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https://github.com/ROCm/composable_kernel.git
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* parse examples inside the add_example_executable function * fix the example 64 cmake file * add xdl flag to the gemm_bias_softmax_gemm_permute example * add filtering of tests based on architecture type * enable test_grouped_gemm for gfx9 only * enable test_transpose only for gfx9 * only linnk test_transpose if it gets built * split the gemm instances by architectures * split gemm_bilinear,grouped_conv_bwd_weight instances by targets * split instances by architecture * split grouped_conv instances by architecture * fix clang format * fix the if-else logic in group_conv headers * small fix for grouped convolution instances * fix the grouped conv bwd weight dl instances * fix client examples * only enable client examples 3 and 4 on gfx9 * set the gfx9 macro * make sure the architecture macros are set by cmake * use separate set of xdl/wmma flags for host code * sinmplify the main cmake file * add conv_fwd_bf8 instance declaration
180 lines
7.0 KiB
C++
180 lines
7.0 KiB
C++
// SPDX-License-Identifier: MIT
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// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
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#include <cstdlib>
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#include <iostream>
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#include <memory>
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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_contraction_impl.hpp"
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#include "profiler/profile_contraction_utils.hpp"
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using F16 = ck::half_t;
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using BF16 = ck::bhalf_t;
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using F32 = float;
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using F64 = double;
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using Row = ck::tensor_layout::gemm::RowMajor;
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using Col = ck::tensor_layout::gemm::ColumnMajor;
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using Bilinear = ck::tensor_operation::element_wise::Bilinear;
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using Scale = ck::tensor_operation::element_wise::Scale;
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struct Dimensions
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{
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std::vector<ck::index_t> M;
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std::vector<ck::index_t> N;
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std::vector<ck::index_t> K;
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};
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template <typename Tuple>
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class TestContraction : public ::testing::Test
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{
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protected:
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using ALayout = std::tuple_element_t<0, Tuple>;
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using BLayout = std::tuple_element_t<1, Tuple>;
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using CDLayout = std::tuple_element_t<2, Tuple>;
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using DataType = std::tuple_element_t<3, Tuple>;
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using DTupleDataType = std::tuple_element_t<4, Tuple>;
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using ComputeDataType = std::tuple_element_t<5, Tuple>;
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using CDElementOp = std::tuple_element_t<6, Tuple>;
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std::vector<Dimensions> dimension_list = {{{32, 32}, {32, 32}, {32, 32}},
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{{16, 16}, {32, 32}, {16, 16}}};
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std::vector<ck::index_t> init_methods = {1, 2};
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std::unique_ptr<CDElementOp> p_cd_element_op;
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void Run()
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{
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for(auto& dimension_params : dimension_list)
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{
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std::vector<ck::index_t> StridesA;
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std::vector<ck::index_t> StridesB;
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std::vector<ck::index_t> StridesC;
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std::vector<ck::index_t> StridesD;
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const auto& M = dimension_params.M;
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const auto& N = dimension_params.N;
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const auto& K = dimension_params.K;
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assign_default_strides(ALayout{}, StridesA, {M[0], M[1], K[0], K[1]});
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assign_default_strides(BLayout{}, StridesB, {N[0], N[1], K[0], K[1]});
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assign_default_strides(CDLayout{}, StridesC, {M[0], M[1], N[0], N[1]});
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assign_default_strides(CDLayout{}, StridesD, {M[0], M[1], N[0], N[1]});
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for(const ck::index_t init_method : init_methods)
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{
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bool pass =
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ck::profiler::profile_contraction_impl<ALayout,
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BLayout,
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CDLayout,
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DataType,
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ComputeDataType,
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DTupleDataType,
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CDElementOp>(true /*do_verification*/,
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init_method,
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false /*do_logs*/,
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false /*time_kernel*/,
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*p_cd_element_op,
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dimension_params.M,
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dimension_params.N,
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dimension_params.K,
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StridesA,
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StridesB,
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StridesC,
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StridesD);
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EXPECT_TRUE(pass);
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}
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}
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}
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};
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template <typename Tuple>
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class TestContractionScale : public TestContraction<Tuple>
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{
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};
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template <typename Tuple>
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class TestContractionBilinear : public TestContraction<Tuple>
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{
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};
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#define ALL_LAYOUT_COMBINATIONS(dt, tuple_dt, compute_dt, op) \
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std::tuple<Row, Row, Row, dt, tuple_dt, compute_dt, op>, \
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std::tuple<Row, Col, Row, dt, tuple_dt, compute_dt, op>, \
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std::tuple<Col, Row, Row, dt, tuple_dt, compute_dt, op>, \
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std::tuple<Col, Col, Row, dt, tuple_dt, compute_dt, op>
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using BilinearKernelTypes =
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::testing::Types<ALL_LAYOUT_COMBINATIONS(F32, ck::Tuple<F32>, F32, Bilinear),
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ALL_LAYOUT_COMBINATIONS(F64, ck::Tuple<F64>, F64, Bilinear)>;
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using ScaleKernelTypes = ::testing::Types<ALL_LAYOUT_COMBINATIONS(F32, ck::Tuple<>, F32, Scale),
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ALL_LAYOUT_COMBINATIONS(F64, ck::Tuple<>, F64, Scale)>;
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TYPED_TEST_SUITE(TestContractionBilinear, BilinearKernelTypes);
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TYPED_TEST_SUITE(TestContractionScale, ScaleKernelTypes);
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TYPED_TEST(TestContractionBilinear, bilinear)
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{
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this->p_cd_element_op = std::make_unique<Bilinear>(1.f, 1.f);
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this->Run();
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this->p_cd_element_op = std::make_unique<Bilinear>(-0.5f, 0.5f);
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this->Run();
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}
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TYPED_TEST(TestContractionScale, scale)
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{
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this->p_cd_element_op = std::make_unique<Scale>(1.f);
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this->Run();
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this->p_cd_element_op = std::make_unique<Scale>(0.5f);
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this->Run();
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}
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template <typename Tuple>
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class TestContractionScaleMixedPrecision : public TestContraction<Tuple>
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{
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};
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template <typename Tuple>
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class TestContractionBilinearMixedPrecision : public TestContraction<Tuple>
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{
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};
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using BilinearKernelTypesMixedPrecision =
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::testing::Types<ALL_LAYOUT_COMBINATIONS(F32, ck::Tuple<F32>, F16, Bilinear),
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ALL_LAYOUT_COMBINATIONS(F32, ck::Tuple<F32>, BF16, Bilinear),
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ALL_LAYOUT_COMBINATIONS(F64, ck::Tuple<F64>, F32, Bilinear),
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ALL_LAYOUT_COMBINATIONS(F16, ck::Tuple<F16>, F32, Bilinear),
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ALL_LAYOUT_COMBINATIONS(BF16, ck::Tuple<BF16>, F32, Bilinear)>;
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using ScaleKernelTypesMixedPrecision =
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::testing::Types<ALL_LAYOUT_COMBINATIONS(F32, ck::Tuple<>, F16, Scale),
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ALL_LAYOUT_COMBINATIONS(F32, ck::Tuple<>, BF16, Scale),
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ALL_LAYOUT_COMBINATIONS(F64, ck::Tuple<>, F32, Scale),
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ALL_LAYOUT_COMBINATIONS(F16, ck::Tuple<>, F32, Scale),
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ALL_LAYOUT_COMBINATIONS(BF16, ck::Tuple<>, F32, Scale)>;
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TYPED_TEST_SUITE(TestContractionBilinearMixedPrecision, BilinearKernelTypesMixedPrecision);
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TYPED_TEST_SUITE(TestContractionScaleMixedPrecision, ScaleKernelTypesMixedPrecision);
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TYPED_TEST(TestContractionBilinearMixedPrecision, bilinear)
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{
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this->p_cd_element_op = std::make_unique<Bilinear>(1.f, 1.f);
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this->Run();
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this->p_cd_element_op = std::make_unique<Bilinear>(-0.5f, 0.5f);
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this->Run();
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}
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TYPED_TEST(TestContractionScaleMixedPrecision, scale)
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{
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this->p_cd_element_op = std::make_unique<Scale>(1.f);
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this->Run();
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this->p_cd_element_op = std::make_unique<Scale>(0.5f);
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this->Run();
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}
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