xutianbing
9 years ago
parent
b1f09f2788
commit
936301f157
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/* Copyright (c) 2016 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 "MulOp.h"
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namespace paddle {
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/**
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* mul operator
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* out = scaleT * out + scaleAB*(in1 * in2)
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*
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* \param outputs[0] output matrix, N * M
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* \param inputs[0] first input (sparse) matrix, N * K
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* \param inputs[1] second input matrix, K * M (non-transpose)
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*/
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template <DeviceType Device>
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class MulFunc : public FunctionBase {
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public:
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void init(const FuncConfig& config) override {
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scaleAB_ = config.get<real>("scaleAB");
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scaleT_ = config.get<real>("scaleT");
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}
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void calc(const BufferArgs& inputs, const BufferArgs& outputs) override {
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/// todo(tianbing), add more checks
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CHECK_EQ((size_t)1, inputs.size());
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CHECK_EQ((size_t)2, outputs.size());
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CHECK(inputs[0].data() && inputs[1].data() && outputs[0].data());
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CHECK_EQ(inputs[0].shape().ndims(), (size_t)2);
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CHECK_EQ(inputs[1].shape().ndims(), (size_t)2);
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CHECK_EQ(outputs[0].shape().ndims(), (size_t)2);
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CHECK_EQ(outputs[0].getArgType(), ASSIGN_TO);
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CHECK(inputs[0].isSparse()) << "SparseMatrix requried here";
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const auto in1_mat = inputs[0].sparse().SparseMatrix<Device>();
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auto out_mat = outputs[0].matrix<Device>();
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const auto in2_mat = inputs[1].matrix<Device>();
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MulOp<Device>(out_mat, in1_mat, in2_mat, scaleAB_, scaleT_);
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}
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private:
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real scaleAB_;
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real scaleT_;
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};
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#ifndef PADDLE_ONLY_CPU
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REGISTER_TYPED_FUNC(MulOp, GPU, MulFunc);
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#endif
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} // namespace paddle
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@ -0,0 +1,30 @@
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/* Copyright (c) 2016 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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#pragma once
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#include "Function.h"
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#include "paddle/math/Matrix.h"
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#include "paddle/math/SparseMatrix.h"
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namespace paddle {
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template <DeviceType DType>
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void MulOp(GpuMatrix& out,
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const GpuSparseMatrix& a,
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const GpuMatrix& b,
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real scaleAB,
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real scaleT);
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} // namespace paddle
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@ -0,0 +1,57 @@
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/* Copyright (c) 2016 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 "hl_base.h"
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#include "MulOp.h"
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#include "paddle/math/Matrix.h"
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#include "paddle/math/SparseMatrix.h"
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namespace paddle {
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/**
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* out = scale_t * out + scale_ab * (a * b)
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*/
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template <>
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void MulOp<DEVICE_TYPE_GPU>(GpuMatrix& out,
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const GpuSparseMatrix& a,
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const GpuMatrix& b,
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real scale_ab,
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real scale_t) {
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CHECK(out.isContiguous());
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CHECK(b.isContiguous());
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CHECK(b.useGpu_ == true) << "Matrix type are not equal";
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CHECK(!out.trans_ && !b.trans_) << "not supported";
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if (!a.trans_) {
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CHECK(out.width_ == b.width_ && out.height_ == a.height_
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&& a.width_ == b.height_) << "Matrix dimensions are not equal";
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} else {
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CHECK(out.width_ == b.width_ && out.height_ == a.width_
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&& a.height_ == b.height_) << "Matrix dimensions are not equal";
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}
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hl_trans_op_t a_trans = a.trans_ ? HPPL_OP_T : HPPL_OP_N;
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hl_sparse_matrix_s a_data = a.sMatrix_.get();
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real* b_data = b.data_;
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real* out_data = out.data_;
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hl_matrix_csr_mul_dense(a_data,
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a_trans,
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b_data,
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HPPL_OP_N,
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out_data,
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out.height_,
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out.width_,
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b.height_,
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scale_ab,
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scale_t);
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}
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} // namespace paddle
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@ -0,0 +1,56 @@
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/* Copyright (c) 2016 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 <gtest/gtest.h>
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#include "FunctionTest.h"
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#include "paddle/math/Matrix.h"
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#include "paddle/math/SparseMatrix.h"
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#include "paddle/testing/TestUtil.h"
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using namespace paddle; // NOLINT
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void testSpMatrixMul(int M, int N, int K, real rate, real scale1, real scale2) {
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/// todo(tianbing) check CPU/GPU
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const auto gpuFunc = FunctionBase::funcRegistrar_.createByType("MulOP-GPU");
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gpuFunc->init(FuncConfig().set("scaleAB", scale1).set("scaleT", scale2));
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int nnz = M * K * rate;
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auto gpuA = std::make_shared<GpuSparseMatrix>(M, K, nnz);
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const auto gpuB = std::make_shared<GpuMatrix>(K, N);
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const auto gpuOut = std::make_shared<GpuMatrix>(M, N);
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gpuA->randomizeUniform();
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gpuB->randomizeUniform();
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gpuOut->randomizeUniform();
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BufferArgs inputs;
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BufferArgs outputs;
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inputs.addArg(*gpuA);
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inputs.addArg(*gpuB);
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outputs.addArg(*gpuOut);
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gpuFunc->calc(inputs, outputs);
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}
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TEST(SMatrix, sMatrixMul) {
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for (auto M : {1, 40, 128, 200}) {
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for (auto N : {100, 2000, 20480}) {
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for (auto K : {100, 512, 1024}) {
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/// todo(tianbing), add scaleAB and scaleT
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VLOG(3) << " M=" << M << " N=" << N << " K=" << K;
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testSpMatrixMul(M, N, K, 0.05, 1, 1);
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}
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}
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}
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}
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