wehub-resource-sync
117 lines
4.6 KiB
C++
117 lines
4.6 KiB
C++
// Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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//
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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/phi/kernels/conv_kernel.h"
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#include "paddle/phi/backends/context_pool.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/kernel_registry.h"
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#ifdef PADDLE_WITH_HIP
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#include "paddle/phi/kernels/gpudnn/conv_miopen_helper.h"
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#else
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#include "paddle/phi/kernels/gpudnn/conv_cudnn_v7.h"
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#endif
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#ifdef PADDLE_WITH_CUDNN_FRONTEND
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// clang-format off
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#include "paddle/phi/backends/dynload/cudnn_frontend.h"
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#include "paddle/phi/kernels/autotune/cache.h"
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#include "paddle/phi/kernels/gpudnn/conv_cudnn_frontend.h"
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// clang-format on
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#endif
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namespace phi {
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template <typename T, typename Context>
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void ConvCudnnKernel(const Context& dev_ctx,
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const DenseTensor& input,
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const DenseTensor& filter,
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const std::vector<int>& strides,
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const std::vector<int>& paddings_t,
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const std::string& padding_algorithm,
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const std::vector<int>& dilations_t,
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int groups,
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const std::string& data_format,
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DenseTensor* output);
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template <typename T, typename Context>
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void DepthwiseConvCudnnKernel(const Context& dev_ctx,
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const DenseTensor& input,
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const DenseTensor& filter,
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const std::vector<int>& strides,
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const std::vector<int>& paddings,
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const std::string& padding_algorithm,
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int groups,
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const std::vector<int>& dilations,
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const std::string& data_format,
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DenseTensor* out) {
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ConvCudnnKernel<T>(dev_ctx,
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input,
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filter,
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strides,
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paddings,
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padding_algorithm,
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dilations,
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groups,
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data_format,
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out);
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}
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template <typename T, typename Context>
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void ConvCudnnGradKernel(const Context& dev_ctx,
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const DenseTensor& input,
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const DenseTensor& filter,
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const DenseTensor& output_grad,
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const std::vector<int>& strides_t,
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const std::vector<int>& paddings_t,
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const std::string& padding_algorithm,
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const std::vector<int>& dilations_t,
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int groups,
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const std::string& data_format,
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DenseTensor* input_grad,
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DenseTensor* filter_grad);
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template <typename T, typename Context>
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void DepthwiseConvCudnnGradKernel(const Context& dev_ctx,
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const DenseTensor& input,
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const DenseTensor& filter,
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const DenseTensor& out_grad,
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const std::vector<int>& strides,
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const std::vector<int>& paddings,
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const std::string& padding_algorithm,
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int groups,
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const std::vector<int>& dilations,
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const std::string& data_format,
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DenseTensor* input_grad,
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DenseTensor* filter_grad) {
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ConvCudnnGradKernel<T>(dev_ctx,
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input,
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filter,
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out_grad,
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strides,
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paddings,
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padding_algorithm,
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dilations,
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groups,
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data_format,
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input_grad,
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filter_grad);
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}
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} // namespace phi
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