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c190d8d61f
* test_convnd_fwd
* test_convnd_bwd_data
* test_conv_bwd_data_scale
* test_grouped_convnd_fwd_clamp
* test_grouped_convnd_fwd_scale
* multiple A/B tensors and D tensor for fwd GPU ref
* test_grouped_convnd_fwd_scaleadd_ab
* test_grouped_convnd_fwd_bias_clamp
* test_grouped_convnd_fwd_bilinear
* test_grouped_convnd_fwd_gk_bias_clamp
* Extend GPU reference to enable batchnorm epilogue
* test_grouped_convnd_fwd{,_gk}_bias_bnorm_clamp
* test_grouped_conv_bwd_data_bilinear
* test_grouped_convnd_bwd_weight_bilinear
* Add missing template instantiation
* Perform operations in float in reference
* Slightly increase tolerance for batchnorm profiler
* Revert "Slightly increase tolerance for batchnorm profiler"
This reverts commit a3b2475229.
* Revert "test_grouped_convnd_fwd{,_gk}_bias_bnorm_clamp"
This reverts commit 6da4576060.
* Revert "Extend GPU reference to enable batchnorm epilogue"
This reverts commit e2f75fa10e.
* Clarify variable names
* Refactor elementwise ops into helper functions
* Make helpers C++17-compatible
117 lines
4.3 KiB
C++
117 lines
4.3 KiB
C++
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#include <cstdlib>
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#include <iostream>
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#include <initializer_list>
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#include <vector>
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#include <tuple>
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#include <gtest/gtest.h>
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#include "profiler/profile_conv_bwd_data_impl.hpp"
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static ck::index_t param_mask = 0xffff;
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static ck::index_t instance_index = -1;
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template <typename Tuple>
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class TestConvndBwdData : public ::testing::Test
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{
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protected:
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using DataType = std::tuple_element_t<0, Tuple>;
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std::vector<ck::utils::conv::ConvParam> conv_params;
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template <ck::index_t NDimSpatial>
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void Run()
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{
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EXPECT_FALSE(conv_params.empty());
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for(size_t i = 0; i < conv_params.size(); i++)
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{
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if((param_mask & (1 << i)) == 0)
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{
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continue;
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}
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auto& param = conv_params[i];
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bool pass;
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pass = ck::profiler::profile_conv_bwd_data_impl<
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NDimSpatial,
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ck::tuple_element_t<NDimSpatial - 1,
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ck::Tuple<ck::tensor_layout::convolution::NWC,
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ck::tensor_layout::convolution::NHWC,
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ck::tensor_layout::convolution::NDHWC>>,
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ck::tuple_element_t<NDimSpatial - 1,
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ck::Tuple<ck::tensor_layout::convolution::KXC,
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ck::tensor_layout::convolution::KYXC,
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ck::tensor_layout::convolution::KZYXC>>,
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ck::tuple_element_t<NDimSpatial - 1,
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ck::Tuple<ck::tensor_layout::convolution::NWK,
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ck::tensor_layout::convolution::NHWK,
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ck::tensor_layout::convolution::NDHWK>>,
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DataType,
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DataType,
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DataType>(2, // do_verification: 2 = GPU reference
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1, // init_method integer value
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false, // do_log
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false, // time_kernel
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param,
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instance_index);
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EXPECT_TRUE(pass);
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}
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}
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};
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using KernelTypes = ::testing::Types<std::tuple<float>,
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std::tuple<ck::half_t>,
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std::tuple<ck::bhalf_t>,
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std::tuple<std::int8_t>>;
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TYPED_TEST_SUITE(TestConvndBwdData, KernelTypes);
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// 1d
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TYPED_TEST(TestConvndBwdData, Conv1dBwdData)
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{
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this->conv_params.clear();
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this->conv_params.push_back({1, 1, 128, 128, 256, {1}, {14}, {2}, {1}, {0}, {0}});
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this->conv_params.push_back({1, 1, 128, 128, 256, {3}, {28}, {1}, {1}, {1}, {1}});
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this->conv_params.push_back({1, 1, 128, 128, 256, {1}, {3}, {1}, {1}, {0}, {0}});
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this->template Run<1>();
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}
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// 2d
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TYPED_TEST(TestConvndBwdData, Conv2dBwdData)
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{
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this->conv_params.clear();
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this->conv_params.push_back(
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{2, 1, 128, 128, 256, {1, 1}, {7, 7}, {2, 2}, {1, 1}, {0, 0}, {0, 0}});
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this->conv_params.push_back(
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{2, 1, 128, 128, 256, {3, 3}, {14, 14}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
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this->conv_params.push_back(
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{2, 1, 128, 128, 256, {1, 1}, {3, 3}, {1, 1}, {1, 1}, {0, 0}, {0, 0}});
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this->template Run<2>();
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}
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// 3d
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TYPED_TEST(TestConvndBwdData, Conv3dBwdData)
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{
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this->conv_params.clear();
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this->conv_params.push_back(
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{3, 1, 128, 128, 256, {1, 1, 1}, {7, 7, 7}, {2, 2, 2}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
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this->conv_params.push_back(
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{3, 1, 128, 128, 256, {3, 3, 3}, {14, 14, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
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this->conv_params.push_back(
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{3, 1, 128, 128, 256, {1, 1, 1}, {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
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this->template Run<3>();
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}
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int main(int argc, char** argv)
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{
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testing::InitGoogleTest(&argc, argv);
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if(argc == 1) {}
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else if(argc == 3)
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{
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param_mask = strtol(argv[1], nullptr, 0);
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instance_index = atoi(argv[2]);
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}
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else
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{
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std::cout << "Usage of " << argv[0] << std::endl;
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std::cout << "Arg1,2: param_mask instance_index(-1 means all)" << std::endl;
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}
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return RUN_ALL_TESTS();
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}
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