Implement the GPU kernel of fc operator (#19687)
* Refine the codes related to fc op. * Add GPU implementation for fc functor. * Apply fc_fuse_pass in GPU inference. test=develop * Change the cmake for fc op. * Change PADDLE_ENFORCE to PADDLE_ENFORCE_EQ. * Add an attribute to set the activation type in fc_op. * Enhance the unittest of fc_op. test=develop * Remove the declaration of FCOpGrad back to the header file. test=develop * Set default value for newly added arguments in test_fc_op. test=developexpand_as_op_1
Yiqun Liu
5 years ago
committed by
GitHub
parent
22301115d0
commit
a65c728e5d
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/* Copyright (c) 2019 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/operators/fc_op.h"
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namespace ops = paddle::operators;
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REGISTER_OP_CUDA_KERNEL(
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fc, ops::FCOpKernel<paddle::platform::CUDADeviceContext, float>,
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ops::FCOpKernel<paddle::platform::CUDADeviceContext, double>);
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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/operators/math/fc.h"
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#include "paddle/fluid/operators/jit/kernels.h"
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#include "paddle/fluid/operators/math/blas.h"
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namespace paddle {
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namespace operators {
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namespace math {
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template <typename T>
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class FCFunctor<platform::CPUDeviceContext, T> {
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public:
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void operator()(const platform::CPUDeviceContext& context, const int M,
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const int N, const int K, const T* X, const T* W, T* Y,
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const T* B = nullptr, bool relu = false) {
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auto blas = math::GetBlas<platform::CPUDeviceContext, T>(context);
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blas.MatMul(M, N, K, X, W, Y);
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if (B == NULL) {
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return;
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}
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if (relu) {
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auto compute =
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jit::KernelFuncs<jit::VAddReluTuple<T>, platform::CPUPlace>::Cache()
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.At(N);
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for (int i = 0; i < M; i++) {
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T* dst = Y + i * N;
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compute(B, dst, dst, N);
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}
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} else {
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auto compute =
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jit::KernelFuncs<jit::VAddTuple<T>, platform::CPUPlace>::Cache().At(
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N);
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#ifdef PADDLE_WITH_MKLML
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#pragma omp parallel for
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#endif
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for (int i = 0; i < M; i++) {
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T* dst = Y + i * N;
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compute(B, dst, dst, N);
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}
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}
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}
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};
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template class FCFunctor<platform::CPUDeviceContext, float>;
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template class FCFunctor<platform::CPUDeviceContext, double>;
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} // namespace math
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} // namespace operators
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} // namespace paddle
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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 <algorithm>
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#include "paddle/fluid/operators/math/blas.h"
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#include "paddle/fluid/operators/math/fc.h"
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namespace paddle {
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namespace operators {
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namespace math {
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template <typename T, bool DoRelu>
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__global__ void InplaceAddReluKernel(const T* bias, T* data, int M, int N) {
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for (int i = blockIdx.x; i < M; i += gridDim.x) {
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int index = i * N + threadIdx.x;
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for (int j = threadIdx.x; j < N; j += blockDim.x) {
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T tmp = data[index] + bias[j];
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if (DoRelu) {
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data[index] = (tmp > 0) ? tmp : 0;
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} else {
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data[index] = tmp;
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}
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index += blockDim.x;
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}
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}
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}
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template <typename T>
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class FCFunctor<platform::CUDADeviceContext, T> {
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public:
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void operator()(const platform::CUDADeviceContext& context, const int M,
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const int N, const int K, const T* X, const T* W, T* Y,
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const T* B = nullptr, bool relu = false) {
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auto blas = math::GetBlas<platform::CUDADeviceContext, T>(context);
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blas.GEMM(false, false, M, N, K, static_cast<T>(1.0), X, K, W, N,
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static_cast<T>(0.0), Y, N);
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if (B == NULL) {
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return;
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}
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const int kThreadsPerBlock = 1024;
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int max_threads = context.GetMaxPhysicalThreadCount();
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int num_threads = std::min(kThreadsPerBlock, (((N + 31) >> 5) << 5));
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int num_blocks = std::max(max_threads / num_threads, 1);
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if (relu) {
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InplaceAddReluKernel<
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T, true><<<num_blocks, num_threads, 0, context.stream()>>>(B, Y, M,
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N);
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} else {
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InplaceAddReluKernel<
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T, false><<<num_blocks, num_threads, 0, context.stream()>>>(B, Y, M,
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N);
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}
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}
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};
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template class FCFunctor<platform::CUDADeviceContext, float>;
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template class FCFunctor<platform::CUDADeviceContext, double>;
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} // namespace math
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} // namespace operators
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} // namespace paddle
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@ -0,0 +1,34 @@
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/* Copyright (c) 2019 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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#pragma once
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#include <string>
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#include "paddle/fluid/platform/device_context.h"
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namespace paddle {
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namespace operators {
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namespace math {
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template <typename DeviceContext, typename T>
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class FCFunctor {
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public:
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void operator()(const DeviceContext& context, const int M, const int N,
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const int K, const T* X, const T* W, T* Y,
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const T* B = nullptr, bool relu = false);
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};
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} // namespace math
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} // namespace operators
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} // namespace paddle
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@ -1,55 +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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#pragma once
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#include "paddle/fluid/operators/jit/kernels.h"
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#include "paddle/fluid/operators/math/blas.h"
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namespace paddle {
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namespace operators {
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namespace math {
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template <typename DeviceContext, typename T>
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inline void FCCompute(const BlasT<DeviceContext, T>& blas, const int M,
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const int N, const int K, const T* X, const T* W, T* Y,
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const T* B = NULL, bool relu = false) {
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blas.MatMul(M, N, K, X, W, Y);
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if (B == NULL) {
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return;
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}
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if (relu) {
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auto compute =
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jit::KernelFuncs<jit::VAddReluTuple<T>, platform::CPUPlace>::Cache().At(
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N);
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for (int i = 0; i < M; i++) {
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T* dst = Y + i * N;
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compute(B, dst, dst, N);
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}
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} else {
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auto compute =
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jit::KernelFuncs<jit::VAddTuple<T>, platform::CPUPlace>::Cache().At(N);
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#ifdef PADDLE_WITH_MKLML
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#pragma omp parallel for
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#endif
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for (int i = 0; i < M; i++) {
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T* dst = Y + i * N;
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compute(B, dst, dst, N);
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}
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}
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}
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} // namespace math
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} // namespace operators
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} // namespace paddle
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