diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/relu_grad_impl.cu b/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/relu_grad_impl.cu new file mode 100644 index 0000000000..9ffcf3245a --- /dev/null +++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/relu_grad_impl.cu @@ -0,0 +1,39 @@ +/** + * Copyright 2020 Huawei Technologies Co., Ltd + * + * 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 "backend/kernel_compiler/gpu/cuda_impl/relu_grad_impl.cuh" +#include "runtime/device/gpu/cuda_common.h" + +template +__global__ void CalReLUGradKernel(int size, T *dy, T *y, T *dx) { + for (int pos = blockIdx.x * blockDim.x + threadIdx.x; pos < size; pos += blockDim.x * gridDim.x) { + dx[pos] = y[pos] > static_cast(0) ? dy[pos] : static_cast(0); + } +} + +template +void CalReLUGrad(int size, T *dy, T *y, T *dx, cudaStream_t cuda_stream) { + CalReLUGradKernel<<>>(size, dy, y, dx); + return; +} + +template void CalReLUGrad(int size, double *dy, double *y, double *dx, cudaStream_t cuda_stream); +template void CalReLUGrad(int size, float *dy, float *y, float *dx, cudaStream_t cuda_stream); +template void CalReLUGrad(int size, half *dy, half *y, half *dx, cudaStream_t cuda_stream); +template void CalReLUGrad(int size, int8_t *dy, int8_t *y, int8_t *dx, cudaStream_t cuda_stream); +template void CalReLUGrad(int size, int16_t *dy, int16_t *y, int16_t *dx, cudaStream_t cuda_stream); +template void CalReLUGrad(int size, int32_t *dy, int32_t *y, int32_t *dx, cudaStream_t cuda_stream); +template void CalReLUGrad(int size, int64_t *dy, int64_t *y, int64_t *dx, cudaStream_t cuda_stream); diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/relu_grad_impl.cuh b/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/relu_grad_impl.cuh new file mode 100644 index 0000000000..1d1fbbde7c --- /dev/null +++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/relu_grad_impl.cuh @@ -0,0 +1,23 @@ +/** + * Copyright 2020 Huawei Technologies Co., Ltd + * + * 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. + */ + +#ifndef MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMP_RELU_GRAD_H_ +#define MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMP_RELU_GRAD_H_ + +#include "runtime/device/gpu/cuda_common.h" +template +void CalReLUGrad(int input_size, T *dy, T *y, T *dx, cudaStream_t cuda_stream); +#endif // MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMP_RELU_GRAD_H_ diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/relu_impl.cu b/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/relu_impl.cu index d7290dc4a4..961ad156d2 100644 --- a/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/relu_impl.cu +++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/relu_impl.cu @@ -38,7 +38,6 @@ template void CalReLU(int size, int8_t *input_addr, int8_t *output_addr, cudaStr template void CalReLU(int size, int16_t *input_addr, int16_t *output_addr, cudaStream_t cuda_stream); template void CalReLU(int size, int32_t *input_addr, int32_t *output_addr, cudaStream_t cuda_stream); template void CalReLU(int size, int64_t *input_addr, int64_t *output_addr, cudaStream_t cuda_stream); -template void CalReLU(int size, uint8_t *input_addr, uint8_t *output_addr, cudaStream_t cuda_stream); template __global__ void ReluV2Kernel(const size_t num, const T *x, T *y, uint32_t *mask) { @@ -79,7 +78,6 @@ template void ReluV2(const size_t num, const int8_t *x, int8_t *y, uint32_t *mas template void ReluV2(const size_t num, const int16_t *x, int16_t *y, uint32_t *mask, cudaStream_t cuda_stream); template void ReluV2(const size_t num, const int32_t *x, int32_t *y, uint32_t *mask, cudaStream_t cuda_stream); template void ReluV2(const size_t num, const int64_t *x, int64_t *y, uint32_t *mask, cudaStream_t cuda_stream); -template void ReluV2(const size_t num, const uint8_t *x, uint8_t *y, uint32_t *mask, cudaStream_t cuda_stream); template void ReluGradV2(const size_t num, const double *dy, const uint32_t *mask, double *dx, cudaStream_t cuda_stream); @@ -93,5 +91,3 @@ template void ReluGradV2(const size_t num, const int32_t *dy, const uint32_t *ma cudaStream_t cuda_stream); template void ReluGradV2(const size_t num, const int64_t *dy, const uint32_t *mask, int64_t *dx, cudaStream_t cuda_stream); -template void ReluGradV2(const size_t num, const uint8_t *dy, const uint32_t *mask, uint8_t *dx, - cudaStream_t cuda_stream); diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.cc index e4d781db17..e69167cae1 100644 --- a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.cc +++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.cc @@ -18,34 +18,6 @@ namespace mindspore { namespace kernel { -MS_REG_GPU_KERNEL_ONE( - ReluGrad, - KernelAttr().AddInputAttr(kNumberTypeFloat64).AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeFloat64), - ActivationGradGpuKernel, double) -MS_REG_GPU_KERNEL_ONE( - ReluGrad, - KernelAttr().AddInputAttr(kNumberTypeFloat32).AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32), - ActivationGradGpuKernel, float) -MS_REG_GPU_KERNEL_ONE( - ReluGrad, - KernelAttr().AddInputAttr(kNumberTypeFloat16).AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16), - ActivationGradGpuKernel, half) -MS_REG_GPU_KERNEL_ONE( - ReluGrad, KernelAttr().AddInputAttr(kNumberTypeInt64).AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeInt64), - ActivationGradGpuKernel, int64_t) -MS_REG_GPU_KERNEL_ONE( - ReluGrad, KernelAttr().AddInputAttr(kNumberTypeInt32).AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt32), - ActivationGradGpuKernel, int32_t) -MS_REG_GPU_KERNEL_ONE( - ReluGrad, KernelAttr().AddInputAttr(kNumberTypeInt16).AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeInt16), - ActivationGradGpuKernel, int16_t) -MS_REG_GPU_KERNEL_ONE( - ReluGrad, KernelAttr().AddInputAttr(kNumberTypeInt8).AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeInt8), - ActivationGradGpuKernel, int8_t) -MS_REG_GPU_KERNEL_ONE( - ReluGrad, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeUInt8), - ActivationGradGpuKernel, uint8_t) - MS_REG_GPU_KERNEL_ONE( ReLU6Grad, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32), diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.h b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.h index b97f7b93bd..30fabdb452 100644 --- a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.h +++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.h @@ -42,7 +42,7 @@ class ActivationGradGpuKernel : public GpuKernel { } T *dy = nullptr; T *y = nullptr; - if (mode_ == CUDNN_ACTIVATION_RELU || mode_ == CUDNN_ACTIVATION_ELU || mode_ == CUDNN_ACTIVATION_CLIPPED_RELU) { + if (mode_ == CUDNN_ACTIVATION_ELU || mode_ == CUDNN_ACTIVATION_CLIPPED_RELU) { dy = GetDeviceAddress(inputs, 0); y = GetDeviceAddress(inputs, 1); } else { @@ -125,7 +125,7 @@ class ActivationGradGpuKernel : public GpuKernel { void ResetResource() noexcept override { cudnn_handle_ = nullptr; activation_desc_ = nullptr; - mode_ = CUDNN_ACTIVATION_RELU; + mode_ = CUDNN_ACTIVATION_SIGMOID; data_descriptor_ = nullptr; is_null_input_ = false; input_size_list_.clear(); @@ -154,8 +154,7 @@ class ActivationGradGpuKernel : public GpuKernel { } private: - std::map kernel_map = {{"ReluGrad", CUDNN_ACTIVATION_RELU}, - {"ReLU6Grad", CUDNN_ACTIVATION_CLIPPED_RELU}, + std::map kernel_map = {{"ReLU6Grad", CUDNN_ACTIVATION_CLIPPED_RELU}, {"TanhGrad", CUDNN_ACTIVATION_TANH}, {"EluGrad", CUDNN_ACTIVATION_ELU}, {"SigmoidGrad", CUDNN_ACTIVATION_SIGMOID}}; diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_gpu_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_gpu_kernel.cc index 2556df5bc8..ebc04534d4 100644 --- a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_gpu_kernel.cc +++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_gpu_kernel.cc @@ -32,7 +32,5 @@ MS_REG_GPU_KERNEL_ONE(ReLU, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutpu ReLUGpuFwdKernel, int16_t) MS_REG_GPU_KERNEL_ONE(ReLU, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeInt8), ReLUGpuFwdKernel, int8_t) -MS_REG_GPU_KERNEL_ONE(ReLU, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeUInt8), - ReLUGpuFwdKernel, uint8_t) } // namespace kernel } // namespace mindspore diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_grad_gpu_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_grad_gpu_kernel.cc new file mode 100644 index 0000000000..fbfb62e887 --- /dev/null +++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_grad_gpu_kernel.cc @@ -0,0 +1,46 @@ +/** + * Copyright 2020 Huawei Technologies Co., Ltd + * + * 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 "backend/kernel_compiler/gpu/nn/relu_grad_gpu_kernel.h" + +namespace mindspore { +namespace kernel { +MS_REG_GPU_KERNEL_ONE( + ReluGrad, + KernelAttr().AddInputAttr(kNumberTypeFloat64).AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeFloat64), + ReluGradGpuFwdKernel, double) +MS_REG_GPU_KERNEL_ONE( + ReluGrad, + KernelAttr().AddInputAttr(kNumberTypeFloat32).AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32), + ReluGradGpuFwdKernel, float) +MS_REG_GPU_KERNEL_ONE( + ReluGrad, + KernelAttr().AddInputAttr(kNumberTypeFloat16).AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16), + ReluGradGpuFwdKernel, half) +MS_REG_GPU_KERNEL_ONE( + ReluGrad, KernelAttr().AddInputAttr(kNumberTypeInt64).AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeInt64), + ReluGradGpuFwdKernel, int64_t) +MS_REG_GPU_KERNEL_ONE( + ReluGrad, KernelAttr().AddInputAttr(kNumberTypeInt32).AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt32), + ReluGradGpuFwdKernel, int32_t) +MS_REG_GPU_KERNEL_ONE( + ReluGrad, KernelAttr().AddInputAttr(kNumberTypeInt16).AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeInt16), + ReluGradGpuFwdKernel, int16_t) +MS_REG_GPU_KERNEL_ONE( + ReluGrad, KernelAttr().AddInputAttr(kNumberTypeInt8).AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeInt8), + ReluGradGpuFwdKernel, int8_t) +} // namespace kernel +} // namespace mindspore diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_grad_gpu_kernel.h b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_grad_gpu_kernel.h new file mode 100644 index 0000000000..a00c459bfe --- /dev/null +++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_grad_gpu_kernel.h @@ -0,0 +1,99 @@ +/** + * Copyright 2020 Huawei Technologies Co., Ltd + * + * 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. + */ + +#ifndef MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_NN_RELU_GRAD_KERNEL_H_ +#define MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_NN_RELU_GRAD_KERNEL_H_ + +#include +#include +#include +#include "backend/kernel_compiler/gpu/gpu_kernel.h" +#include "backend/kernel_compiler/gpu/gpu_kernel_factory.h" +#include "backend/kernel_compiler/gpu/kernel_constants.h" +#include "backend/kernel_compiler/gpu/cuda_impl/relu_grad_impl.cuh" + +namespace mindspore { +namespace kernel { +template +class ReluGradGpuFwdKernel : public GpuKernel { + public: + ReluGradGpuFwdKernel() { ResetResource(); } + ~ReluGradGpuFwdKernel() override = default; + const std::vector &GetInputSizeList() const override { return input_size_list_; } + const std::vector &GetOutputSizeList() const override { return output_size_list_; } + const std::vector &GetWorkspaceSizeList() const override { return workspace_size_list_; } + + bool Launch(const std::vector &inputs, const std::vector &, + const std::vector &outputs, void *stream_ptr) override { + if (is_null_input_) { + return true; + } + T *dy = GetDeviceAddress(inputs, 0); + T *y = GetDeviceAddress(inputs, 1); + T *dx = GetDeviceAddress(outputs, 0); + + const int size = input_size_ / sizeof(T); + CalReLUGrad(size, dy, y, dx, reinterpret_cast(stream_ptr)); + + return true; + } + bool Init(const CNodePtr &kernel_node) override { + InitResource(); + size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node); + if (input_num != 2) { + MS_LOG(ERROR) << "Argument number is " << input_num << ", but ReluGradGpuKernel needs 2."; + return false; + } + auto input_shape = AnfAlgo::GetInputRealDeviceShapeIfExist(kernel_node, 0); + is_null_input_ = CHECK_NULL_INPUT(input_shape); + if (is_null_input_) { + MS_LOG(WARNING) << "ActivationGradGpuKernel input is null."; + } + size_t size = 1; + for (size_t i = 0; i < input_shape.size(); i++) { + size *= input_shape[i]; + } + input_size_ = size * sizeof(T); + + InitSizeLists(); + return true; + } + void ResetResource() noexcept override { + is_null_input_ = false; + input_size_list_.clear(); + output_size_list_.clear(); + workspace_size_list_.clear(); + input_size_ = 0; + } + + protected: + void InitSizeLists() override { + input_size_list_.push_back(input_size_); + output_size_list_.push_back(input_size_); + input_size_list_.push_back(input_size_); + } + + private: + bool is_null_input_; + std::vector input_size_list_; + std::vector output_size_list_; + std::vector workspace_size_list_; + size_t input_size_; +}; +} // namespace kernel +} // namespace mindspore + +#endif // MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_NN_RELU_GRAD_KERNEL_H_ diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_grad_v2_gpu_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_grad_v2_gpu_kernel.cc index 3e85ceda30..b0dd73a8a2 100644 --- a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_grad_v2_gpu_kernel.cc +++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_grad_v2_gpu_kernel.cc @@ -45,10 +45,5 @@ MS_REG_GPU_KERNEL_ONE( ReluGradV2, KernelAttr().AddInputAttr(kNumberTypeInt64).AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeInt64), ReluGradV2GpuKernel, int64_t) -MS_REG_GPU_KERNEL_ONE( - ReluGradV2, - KernelAttr().AddInputAttr(kNumberTypeUInt8).AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeUInt8), - ReluGradV2GpuKernel, uint8_t) - } // namespace kernel } // namespace mindspore diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_v2_gpu_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_v2_gpu_kernel.cc index 9fa07bd1ff..900f4e2cd3 100644 --- a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_v2_gpu_kernel.cc +++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/relu_v2_gpu_kernel.cc @@ -42,8 +42,5 @@ MS_REG_GPU_KERNEL_ONE( MS_REG_GPU_KERNEL_ONE( ReLUV2, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeUInt32), ReluV2GpuKernel, int64_t) -MS_REG_GPU_KERNEL_ONE( - ReLUV2, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeUInt32), - ReluV2GpuKernel, uint8_t) } // namespace kernel } // namespace mindspore