUM = 10 +PASS_NUM = 1 init_net.run(scope, dev_ctx) for pass_id in range(PASS_NUM): From 3120ee5cfbbe6ecf3550b6a338a4c14afe6e4ebd Mon Sep 17 00:00:00 2001 From: dongzhihong Date: Sat, 26 Aug 2017 18:46:06 -0700 Subject: [PATCH 138/138] fix backward doc --- paddle/framework/backward.md | 28 +++++++++++++++++++++------- 1 file changed, 21 insertions(+), 7 deletions(-) diff --git a/paddle/framework/backward.md b/paddle/framework/backward.md index 74c001b06a..c8fa3fefe5 100644 --- a/paddle/framework/backward.md +++ b/paddle/framework/backward.md @@ -21,18 +21,32 @@ grad_op_builder(fengjiayi) given a forward network, it generates the backward network. We only care about the Gradients—`OutputGradients`,`InputGradients`. -1. bla bla bla (yuyang) +1. Op + + when the input forward network is a Op, return its gradient Operator Immediately. 2. NetOp - when the input forward network is a NetOp, it need to call the sub NetOp/Operators backward function recursively and ensure them done. During the process, we need to collect the `OutputGradients` name. + when the input forward network is a NetOp, it need to call the sub NetOp/Operators backward function recursively. During the process, we need to collect the `OutputGradients` name according to forward NetOp. + + **shared variable**. As illustrated in the pictures, two operator's `Output` `Gradient` will overwirte their shared input variable. + +

+
+ + 1. shared variable in two operators. + +

+ + Share variable between operators or same input variable used in multiple operators lead to a duplicate gradient variable. As demo show above, we need to rename gradient name recursively, and add a generic add operator replace the overwirte links. + +

+
- We share variable in the same scope, as a result, duplicate operator `OutputGradients` will overwirte then duplicate variable. + 2. replace shared variable gradient with `Add` Operator - ![./images/duplicate_op]() +

- Share variable between operators or same input variable used in multiple operators lead to a duplicate gradient variable. As demo show above, we need to rename gradient name recursively, and add a generic add operator instead. -![./images/duplicate_op2]() -​ Then collect the sub graph OutputGradients/InputGradients as the NetOp's and return it. +​ Then collect the sub graph `OutputGradients`/`InputGradients` as the NetOp's and return it.