mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-14 18:17:44 +00:00
Average pool backward deviceOP and example (#797)
* Add avgpool bwd reference code
* Refine naming
* Fix invalid in_element op in ref_conv
* Add example (only reference now)
* Add the full example of avgpool bwd
* Fix copyright
* Imitate MakeDescriptor from transform_conv_bwd_data_to_gemm_v1.hpp
* rename channel to c from k
* Arrange the code
* Imitate the argument from conv bwd
* Implement invoker
* Fix order of parameter in example
* Refactor reference code for different dimension
* Support different stride
* Check if argument is valid
* Fix kernel parameter for NDHWC, fastest dimension C is not reduced
* Add more data type in example
* Fix bug in example
* calculate Do Ho Wo according to the dilation
* Remove useless header
* Add comment in reference code
* Add layout parameter
* Remove layout in derived class
* Refine reference comment
[ROCm/composable_kernel commit: 578142db3a]
This commit is contained in:
rocking
3
example/51_avgpool3d_bwd/CMakeLists.txt
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3
example/51_avgpool3d_bwd/CMakeLists.txt
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add_example_executable(example_avgpool3d_bwd_bf16 avgpool3d_bwd_bf16.cpp)
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add_example_executable(example_avgpool3d_bwd_fp16 avgpool3d_bwd_fp16.cpp)
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add_example_executable(example_avgpool3d_bwd_fp32 avgpool3d_bwd_fp32.cpp)
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62
example/51_avgpool3d_bwd/avgpool3d_bwd_bf16.cpp
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62
example/51_avgpool3d_bwd/avgpool3d_bwd_bf16.cpp
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
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#include <iostream>
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#include "ck/ck.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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#include "ck/tensor_operation/gpu/device/impl/device_avgpool3d_bwd_ndhwc_ndhwc.hpp"
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#include "avgpool3d_bwd_common.hpp"
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using DOutDataType = ck::bhalf_t;
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using DInDataType = ck::bhalf_t;
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using ComputeDataType = float;
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#if 1
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using DOutLayout = ck::tensor_layout::convolution::NDHWC;
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using DInLayout = ck::tensor_layout::convolution::NDHWC;
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#else
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using DOutLayout = ck::tensor_layout::convolution::NCDHW;
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using DInLayout = ck::tensor_layout::convolution::NCDHW;
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#endif
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using DevicePoolBwdInstance =
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ck::tensor_operation::device::DeviceAvgPool3dBwd_NDHWC_NDHWC<DOutDataType,
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DInDataType,
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ComputeDataType,
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64, // BlockSize
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64, // ReduceMThreadClusterSize
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1, // ReduceKThreadClusterSize
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1, // ReduceMThreadSliceSize
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1, // ReduceKThreadSliceSize
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1>; // InSrcOutDstVectorSize
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int main()
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{
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std::vector<ck::index_t> window_lengths = {5, 5, 5};
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std::vector<ck::index_t> window_strides = {2, 2, 2};
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std::vector<ck::index_t> window_dilations = {2, 2, 2};
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std::vector<ck::index_t> dinput_left_pads = {0, 0, 0};
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std::vector<ck::index_t> dinput_right_pads = {0, 0, 0};
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ck::index_t N = 1;
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ck::index_t C = 16;
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ck::index_t Di = 40;
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ck::index_t Hi = 40;
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ck::index_t Wi = 40;
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pool3d_bwd_test<DevicePoolBwdInstance, DOutDataType, DInDataType, DOutLayout, DInLayout>(
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true,
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false,
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N,
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C,
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Di,
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Hi,
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Wi,
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window_lengths,
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window_strides,
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window_dilations,
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dinput_left_pads,
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dinput_right_pads);
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}
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147
example/51_avgpool3d_bwd/avgpool3d_bwd_common.hpp
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147
example/51_avgpool3d_bwd/avgpool3d_bwd_common.hpp
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
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#include <iostream>
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#include "ck/ck.hpp"
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#include "ck/library/utility/check_err.hpp"
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#include "ck/library/utility/device_memory.hpp"
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#include "ck/library/utility/host_tensor.hpp"
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#include "ck/library/utility/host_tensor_generator.hpp"
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#include "ck/library/utility/literals.hpp"
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#include "ck/library/reference_tensor_operation/cpu/reference_avgpool_bwd.hpp"
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template <typename TensorLayout>
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std::vector<ck::index_t> f_tensor_strides_ncdhw(ck::index_t N_,
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ck::index_t C_,
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ck::index_t D,
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ck::index_t H,
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ck::index_t W,
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TensorLayout layout)
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{
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using namespace ck::literals;
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(void)N_;
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if constexpr(ck::is_same<decltype(layout), ck::tensor_layout::convolution::NCDHW>::value)
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return {C_ * D * H * W, D * H * W, H * W, W, 1_uz};
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else if constexpr(ck::is_same<decltype(layout), ck::tensor_layout::convolution::NDHWC>::value)
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return {D * C_ * H * W, 1_uz, C_ * H * W, W * C_, C_};
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};
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template <typename TensorLayout>
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HostTensorDescriptor f_host_tensor_descriptor(std::size_t N_,
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std::size_t C_,
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std::size_t D,
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std::size_t H,
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std::size_t W,
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TensorLayout layout)
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{
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using namespace ck::literals;
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if constexpr(ck::is_same<decltype(layout), ck::tensor_layout::convolution::NCDHW>::value)
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{
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return HostTensorDescriptor({N_, C_, D, H, W}, {C_ * D * H * W, D * H * W, H * W, W, 1_uz});
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}
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else if constexpr(ck::is_same<decltype(layout), ck::tensor_layout::convolution::NDHWC>::value)
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{
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return HostTensorDescriptor({N_, C_, D, H, W},
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{D * C_ * H * W, 1_uz, C_ * H * W, W * C_, C_});
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}
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};
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template <typename DevicePoolBwdInstance,
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typename DOutDataType,
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typename DInDataType,
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typename DOutLayout,
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typename DInLayout>
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bool pool3d_bwd_test(bool do_verification,
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bool time_kernel,
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ck::index_t N,
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ck::index_t C,
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ck::index_t Di,
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ck::index_t Hi,
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ck::index_t Wi,
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std::vector<ck::index_t> window_lengths,
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std::vector<ck::index_t> window_strides,
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std::vector<ck::index_t> window_dilations,
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std::vector<ck::index_t> dinput_left_pads,
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std::vector<ck::index_t> dinput_right_pads)
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{
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auto OutSpatialLength = [&](auto InSpatialLength, int index) {
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ck::index_t left_pad = dinput_left_pads[index];
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ck::index_t right_pad = dinput_right_pads[index];
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ck::index_t window_len = window_lengths[index];
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ck::index_t stride = window_strides[index];
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ck::index_t dilation = window_dilations[index];
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ck::index_t eff = (window_len - 1) * dilation + 1;
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return (InSpatialLength + left_pad + right_pad - eff) / stride + 1;
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};
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ck::index_t Do = OutSpatialLength(Di, 0);
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ck::index_t Ho = OutSpatialLength(Hi, 1);
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ck::index_t Wo = OutSpatialLength(Wi, 2);
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Tensor<DOutDataType> dout(f_host_tensor_descriptor(N, C, Do, Ho, Wo, DOutLayout{}));
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Tensor<DInDataType> din_dev(f_host_tensor_descriptor(N, C, Di, Hi, Wi, DInLayout{}));
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Tensor<DInDataType> din_host(f_host_tensor_descriptor(N, C, Di, Hi, Wi, DInLayout{}));
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std::cout << "dout: " << dout.mDesc << std::endl;
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std::cout << "din_host: " << din_host.mDesc << std::endl;
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dout.GenerateTensorValue(GeneratorTensor_3<DOutDataType>{0.0, 1.0});
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DeviceMem dout_device_buf(sizeof(DOutDataType) * dout.mDesc.GetElementSpaceSize());
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DeviceMem din_device_buf(sizeof(DInDataType) * din_dev.mDesc.GetElementSpaceSize());
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dout_device_buf.ToDevice(dout.mData.data());
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din_device_buf.SetZero();
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auto pool = DevicePoolBwdInstance{};
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auto invoker_ptr = pool.MakeInvokerPointer();
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auto argument_ptr =
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pool.MakeArgumentPointer(static_cast<DOutDataType*>(dout_device_buf.GetDeviceBuffer()),
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static_cast<DInDataType*>(din_device_buf.GetDeviceBuffer()),
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{N, C, Do, Ho, Wo},
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{N, C, Di, Hi, Wi},
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f_tensor_strides_ncdhw(N, C, Do, Ho, Wo, DOutLayout{}),
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f_tensor_strides_ncdhw(N, C, Di, Hi, Wi, DInLayout{}),
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window_lengths,
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window_strides,
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window_dilations,
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dinput_left_pads,
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dinput_right_pads);
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if(!pool.IsSupportedArgument(argument_ptr.get()))
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{
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throw std::runtime_error("wrong! device_op with the specified compilation parameters does "
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"not support this problem");
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}
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float ave_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, time_kernel});
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std::cout << "Perf: " << ave_time << std::endl;
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bool pass = true;
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if(do_verification)
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{
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auto ref_pool =
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ck::tensor_operation::host::ReferenceAvgPoolBwd<3, DInDataType, DOutDataType>();
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auto ref_invoker = ref_pool.MakeInvoker();
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auto ref_argument = ref_pool.MakeArgument(din_host,
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dout,
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window_lengths,
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window_strides,
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window_dilations,
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dinput_left_pads,
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dinput_right_pads);
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ref_invoker.Run(ref_argument);
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din_device_buf.FromDevice(din_dev.mData.data());
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pass = ck::utils::check_err(din_dev, din_host);
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}
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return pass;
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}
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62
example/51_avgpool3d_bwd/avgpool3d_bwd_fp16.cpp
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62
example/51_avgpool3d_bwd/avgpool3d_bwd_fp16.cpp
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@@ -0,0 +1,62 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
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#include <iostream>
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#include "ck/ck.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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#include "ck/tensor_operation/gpu/device/impl/device_avgpool3d_bwd_ndhwc_ndhwc.hpp"
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#include "avgpool3d_bwd_common.hpp"
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using DOutDataType = ck::half_t;
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using DInDataType = ck::half_t;
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using ComputeDataType = float;
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#if 1
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using DOutLayout = ck::tensor_layout::convolution::NDHWC;
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using DInLayout = ck::tensor_layout::convolution::NDHWC;
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#else
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using DOutLayout = ck::tensor_layout::convolution::NCDHW;
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using DInLayout = ck::tensor_layout::convolution::NCDHW;
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#endif
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using DevicePoolBwdInstance =
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ck::tensor_operation::device::DeviceAvgPool3dBwd_NDHWC_NDHWC<DOutDataType,
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DInDataType,
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ComputeDataType,
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64, // BlockSize
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64, // ReduceMThreadClusterSize
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1, // ReduceKThreadClusterSize
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1, // ReduceMThreadSliceSize
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1, // ReduceKThreadSliceSize
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1>; // InSrcOutDstVectorSize
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int main()
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{
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std::vector<ck::index_t> window_lengths = {5, 5, 5};
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std::vector<ck::index_t> window_strides = {2, 2, 2};
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std::vector<ck::index_t> window_dilations = {2, 2, 2};
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std::vector<ck::index_t> dinput_left_pads = {0, 0, 0};
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std::vector<ck::index_t> dinput_right_pads = {0, 0, 0};
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ck::index_t N = 1;
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ck::index_t C = 16;
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ck::index_t Di = 40;
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ck::index_t Hi = 40;
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ck::index_t Wi = 40;
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pool3d_bwd_test<DevicePoolBwdInstance, DOutDataType, DInDataType, DOutLayout, DInLayout>(
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true,
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false,
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N,
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C,
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Di,
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Hi,
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Wi,
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window_lengths,
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window_strides,
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window_dilations,
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dinput_left_pads,
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dinput_right_pads);
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}
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62
example/51_avgpool3d_bwd/avgpool3d_bwd_fp32.cpp
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62
example/51_avgpool3d_bwd/avgpool3d_bwd_fp32.cpp
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@@ -0,0 +1,62 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
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#include <iostream>
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#include "ck/ck.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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#include "ck/tensor_operation/gpu/device/impl/device_avgpool3d_bwd_ndhwc_ndhwc.hpp"
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#include "avgpool3d_bwd_common.hpp"
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using DOutDataType = float;
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using DInDataType = float;
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using ComputeDataType = float;
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#if 1
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using DOutLayout = ck::tensor_layout::convolution::NDHWC;
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using DInLayout = ck::tensor_layout::convolution::NDHWC;
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#else
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using DOutLayout = ck::tensor_layout::convolution::NCDHW;
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using DInLayout = ck::tensor_layout::convolution::NCDHW;
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#endif
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using DevicePoolBwdInstance =
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ck::tensor_operation::device::DeviceAvgPool3dBwd_NDHWC_NDHWC<DOutDataType,
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DInDataType,
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ComputeDataType,
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64, // BlockSize
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64, // ReduceMThreadClusterSize
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1, // ReduceKThreadClusterSize
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1, // ReduceMThreadSliceSize
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1, // ReduceKThreadSliceSize
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1>; // InSrcOutDstVectorSize
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int main()
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{
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std::vector<ck::index_t> window_lengths = {5, 5, 5};
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std::vector<ck::index_t> window_strides = {2, 2, 2};
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std::vector<ck::index_t> window_dilations = {2, 2, 2};
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std::vector<ck::index_t> dinput_left_pads = {0, 0, 0};
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std::vector<ck::index_t> dinput_right_pads = {0, 0, 0};
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ck::index_t N = 1;
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ck::index_t C = 16;
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ck::index_t Di = 40;
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ck::index_t Hi = 40;
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ck::index_t Wi = 40;
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pool3d_bwd_test<DevicePoolBwdInstance, DOutDataType, DInDataType, DOutLayout, DInLayout>(
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true,
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false,
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N,
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C,
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Di,
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Hi,
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Wi,
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window_lengths,
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window_strides,
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window_dilations,
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dinput_left_pads,
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dinput_right_pads);
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}
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Reference in New Issue
Block a user