Yang Yang
8 years ago
commit
5229ccbdc7
@ -1,119 +0,0 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/fluid/framework/tensor_util.h"
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namespace paddle {
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namespace framework {
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template <typename Predicate, typename DevCtx>
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struct AnyDTypeVisitor {
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Predicate predicate_;
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const Tensor& tensor_;
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const DevCtx& ctx_;
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Tensor* out_;
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AnyDTypeVisitor(Predicate predicate, const Tensor& tensor, const DevCtx& ctx,
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Tensor* out)
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: predicate_(predicate), tensor_(tensor), ctx_(ctx), out_(out) {}
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template <typename T>
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void operator()() const {
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auto t = EigenVector<T>::Flatten(tensor_);
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auto o = EigenScalar<bool>::From(*out_);
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// return any of predicate_(t) is true.
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o.device(*ctx_.eigen_device()) = predicate_(t).any();
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}
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};
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template <typename Predicate, typename DevCtx>
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inline void AnyImpl(Predicate predicate, const framework::Tensor& tensor,
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const DevCtx& ctx, framework::Tensor* out) {
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VisitDataType(ToDataType(tensor.type()), AnyDTypeVisitor<Predicate, DevCtx>(
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predicate, tensor, ctx, out));
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}
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template <typename Predicate>
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struct AnyVisitor : public boost::static_visitor<bool> {
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const framework::Tensor& tensor_;
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Predicate predicate_;
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AnyVisitor(const framework::Tensor& tensor, Predicate predicate)
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: tensor_(tensor), predicate_(std::move(predicate)) {}
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template <typename Place>
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bool operator()(const Place& place) const {
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framework::Tensor out;
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out.Resize({1});
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out.mutable_data<bool>(place);
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auto* ctx = platform::DeviceContextPool::Instance().GetByPlace(place);
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AnyImpl(predicate_, tensor_, *ctx, &out);
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return this->GetResult(out, place);
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}
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bool GetResult(const framework::Tensor& out,
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const platform::CUDAPlace& gpu) const {
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platform::CPUPlace cpu;
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framework::Tensor tmp;
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tmp.Resize({1});
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tmp.mutable_data<bool>(cpu);
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auto gpuctx = platform::DeviceContextPool::Instance().Get(gpu);
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gpuctx->Wait();
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Copy(out, cpu, *gpuctx, &tmp);
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gpuctx->Wait();
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return GetResult(tmp, cpu);
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}
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bool GetResult(const framework::Tensor& out,
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const platform::CPUPlace& cpu) const {
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return *out.data<bool>();
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}
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};
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template <typename Predicate>
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inline bool Any(const framework::Tensor& tensor, Predicate predicate) {
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AnyVisitor<Predicate> visitor(tensor, predicate);
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auto place = tensor.place();
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return platform::VisitPlace(place, visitor);
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}
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struct HasNANPredicate {
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template <typename T>
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auto operator()(const T& eigen_vec) const
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-> decltype(std::declval<T>().isnan()) {
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// Cast eigen_vector to vector of bool. true if is inf.
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return eigen_vec.isnan();
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}
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};
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bool HasNAN(const framework::Tensor& tensor) {
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HasNANPredicate predicate;
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return Any(tensor, predicate);
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}
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struct HasInfPredicate {
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template <typename T>
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auto operator()(const T& eigen_vec) const
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-> decltype(std::declval<T>().isinf()) {
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// Cast eigen_vector to vector of bool. true if is inf.
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return eigen_vec.isinf();
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}
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};
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bool HasInf(const framework::Tensor& tensor) {
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HasInfPredicate predicate;
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return Any(tensor, predicate);
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}
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} // namespace framework
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} // namespace paddle
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@ -0,0 +1 @@
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tensor_util.cc
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File diff suppressed because it is too large
Load Diff
@ -0,0 +1,64 @@
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/fluid/operators/batch_size_like.h"
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namespace paddle {
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namespace operators {
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void BatchSizeLikeOp::InferShape(framework::InferShapeContext *ctx) const {
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PADDLE_ENFORCE(ctx->HasInput("Input"),
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"Input(Input) of %s should not be null.", Type());
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PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) of %s should not be null.",
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Type());
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auto &shape = ctx->Attrs().Get<std::vector<int>>("shape");
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PADDLE_ENFORCE_GT(shape.size(), 0);
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std::vector<int64_t> shape_int64(shape.size(), 0);
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std::transform(shape.begin(), shape.end(), shape_int64.begin(),
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[](int a) { return static_cast<int64_t>(a); });
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auto output_dim = framework::make_ddim(shape_int64);
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int input_dim_idx = ctx->Attrs().Get<int>("input_dim_idx");
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PADDLE_ENFORCE_GE(input_dim_idx, 0);
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PADDLE_ENFORCE_GT(ctx->GetInputDim("Input").size(), input_dim_idx);
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int output_dim_idx = ctx->Attrs().Get<int>("output_dim_idx");
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PADDLE_ENFORCE_GE(output_dim_idx, 0);
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PADDLE_ENFORCE_GT(static_cast<int>(shape.size()), output_dim_idx);
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output_dim[output_dim_idx] = ctx->GetInputDim("Input")[input_dim_idx];
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ctx->SetOutputDim("Out", output_dim);
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}
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BatchSizeLikeOpMaker::BatchSizeLikeOpMaker(OpProto *proto,
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OpAttrChecker *op_checker)
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: framework::OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("Input",
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"(Tensor) Tensor "
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"whose input_dim_idx'th dimension specifies the batch_size");
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AddOutput("Out",
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"(Tensor) Tensor of specified shape will be filled "
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"with the specified value");
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AddAttr<std::vector<int>>("shape", "(vector<int>) The shape of the output");
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AddAttr<int>("input_dim_idx",
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"(int, default 0) The index of input's batch size dimension")
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.SetDefault(0);
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AddAttr<int>("output_dim_idx",
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"(int, default 0) The index of output's batch size dimension")
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.SetDefault(0);
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}
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} // namespace operators
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} // namespace paddle
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@ -0,0 +1,36 @@
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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|
you may not use this file except in compliance with the License.
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|
You may obtain a copy of the License at
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|
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|
http://www.apache.org/licenses/LICENSE-2.0
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|
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|
Unless required by applicable law or agreed to in writing, software
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|
distributed under the License is distributed on an "AS IS" BASIS,
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|
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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|
See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/operators/math/math_function.h"
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namespace paddle {
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namespace operators {
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class BatchSizeLikeOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext *ctx) const override;
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};
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class BatchSizeLikeOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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BatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker);
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};
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} // namespace operators
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} // namespace paddle
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