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* Use googletest for tests. Add conv2d_fwd UT.
* Add conv1D/3D to gtest UT.
* Fix: not duplicate test with CTest.
* Convert more tests to googltests.
* Fix: GIT_SHALLOW is not allowed for git commit hash.
* Clang-format
* use integer value for GEMM test
Co-authored-by: Adam Osewski <aosewski@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
Co-authored-by: Chao Liu <lc.roy86@gmail.com>
[ROCm/composable_kernel commit: 8eca05a633]
215 lines
9.9 KiB
C++
215 lines
9.9 KiB
C++
#include <half.hpp>
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#include <iostream>
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#include <stdexcept>
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#include <tuple>
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#include <vector>
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#include "gtest/gtest.h"
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#include "data_type.hpp"
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#include "element_wise_operation.hpp"
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#include "conv_fwd_util.hpp"
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#include "conv_util.hpp"
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namespace {
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template <typename T>
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bool test_conv3d_ndhwc_instances(const std::vector<test::conv::DeviceConvFwdNoOpPtr>& conv_ptrs)
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{
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using namespace std::placeholders;
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using namespace ck::utils;
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namespace ctl = ck::tensor_layout::convolution;
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conv::ConvParams params;
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params.N = 64;
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params.num_dim_spatial = 3;
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params.filter_spatial_lengths = std::vector<ck::index_t>{3, 3, 2};
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params.input_spatial_lengths = std::vector<ck::index_t>{32, 32, 2};
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params.conv_filter_strides = std::vector<ck::index_t>{2, 2, 2};
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params.conv_filter_dilations = std::vector<ck::index_t>{1, 1, 1};
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params.input_left_pads = std::vector<ck::index_t>{1, 1, 1};
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params.input_right_pads = std::vector<ck::index_t>{1, 1, 1};
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conv::ConvFwdOpInstance<T, T, T, ctl::NDHWC, ctl::KZYXC, ctl::NDHWK> conv_instance(params);
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auto reference_conv_fwd_fun =
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std::bind(conv::run_reference_convolution_forward<3, T, T, T>, params, _1, _2, _3);
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OpInstanceRunEngine<T, T, T> run_engine(conv_instance, reference_conv_fwd_fun);
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return run_engine.Test(conv_ptrs);
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}
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} // anonymous namespace
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TEST(Conv3DFwdNDHWC, TestConv3D)
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{
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using namespace std::placeholders;
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using namespace ck::utils;
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namespace ctl = ck::tensor_layout::convolution;
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conv::ConvParams params;
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params.num_dim_spatial = 3;
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params.N = 2;
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params.K = 16;
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params.C = 4;
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params.filter_spatial_lengths = std::vector<ck::index_t>{3, 3, 3};
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params.input_spatial_lengths = std::vector<ck::index_t>{16, 16, 16};
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params.conv_filter_strides = std::vector<ck::index_t>{1, 1, 1};
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params.conv_filter_dilations = std::vector<ck::index_t>{1, 1, 1};
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params.input_left_pads = std::vector<ck::index_t>{1, 1, 1};
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params.input_right_pads = std::vector<ck::index_t>{1, 1, 1};
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std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
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test::conv::get_test_convolution_fwd_instance<3>(conv_ptrs);
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conv::ConvFwdOpInstance<float, float, float, ctl::NDHWC, ctl::KZYXC, ctl::NDHWK> conv_instance(
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params);
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auto reference_conv_fwd_fun = std::bind(
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conv::run_reference_convolution_forward<3, float, float, float>, params, _1, _2, _3);
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OpInstanceRunEngine<float, float, float> run_engine(conv_instance, reference_conv_fwd_fun);
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run_engine.SetAtol(1e-5);
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run_engine.SetRtol(1e-4);
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EXPECT_TRUE(run_engine.Test(conv_ptrs));
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}
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TEST(Conv3DFwdNDHWC, InputOver2GB)
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{
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using PassThrough = ck::tensor_operation::element_wise::PassThrough;
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using namespace ck::utils;
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// >2GB Input
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conv::ConvParams params;
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params.num_dim_spatial = 3;
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params.N = 2;
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params.K = 16;
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params.C = 32;
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params.filter_spatial_lengths = std::vector<ck::index_t>{3, 3, 3};
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params.input_spatial_lengths = std::vector<ck::index_t>{32, 1000, 1000};
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params.conv_filter_strides = std::vector<ck::index_t>{1, 1, 1};
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params.conv_filter_dilations = std::vector<ck::index_t>{1, 1, 1};
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params.input_left_pads = std::vector<ck::index_t>{1, 1, 1};
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params.input_right_pads = std::vector<ck::index_t>{1, 1, 1};
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std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
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test::conv::get_test_convolution_fwd_instance<3>(conv_ptrs);
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auto arg = conv_ptrs.back()->MakeArgumentPointer(nullptr,
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nullptr,
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nullptr,
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params.N,
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params.K,
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params.C,
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params.input_spatial_lengths,
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params.filter_spatial_lengths,
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params.GetOutputSpatialLengths(),
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params.conv_filter_strides,
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params.conv_filter_dilations,
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params.input_left_pads,
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params.input_right_pads,
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PassThrough{},
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PassThrough{},
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PassThrough{});
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EXPECT_FALSE(conv_ptrs.back()->IsSupportedArgument(arg.get()));
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}
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TEST(Conv3DFwdNDHWC, FiltersOver2GB)
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{
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using PassThrough = ck::tensor_operation::element_wise::PassThrough;
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using namespace ck::utils;
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// >2GB Filters
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conv::ConvParams params;
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params.num_dim_spatial = 3;
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params.N = 2;
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params.K = 16;
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params.C = 32;
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params.filter_spatial_lengths = std::vector<ck::index_t>{4, 1000, 1000};
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params.input_spatial_lengths = std::vector<ck::index_t>{16, 16, 16};
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params.conv_filter_strides = std::vector<ck::index_t>{1, 1, 1};
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params.conv_filter_dilations = std::vector<ck::index_t>{1, 1, 1};
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params.input_left_pads = std::vector<ck::index_t>{1, 1, 1};
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params.input_right_pads = std::vector<ck::index_t>{1, 1, 1};
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std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
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test::conv::get_test_convolution_fwd_instance<3>(conv_ptrs);
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auto arg = conv_ptrs.back()->MakeArgumentPointer(nullptr,
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nullptr,
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nullptr,
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params.N,
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params.K,
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params.C,
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params.input_spatial_lengths,
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params.filter_spatial_lengths,
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params.GetOutputSpatialLengths(),
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params.conv_filter_strides,
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params.conv_filter_dilations,
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params.input_left_pads,
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params.input_right_pads,
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PassThrough{},
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PassThrough{},
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PassThrough{});
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EXPECT_FALSE(conv_ptrs.back()->IsSupportedArgument(arg.get()));
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}
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TEST(Conv3DFwdNDHWC, OutputOver2GB)
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{
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using PassThrough = ck::tensor_operation::element_wise::PassThrough;
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using namespace ck::utils;
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// >2GB Output
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conv::ConvParams params;
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params.num_dim_spatial = 3;
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params.N = 2;
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params.K = 16;
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params.C = 2;
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params.filter_spatial_lengths = std::vector<ck::index_t>{1, 1, 1};
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params.input_spatial_lengths = std::vector<ck::index_t>{1000, 1000, 30};
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params.conv_filter_strides = std::vector<ck::index_t>{1, 1, 1};
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params.conv_filter_dilations = std::vector<ck::index_t>{1, 1, 1};
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params.input_left_pads = std::vector<ck::index_t>{2, 2, 2};
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params.input_right_pads = std::vector<ck::index_t>{2, 2, 2};
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std::vector<test::conv::DeviceConvFwdNoOpPtr> conv_ptrs;
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test::conv::get_test_convolution_fwd_instance<3>(conv_ptrs);
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auto arg = conv_ptrs.back()->MakeArgumentPointer(nullptr,
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nullptr,
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nullptr,
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params.N,
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params.K,
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params.C,
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params.input_spatial_lengths,
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params.filter_spatial_lengths,
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params.GetOutputSpatialLengths(),
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params.conv_filter_strides,
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params.conv_filter_dilations,
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params.input_left_pads,
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params.input_right_pads,
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PassThrough{},
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PassThrough{},
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PassThrough{});
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EXPECT_FALSE(conv_ptrs.back()->IsSupportedArgument(arg.get()));
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}
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TEST(Conv3DFwdNDHWC, Bf16Instances)
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{
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EXPECT_TRUE(test_conv3d_ndhwc_instances<ck::bhalf_t>(
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ck::utils::conv::ConvolutionFwdInstances<ck::bhalf_t, ck::bhalf_t, ck::bhalf_t>::Get<3>()));
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}
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TEST(Conv3DFwdNDHWC, F16Instances)
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{
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EXPECT_TRUE(test_conv3d_ndhwc_instances<ck::half_t>(
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ck::utils::conv::ConvolutionFwdInstances<ck::half_t, ck::half_t, ck::half_t>::Get<3>()));
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}
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TEST(Conv3DFwdNDHWC, F32Instances)
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{
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EXPECT_TRUE(test_conv3d_ndhwc_instances<float>(
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ck::utils::conv::ConvolutionFwdInstances<float, float, float>::Get<3>()));
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}
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TEST(Conv3DFwdNDHWC, Int8Instances)
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{
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EXPECT_TRUE(test_conv3d_ndhwc_instances<int8_t>(
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ck::utils::conv::ConvolutionFwdInstances<int8_t, int8_t, int8_t>::Get<3>()));
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}
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