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https://github.com/ROCm/composable_kernel.git
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395 lines
23 KiB
C++
395 lines
23 KiB
C++
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#include <cmath>
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#include <cstdlib>
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#include <numeric>
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#include <type_traits>
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#include <vector>
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#include <gtest/gtest.h>
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#include "ck/ck.hpp"
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#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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#include "ck/library/utility/algorithm.hpp"
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#include "ck/library/utility/check_err.hpp"
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#include "ck/library/utility/fill.hpp"
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#include "ck/library/utility/host_tensor.hpp"
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#include "ck/library/utility/convolution_parameter.hpp"
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#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
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#include "ck/library/reference_tensor_operation/cpu/reference_conv_fwd.hpp"
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namespace {
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using ::ck::Tensor;
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using InElementOp = ck::tensor_operation::element_wise::PassThrough;
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using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
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using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
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template <ck::index_t NDimSpatial,
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typename InDataType = float,
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typename WeiDataType = float,
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typename OutDataType = float,
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typename InLayout = ck::tensor_layout::convolution::GNHWC,
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typename WeiLayout = ck::tensor_layout::convolution::GKYXC,
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typename OutLayout = ck::tensor_layout::convolution::GNHWK,
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typename FillInputOp = ck::utils::FillMonotonicSeq<InDataType>,
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typename FillWeightsOp = ck::utils::FillConstant<WeiDataType>>
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Tensor<OutDataType>
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run_reference_convolution_forward(const ck::utils::conv::ConvParam& conv_param,
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const FillInputOp& fill_input_op = FillInputOp{},
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const FillWeightsOp& fill_weights_op = FillWeightsOp{0.5f})
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{
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const auto in_g_n_c_wis_desc =
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ck::utils::conv::make_input_host_tensor_descriptor_g_n_c_wis_packed<InLayout>(conv_param);
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const auto wei_g_k_c_xs_desc =
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ck::utils::conv::make_weight_host_tensor_descriptor_g_k_c_xs_packed<WeiLayout>(conv_param);
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const auto out_g_n_k_wos_desc =
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ck::utils::conv::make_output_host_tensor_descriptor_g_n_k_wos_packed<OutLayout>(conv_param);
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Tensor<InDataType> input(in_g_n_c_wis_desc);
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Tensor<WeiDataType> weights(wei_g_k_c_xs_desc);
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Tensor<OutDataType> host_output(out_g_n_k_wos_desc);
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fill_input_op(input.begin(), input.end());
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fill_weights_op(weights.begin(), weights.end());
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ck::ranges::fill<OutDataType>(host_output, 0.f);
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auto ref_conv = ck::tensor_operation::host::ReferenceConvFwd<NDimSpatial,
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InDataType,
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WeiDataType,
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OutDataType,
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InElementOp,
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WeiElementOp,
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OutElementOp>();
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auto ref_invoker = ref_conv.MakeInvoker();
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auto ref_argument = ref_conv.MakeArgument(input,
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weights,
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host_output,
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conv_param.conv_filter_strides_,
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conv_param.conv_filter_dilations_,
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conv_param.input_left_pads_,
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conv_param.input_right_pads_,
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InElementOp{},
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WeiElementOp{},
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OutElementOp{});
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ref_invoker.Run(ref_argument);
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return host_output;
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}
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} // anonymous namespace
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// Eeference convolution assume dimensions of tensor descriptors are in GNCDHW/GKCZYX/GNKDHW order,
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// regardless of physical tensor layouts in memory.
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// Some tests below assume dimensions of tensor descriptors can be in other order, and therefore
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// are disabled
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// TODO: add more tests, which comply with assumption about dimension order of reference convolution
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// and add tests for more physical layout
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#if 0
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TEST(ReferenceConvolutionFWD, Conv2DGNHWC)
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{
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ck::utils::conv::ConvParam conv_param(2,
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1,
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1,
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1,
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2,
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std::vector<ck::index_t>{3, 3},
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std::vector<ck::index_t>{6, 6},
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std::vector<ck::index_t>{1, 1},
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std::vector<ck::index_t>{1, 1},
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std::vector<ck::index_t>{0, 0},
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std::vector<ck::index_t>{0, 0});
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auto out_tensor = run_reference_convolution_forward<2>(conv_param);
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std::vector<std::size_t> ref_dims{1, 1, 4, 4, 1};
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std::vector<float> ref_data{130.5,
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148.5,
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166.5,
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184.5,
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238.5,
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256.5,
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274.5,
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292.5,
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346.5,
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364.5,
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382.5,
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400.5,
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454.5,
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472.5,
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490.5,
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508.5};
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EXPECT_TRUE(ck::utils::check_err(
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out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
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EXPECT_TRUE(ck::utils::check_err(out_tensor, ref_data, "Error: incorrect results!"));
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}
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TEST(ReferenceConvolutionFWD, Conv2DGNHWCStridesDilationsPadding)
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{
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ck::utils::conv::ConvParam conv_param(2,
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1,
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1,
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2,
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2,
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std::vector<ck::index_t>{3, 3},
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std::vector<ck::index_t>{12, 12},
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std::vector<ck::index_t>{2, 2},
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std::vector<ck::index_t>{2, 2},
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std::vector<ck::index_t>{1, 1},
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std::vector<ck::index_t>{1, 1});
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auto out_tensor = run_reference_convolution_forward<2>(conv_param);
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std::vector<std::size_t> ref_dims = std::vector<std::size_t>{1, 5, 5, 2};
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std::vector<float> ref_data{
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210., 210., 327., 327., 351., 351., 375., 375., 399., 399.,
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459., 459., 706.5, 706.5, 742.5, 742.5, 778.5, 778.5, 814.5, 814.5,
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747., 747., 1138.5, 1138.5, 1174.5, 1174.5, 1210.5, 1210.5, 1246.5, 1246.5,
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1035., 1035., 1570.5, 1570.5, 1606.5, 1606.5, 1642.5, 1642.5, 1678.5, 1678.5,
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1323., 1323., 2002.5, 2002.5, 2038.5, 2038.5, 2074.5, 2074.5, 2110.5, 2110.5};
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EXPECT_TRUE(ck::utils::check_err(
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out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
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EXPECT_TRUE(ck::utils::check_err(out_tensor, ref_data, "Error: incorrect results!"));
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}
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TEST(ReferenceConvolutionFWD, Conv1DGNWC)
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{
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ck::utils::conv::ConvParam conv_param(1,
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1,
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1,
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1,
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2,
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std::vector<ck::index_t>{3},
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std::vector<ck::index_t>{6},
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std::vector<ck::index_t>{1},
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std::vector<ck::index_t>{1},
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std::vector<ck::index_t>{0},
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std::vector<ck::index_t>{0});
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auto out_tensor =
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run_reference_convolution_forward<1,
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float,
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float,
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float,
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ck::tensor_layout::convolution::GNWC,
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ck::tensor_layout::convolution::GKXC,
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ck::tensor_layout::convolution::GNWK>(conv_param);
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std::vector<std::size_t> ref_dims{1, 1, 4, 1};
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std::vector<float> ref_data{7.5, 13.5, 19.5, 25.5};
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EXPECT_TRUE(ck::utils::check_err(
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out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
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EXPECT_TRUE(ck::utils::check_err(out_tensor, ref_data, "Error: incorrect results!"));
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}
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TEST(ReferenceConvolutionFWD, Conv1DGNWCStridesDilationsPadding)
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{
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ck::utils::conv::ConvParam conv_param(1,
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1,
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1,
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2,
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2,
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std::vector<ck::index_t>{3},
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std::vector<ck::index_t>{12},
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std::vector<ck::index_t>{2},
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std::vector<ck::index_t>{2},
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std::vector<ck::index_t>{1},
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std::vector<ck::index_t>{1});
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auto out_tensor =
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run_reference_convolution_forward<1,
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float,
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float,
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float,
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ck::tensor_layout::convolution::GNWC,
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ck::tensor_layout::convolution::GKXC,
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ck::tensor_layout::convolution::GNWK>(conv_param);
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std::vector<std::size_t> ref_dims{1, 1, 5, 2};
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std::vector<float> ref_data{9., 9., 19.5, 19.5, 31.5, 31.5, 43.5, 43.5, 55.5, 55.5};
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EXPECT_TRUE(ck::utils::check_err(
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out_tensor.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
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EXPECT_TRUE(ck::utils::check_err(out_tensor, ref_data, "Error: incorrect results!"));
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}
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TEST(ReferenceConvolutionFWD, Conv1DGNWCSameOutputSize)
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{
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ck::utils::conv::ConvParam conv_param(1,
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1,
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2,
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16,
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4,
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std::vector<ck::index_t>{3},
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std::vector<ck::index_t>{16},
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std::vector<ck::index_t>{1},
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std::vector<ck::index_t>{1},
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std::vector<ck::index_t>{1},
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std::vector<ck::index_t>{1});
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auto out_tensor2 = run_reference_convolution_forward<1,
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float,
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float,
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float,
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ck::tensor_layout::convolution::GNWC,
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ck::tensor_layout::convolution::GKXC,
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ck::tensor_layout::convolution::GNWK>(
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conv_param, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
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std::vector<std::size_t> ref_dims{1, 2, 16, 16};
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std::vector<float> ref_data{
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1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4,
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1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4,
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3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3,
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3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3, 3.3,
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5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7,
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5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7, 5.7,
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8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1,
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8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1, 8.1,
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10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5,
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10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5, 10.5,
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12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001,
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12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001, 12.900001,
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15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3,
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15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3, 15.3,
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17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7,
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17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7, 17.7,
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20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1,
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20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1, 20.1,
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22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5,
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22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5, 22.5,
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24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002,
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24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002, 24.900002,
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27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001,
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27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001, 27.300001,
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29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7,
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29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7, 29.7,
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32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002,
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32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002, 32.100002,
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34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5,
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34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5, 34.5,
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23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8,
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23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8, 23.8,
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27., 27., 27., 27., 27., 27., 27., 27.,
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27., 27., 27., 27., 27., 27., 27., 27.,
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41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7,
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41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7, 41.7,
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44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002,
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44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002, 44.100002,
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46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5,
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46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5, 46.5,
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48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998,
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48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998, 48.899998,
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51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3,
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51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3, 51.3,
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53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7,
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53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7, 53.7,
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56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002,
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56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002, 56.100002,
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58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5,
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58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5, 58.5,
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60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998,
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60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998, 60.899998,
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63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3,
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63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3, 63.3,
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65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7,
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65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7, 65.7,
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68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1,
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68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1, 68.1,
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70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5,
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70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5, 70.5,
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72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9,
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72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9, 72.9,
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49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4,
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49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4, 49.4};
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EXPECT_TRUE(ck::utils::check_err(
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out_tensor2.mDesc.GetLengths(), ref_dims, "Error: wrong output tensor dimensions!"));
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EXPECT_TRUE(ck::utils::check_err(out_tensor2, ref_data, "Error: incorrect results!"));
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}
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#endif
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TEST(ReferenceConvolutionFWD, Conv3DGNCDHW)
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{
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ck::utils::conv::ConvParam conv_param(3,
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1,
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1,
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1,
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2,
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std::vector<ck::index_t>{3, 3, 3},
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std::vector<ck::index_t>{6, 6, 6},
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std::vector<ck::index_t>{1, 1, 1},
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std::vector<ck::index_t>{1, 1, 1},
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std::vector<ck::index_t>{0, 0, 0},
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std::vector<ck::index_t>{0, 0, 0});
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auto out_tensor = run_reference_convolution_forward<3,
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float,
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float,
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float,
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ck::tensor_layout::convolution::GNCDHW,
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ck::tensor_layout::convolution::GKCZYX,
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ck::tensor_layout::convolution::GNKDHW>(
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conv_param, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
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std::vector<std::size_t> ref_dims{1, 1, 1, 4, 4, 4};
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std::vector<float> ref_data{
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407.7, 410.40002, 413.09998, 415.80002, 423.90002, 426.6, 429.30002, 432.,
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440.1, 442.80002, 445.5, 448.2, 456.30002, 459., 461.7, 464.40002,
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504.90002, 507.6, 510.30002, 513., 521.1, 523.8, 526.5, 529.2001,
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537.3, 540., 542.7001, 545.4, 553.5, 556.2001, 558.9, 561.6,
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602.10004, 604.8, 607.5, 610.2, 618.3, 621., 623.7, 626.4,
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634.5, 637.2, 639.9, 642.60004, 650.7, 653.4, 656.10004, 658.8,
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699.3, 702., 704.7, 707.4, 715.5, 718.2, 720.9, 723.60004,
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731.7, 734.4001, 737.10004, 739.8, 747.9001, 750.60004, 753.3, 756.};
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EXPECT_TRUE(ck::utils::check_err(out_tensor.mDesc.GetLengths(),
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|
ref_dims,
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|
"Error [case 1]: wrong output tensor dimensions!"));
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|
EXPECT_TRUE(ck::utils::check_err(out_tensor, ref_data, "Error [case 1]: incorrect results!"));
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|
}
|
|
|
|
TEST(ReferenceConvolutionFWD, Conv3DGNCDHWStridesDilations)
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|
{
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|
ck::utils::conv::ConvParam conv_param(3,
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|
1,
|
|
1,
|
|
2,
|
|
2,
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|
std::vector<ck::index_t>{3, 3, 3},
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|
std::vector<ck::index_t>{12, 12, 12},
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|
std::vector<ck::index_t>{3, 3, 3},
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|
std::vector<ck::index_t>{1, 1, 1},
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|
std::vector<ck::index_t>{0, 0, 0},
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|
std::vector<ck::index_t>{0, 0, 0});
|
|
|
|
auto out_tensor = run_reference_convolution_forward<3,
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|
float,
|
|
float,
|
|
float,
|
|
ck::tensor_layout::convolution::GNCDHW,
|
|
ck::tensor_layout::convolution::GKCZYX,
|
|
ck::tensor_layout::convolution::GNKDHW>(
|
|
conv_param, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
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|
std::vector<std::size_t> ref_dims{1, 1, 2, 4, 4, 4};
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|
std::vector<float> ref_data{
|
|
2756.7002, 2764.7998, 2772.9001, 2781., 2853.9001, 2862., 2870.1, 2878.2002,
|
|
2951.1, 2959.2002, 2967.2998, 2975.4001, 3048.2998, 3056.4001, 3064.5, 3072.6,
|
|
3923.1, 3931.2, 3939.2998, 3947.4, 4020.2998, 4028.4001, 4036.5002, 4044.5999,
|
|
4117.5, 4125.6, 4133.7, 4141.8, 4214.7, 4222.8, 4230.9004, 4239.,
|
|
5089.5, 5097.5996, 5105.7, 5113.8, 5186.7, 5194.8, 5202.9, 5211.,
|
|
5283.9004, 5292., 5300.0996, 5308.2, 5381.0996, 5389.2, 5397.3, 5405.4004,
|
|
6255.9004, 6264.0005, 6272.1, 6280.2, 6353.1, 6361.2, 6369.301, 6377.4,
|
|
6450.301, 6458.4, 6466.5, 6474.6, 6547.5, 6555.6, 6563.699, 6571.801,
|
|
2756.7002, 2764.7998, 2772.9001, 2781., 2853.9001, 2862., 2870.1, 2878.2002,
|
|
2951.1, 2959.2002, 2967.2998, 2975.4001, 3048.2998, 3056.4001, 3064.5, 3072.6,
|
|
3923.1, 3931.2, 3939.2998, 3947.4, 4020.2998, 4028.4001, 4036.5002, 4044.5999,
|
|
4117.5, 4125.6, 4133.7, 4141.8, 4214.7, 4222.8, 4230.9004, 4239.,
|
|
5089.5, 5097.5996, 5105.7, 5113.8, 5186.7, 5194.8, 5202.9, 5211.,
|
|
5283.9004, 5292., 5300.0996, 5308.2, 5381.0996, 5389.2, 5397.3, 5405.4004,
|
|
6255.9004, 6264.0005, 6272.1, 6280.2, 6353.1, 6361.2, 6369.301, 6377.4,
|
|
6450.301, 6458.4, 6466.5, 6474.6, 6547.5, 6555.6, 6563.699, 6571.801};
|
|
EXPECT_TRUE(ck::utils::check_err(out_tensor.mDesc.GetLengths(),
|
|
ref_dims,
|
|
"Error [case 2]: wrong output tensor dimensions!"));
|
|
EXPECT_TRUE(ck::utils::check_err(
|
|
out_tensor, ref_data, "Error [case 2]: incorrect results!", 1e-4f, 1e-6f));
|
|
}
|