mirror of
https://github.com/ROCm/composable_kernel.git
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test(grouped_gemm): add unit tests for grouped_gemm bquant with preshuffleB true (#3119)
* add tensorwise quant in grouped gemm * fix example issue * update test cases * format codes * clang format * use GTEST_FAIL * add bquant to grouped_gemm * add tensorwise quant in grouped gemm * fix example issue * update test cases * format codes * clang format * use GTEST_FAIL * fix a bug in test_grouped_gemm_util * skip test when use wmma on grouped_quant kernel * change cmake * fix a bug in test_grouped_gemm_util * skip test when use wmma on grouped_quant kernel * change cmake * tests(quant_grouped_gemm): add unit tests to cover bquant in grouped_gemm * Update test/ck_tile/grouped_gemm_quant/test_grouped_gemm_util_quant.hpp Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update example/ck_tile/17_grouped_gemm/quant_grouped_gemm.hpp Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * feat: add bf8 support * chore: remove unnecessary decltype usage * chore: add default quant_mode to function signature as fallback * fix: pass correct runtime pipeline params in grouped_gemm bquant kernel Calculate has_hot_loop, num_loop, and tail_number on device side for each GEMM problem instead of using default values. This fixes incorrect results when different problems in the group have different K dimensions. * chore: set default quant mode in function signature * test: add additional test cases to cover edge case of no hotloop * change code based on comments * WIP: bquant preshuffle b compiles but gives numerical error * feat(grouped_gemm_quant): bquant with preshuffleB support added to grouped_gemm example & kernel * refactor: refactor code after merge commit * chore: remove print statements * test(grouped_gemm): split test cases by quant mode to reduce compilation time and add bquant-preshuffleB mode test cases --------- Co-authored-by: kyle-256 <Kyle.Zhao@amd.com> Co-authored-by: ThomasNing <thomas.ning@amd.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
This commit is contained in:
Aviral Goel
@@ -4,7 +4,14 @@ if(CK_USE_OCP_FP8)
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endif()
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if(GPU_TARGETS MATCHES "gfx94|gfx95")
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add_gtest_executable(test_ck_tile_grouped_gemm_quant test_grouped_gemm_quant.cpp)
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target_compile_options(test_ck_tile_grouped_gemm_quant PRIVATE ${EXAMPLE_GEMM_COMPILE_OPTIONS})
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# Split into three separate test executables for faster parallel compilation
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add_gtest_executable(test_ck_tile_grouped_gemm_quant_rowcol test_grouped_gemm_quant_rowcol.cpp)
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target_compile_options(test_ck_tile_grouped_gemm_quant_rowcol PRIVATE ${EXAMPLE_GEMM_COMPILE_OPTIONS})
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add_gtest_executable(test_ck_tile_grouped_gemm_quant_tensor test_grouped_gemm_quant_tensor.cpp)
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target_compile_options(test_ck_tile_grouped_gemm_quant_tensor PRIVATE ${EXAMPLE_GEMM_COMPILE_OPTIONS})
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add_gtest_executable(test_ck_tile_grouped_gemm_quant_bquant test_grouped_gemm_quant_bquant.cpp)
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target_compile_options(test_ck_tile_grouped_gemm_quant_bquant PRIVATE ${EXAMPLE_GEMM_COMPILE_OPTIONS})
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endif()
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@@ -22,26 +22,28 @@ using BQuant = std::integral_constant<ck_tile::QuantType, ck_tile::QuantTyp
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// clang-format off
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using KernelTypes = ::testing::Types<
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// ALayout, BLayout, CLayout, ADataType, AQDataType, BDataType, BQDataType, AccDataType, CDataType, QuantType
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std::tuple< Row, Col, Row, FP8, F32, FP8, F32, F32, F16, RowColQuant>,
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std::tuple< Col, Col, Row, FP8, F32, FP8, F32, F32, F16, RowColQuant>,
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std::tuple< Row, Row, Row, FP8, F32, FP8, F32, F32, F16, RowColQuant>,
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std::tuple< Col, Row, Row, FP8, F32, FP8, F32, F32, F16, RowColQuant>,
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// ALayout, BLayout, CLayout, ADataType, AQDataType, BDataType, BQDataType, AccDataType, CDataType, QuantType, PreshuffleB
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std::tuple< Row, Col, Row, FP8, F32, FP8, F32, F32, F16, RowColQuant, False>,
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std::tuple< Col, Col, Row, FP8, F32, FP8, F32, F32, F16, RowColQuant, False>,
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std::tuple< Row, Row, Row, FP8, F32, FP8, F32, F32, F16, RowColQuant, False>,
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std::tuple< Col, Row, Row, FP8, F32, FP8, F32, F32, F16, RowColQuant, False>,
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std::tuple< Row, Col, Row, BF8, F32, BF8, F32, F32, F16, RowColQuant>,
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std::tuple< Col, Col, Row, BF8, F32, BF8, F32, F32, F16, RowColQuant>,
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std::tuple< Row, Row, Row, BF8, F32, BF8, F32, F32, F16, RowColQuant>,
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std::tuple< Col, Row, Row, BF8, F32, BF8, F32, F32, F16, RowColQuant>,
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std::tuple< Row, Col, Row, FP8, F32, FP8, F32, F32, F16, TensorQuant>,
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std::tuple< Col, Col, Row, FP8, F32, FP8, F32, F32, F16, TensorQuant>,
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std::tuple< Row, Row, Row, FP8, F32, FP8, F32, F32, F16, TensorQuant>,
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std::tuple< Col, Row, Row, FP8, F32, FP8, F32, F32, F16, TensorQuant>,
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std::tuple< Row, Col, Row, BF8, F32, BF8, F32, F32, F16, TensorQuant>,
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std::tuple< Col, Col, Row, BF8, F32, BF8, F32, F32, F16, TensorQuant>,
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std::tuple< Row, Row, Row, BF8, F32, BF8, F32, F32, F16, TensorQuant>,
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std::tuple< Col, Row, Row, BF8, F32, BF8, F32, F32, F16, TensorQuant>,
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std::tuple< Row, Col, Row, FP8, F32, FP8, F32, F32, F16, BQuant>,
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std::tuple< Row, Col, Row, BF8, F32, BF8, F32, F32, F16, BQuant>
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std::tuple< Row, Col, Row, BF8, F32, BF8, F32, F32, F16, RowColQuant, False>,
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std::tuple< Col, Col, Row, BF8, F32, BF8, F32, F32, F16, RowColQuant, False>,
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std::tuple< Row, Row, Row, BF8, F32, BF8, F32, F32, F16, RowColQuant, False>,
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std::tuple< Col, Row, Row, BF8, F32, BF8, F32, F32, F16, RowColQuant, False>,
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std::tuple< Row, Col, Row, FP8, F32, FP8, F32, F32, F16, TensorQuant, False>,
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std::tuple< Col, Col, Row, FP8, F32, FP8, F32, F32, F16, TensorQuant, False>,
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std::tuple< Row, Row, Row, FP8, F32, FP8, F32, F32, F16, TensorQuant, False>,
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std::tuple< Col, Row, Row, FP8, F32, FP8, F32, F32, F16, TensorQuant, False>,
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std::tuple< Row, Col, Row, BF8, F32, BF8, F32, F32, F16, TensorQuant, False>,
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std::tuple< Col, Col, Row, BF8, F32, BF8, F32, F32, F16, TensorQuant, False>,
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std::tuple< Row, Row, Row, BF8, F32, BF8, F32, F32, F16, TensorQuant, False>,
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std::tuple< Col, Row, Row, BF8, F32, BF8, F32, F32, F16, TensorQuant, False>,
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std::tuple< Row, Col, Row, FP8, F32, FP8, F32, F32, F16, BQuant, False>,
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std::tuple< Row, Col, Row, BF8, F32, BF8, F32, F32, F16, BQuant, False>,
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std::tuple< Row, Col, Row, BF8, F32, BF8, F32, F32, F16, BQuant, True>,
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std::tuple< Row, Col, Row, FP8, F32, FP8, F32, F32, F16, BQuant, True>
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>;
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// clang-format on
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@@ -0,0 +1,33 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
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#include <tuple>
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#include "gtest/gtest.h"
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#include "ck_tile/host.hpp"
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#include "test_grouped_gemm_util_quant.hpp"
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using F16 = ck_tile::half_t;
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using F32 = float;
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using FP8 = ck_tile::fp8_t;
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using BF8 = ck_tile::bf8_t;
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using Row = ck_tile::tensor_layout::gemm::RowMajor;
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using Col = ck_tile::tensor_layout::gemm::ColumnMajor;
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using True = ck_tile::bool_constant<true>;
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using False = ck_tile::bool_constant<false>;
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using BQuant = std::integral_constant<ck_tile::QuantType, ck_tile::QuantType::BQuantGrouped>;
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// clang-format off
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using KernelTypes_BQuant = ::testing::Types<
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// ALayout, BLayout, CLayout, ADataType, AQDataType, BDataType, BQDataType, AccDataType, CDataType, QuantType, PreshuffleB
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std::tuple< Row, Col, Row, FP8, F32, FP8, F32, F32, F16, BQuant, False>,
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std::tuple< Row, Col, Row, FP8, F32, FP8, F32, F32, F16, BQuant, True>
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>;
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// clang-format on
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TYPED_TEST_SUITE(TestCkTileGroupedGemmQuant_BQuant, KernelTypes_BQuant);
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#define TEST_CLASS_NAME TestCkTileGroupedGemmQuant_BQuant
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#include "test_grouped_gemm_quant_ut_cases.inc"
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#undef TEST_CLASS_NAME
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@@ -0,0 +1,35 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
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#include <tuple>
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#include "gtest/gtest.h"
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#include "ck_tile/host.hpp"
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#include "test_grouped_gemm_util_quant.hpp"
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using F16 = ck_tile::half_t;
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using F32 = float;
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using FP8 = ck_tile::fp8_t;
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using BF8 = ck_tile::bf8_t;
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using Row = ck_tile::tensor_layout::gemm::RowMajor;
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using Col = ck_tile::tensor_layout::gemm::ColumnMajor;
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using True = ck_tile::bool_constant<true>;
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using False = ck_tile::bool_constant<false>;
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using RowColQuant = std::integral_constant<ck_tile::QuantType, ck_tile::QuantType::RowColQuant>;
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// clang-format off
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using KernelTypes_RowCol = ::testing::Types<
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// ALayout, BLayout, CLayout, ADataType, AQDataType, BDataType, BQDataType, AccDataType, CDataType, QuantType, PreshuffleB
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std::tuple< Row, Col, Row, FP8, F32, FP8, F32, F32, F16, RowColQuant, False>,
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std::tuple< Col, Col, Row, FP8, F32, FP8, F32, F32, F16, RowColQuant, False>,
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std::tuple< Row, Row, Row, FP8, F32, FP8, F32, F32, F16, RowColQuant, False>,
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std::tuple< Col, Row, Row, FP8, F32, FP8, F32, F32, F16, RowColQuant, False>
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>;
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// clang-format on
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TYPED_TEST_SUITE(TestCkTileGroupedGemmQuant_RowCol, KernelTypes_RowCol);
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#define TEST_CLASS_NAME TestCkTileGroupedGemmQuant_RowCol
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#include "test_grouped_gemm_quant_ut_cases.inc"
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#undef TEST_CLASS_NAME
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@@ -0,0 +1,35 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
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#include <tuple>
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#include "gtest/gtest.h"
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#include "ck_tile/host.hpp"
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#include "test_grouped_gemm_util_quant.hpp"
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using F16 = ck_tile::half_t;
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using F32 = float;
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using FP8 = ck_tile::fp8_t;
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using BF8 = ck_tile::bf8_t;
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using Row = ck_tile::tensor_layout::gemm::RowMajor;
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using Col = ck_tile::tensor_layout::gemm::ColumnMajor;
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using True = ck_tile::bool_constant<true>;
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using False = ck_tile::bool_constant<false>;
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using TensorQuant = std::integral_constant<ck_tile::QuantType, ck_tile::QuantType::TensorQuant>;
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// clang-format off
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using KernelTypes_Tensor = ::testing::Types<
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// ALayout, BLayout, CLayout, ADataType, AQDataType, BDataType, BQDataType, AccDataType, CDataType, QuantType, PreshuffleB
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std::tuple< Row, Col, Row, FP8, F32, FP8, F32, F32, F16, TensorQuant, False>,
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std::tuple< Col, Col, Row, FP8, F32, FP8, F32, F32, F16, TensorQuant, False>,
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std::tuple< Row, Row, Row, FP8, F32, FP8, F32, F32, F16, TensorQuant, False>,
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std::tuple< Col, Row, Row, FP8, F32, FP8, F32, F32, F16, TensorQuant, False>
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>;
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// clang-format on
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TYPED_TEST_SUITE(TestCkTileGroupedGemmQuant_Tensor, KernelTypes_Tensor);
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#define TEST_CLASS_NAME TestCkTileGroupedGemmQuant_Tensor
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#include "test_grouped_gemm_quant_ut_cases.inc"
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#undef TEST_CLASS_NAME
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@@ -1,6 +1,6 @@
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#pragma once
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TYPED_TEST(TestCkTileGroupedGemmQuant, Basic)
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TYPED_TEST(TEST_CLASS_NAME, Basic)
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{
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const int group_count = 8;
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std::vector<int> Ms;
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@@ -29,7 +29,7 @@ TYPED_TEST(TestCkTileGroupedGemmQuant, Basic)
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// No Hot Loop Test Case, this is to test the correctness of the kernel when there is no hot loop
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// Using 256x256x128 to match the test kernel's tile size (M_Tile=256, N_Tile=256, K_Tile=128)
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TYPED_TEST(TestCkTileGroupedGemmQuant, SmallUniform) //
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TYPED_TEST(TEST_CLASS_NAME, SmallUniform) //
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{
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const int group_count = 2;
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std::vector<int> Ms;
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@@ -55,3 +55,29 @@ TYPED_TEST(TestCkTileGroupedGemmQuant, SmallUniform) //
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this->Run(Ms, Ns, Ks, stride_As, stride_Bs, stride_Cs, stride_AQs, stride_BQs, group_count);
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}
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TYPED_TEST(TEST_CLASS_NAME, OddTail) //
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{
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const int group_count = 2;
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std::vector<int> Ms;
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std::vector<int> Ns;
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std::vector<int> Ks;
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std::vector<int> stride_As;
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std::vector<int> stride_Bs;
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std::vector<int> stride_Cs;
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std::vector<int> stride_AQs;
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std::vector<int> stride_BQs;
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for(int i = 0; i < group_count; i++)
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{
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Ms.push_back(256);
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Ns.push_back(256);
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Ks.push_back(128);
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stride_As.push_back(0);
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stride_Bs.push_back(0);
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stride_Cs.push_back(0);
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stride_AQs.push_back(0);
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stride_BQs.push_back(0);
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}
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this->Run(Ms, Ns, Ks, stride_As, stride_Bs, stride_Cs, stride_AQs, stride_BQs, group_count);
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}
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@@ -17,23 +17,40 @@ template <typename Tuple>
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class TestCkTileGroupedGemmQuant : 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 CLayout = std::tuple_element_t<2, Tuple>;
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using ADataType = std::tuple_element_t<3, Tuple>;
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using AQDataType = std::tuple_element_t<4, Tuple>;
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using BDataType = std::tuple_element_t<5, Tuple>;
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using BQDataType = std::tuple_element_t<6, Tuple>;
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using AccDataType = std::tuple_element_t<7, Tuple>;
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using CDataType = std::tuple_element_t<8, Tuple>;
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static constexpr auto QuantType = std::tuple_element_t<9, Tuple>::value;
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using DsLayout = ck_tile::tuple<>;
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using DsDataType = ck_tile::tuple<>;
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using Row = ck_tile::tensor_layout::gemm::RowMajor;
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using Col = ck_tile::tensor_layout::gemm::ColumnMajor;
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using AQLayout = Row;
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using BQLayout = Col;
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static constexpr bool Persistent = true;
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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 CLayout = std::tuple_element_t<2, Tuple>;
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using ADataType = std::tuple_element_t<3, Tuple>;
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using AQDataType = std::tuple_element_t<4, Tuple>;
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using BDataType = std::tuple_element_t<5, Tuple>;
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using BQDataType = std::tuple_element_t<6, Tuple>;
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using AccDataType = std::tuple_element_t<7, Tuple>;
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using CDataType = std::tuple_element_t<8, Tuple>;
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static constexpr auto QuantType = std::tuple_element_t<9, Tuple>::value;
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using DsLayout = ck_tile::tuple<>;
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using DsDataType = ck_tile::tuple<>;
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using Row = ck_tile::tensor_layout::gemm::RowMajor;
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using Col = ck_tile::tensor_layout::gemm::ColumnMajor;
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using AQLayout = Row;
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using BQLayout = Col;
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static constexpr bool Persistent = true;
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static constexpr bool PreshuffleB = std::tuple_element_t<10, Tuple>::value;
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template <typename PrecType, ck_tile::index_t M_Warp_Tile>
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static constexpr ck_tile::index_t get_k_from_preshuffled_warp_tile()
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{
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#if defined(CK_GFX950_SUPPORT)
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if constexpr(M_Warp_Tile == 32)
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return sizeof(PrecType) == 2 ? 16 : 64;
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else
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return sizeof(PrecType) == 2 ? 32 : 128;
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#else
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if constexpr(M_Warp_Tile == 32)
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return sizeof(PrecType) == 2 ? 16 : 32;
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else
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return sizeof(PrecType) == 2 ? 32 : 64;
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#endif
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}
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struct GroupedGemKernelParam_Mfma
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{
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@@ -52,7 +69,9 @@ class TestCkTileGroupedGemmQuant : public ::testing::Test
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static const ck_tile::index_t M_Warp_Tile = 32;
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static const ck_tile::index_t N_Warp_Tile = 32;
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static const ck_tile::index_t K_Warp_Tile = 16;
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static const ck_tile::index_t K_Warp_Tile =
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TestCkTileGroupedGemmQuant::template get_k_from_preshuffled_warp_tile<BDataType,
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M_Warp_Tile>();
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};
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using grouped_gemm_kargs = ck_tile::QuantGroupedGemmHostArgs;
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@@ -66,8 +85,9 @@ class TestCkTileGroupedGemmQuant : public ::testing::Test
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const ck_tile::index_t num_groups,
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void* kargs_ptr)
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{
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constexpr bool TransposeC = false;
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constexpr bool DoubleSmemBuffer = false;
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constexpr bool TransposeC = false;
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constexpr bool DoubleSmemBuffer =
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PreshuffleB; // currently DoubleSmemBuffer is only supported for preshuffled B
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constexpr int kBlockPerCu = 1;
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constexpr ck_tile::index_t TileParitionerGroupNum = 8;
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@@ -90,7 +110,7 @@ class TestCkTileGroupedGemmQuant : public ::testing::Test
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GroupedGemKernelParam::kPadN,
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GroupedGemKernelParam::kPadK,
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false,
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false,
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PreshuffleB,
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ALayout,
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BLayout,
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CLayout,
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@@ -126,11 +146,13 @@ class TestCkTileGroupedGemmQuant : public ::testing::Test
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BDataType,
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scheduler>>::type;
|
||||
|
||||
using GemmPipeline = typename std::conditional<
|
||||
QuantType == ck_tile::QuantType::BQuantGrouped,
|
||||
ck_tile::BQuantGemmPipelineAgBgCrCompV3<QuantGemmProblem>,
|
||||
ck_tile::GemmPipelineAgBgCrCompV3<QuantGemmProblem>>::type;
|
||||
|
||||
using GemmPipeline = std::conditional_t<
|
||||
QuantType == ck_tile::QuantType::RowColQuant ||
|
||||
QuantType == ck_tile::QuantType::TensorQuant,
|
||||
ck_tile::GemmPipelineAgBgCrCompV3<QuantGemmProblem>,
|
||||
std::conditional_t<PreshuffleB == true,
|
||||
ck_tile::WPQuantBPipelineAgBgCrV2<QuantGemmProblem>,
|
||||
ck_tile::BQuantGemmPipelineAgBgCrCompV3<QuantGemmProblem>>>;
|
||||
using GemmEpilogue = ck_tile::CShuffleEpilogue<
|
||||
ck_tile::CShuffleEpilogueProblem<ADataType,
|
||||
BDataType,
|
||||
@@ -344,7 +366,18 @@ class TestCkTileGroupedGemmQuant : public ::testing::Test
|
||||
bq_tensors[i].get_element_space_size_in_bytes()));
|
||||
|
||||
a_m_k_dev_buf[i]->ToDevice(a_m_k_tensors[i].data());
|
||||
b_k_n_dev_buf[i]->ToDevice(b_k_n_tensors[i].data());
|
||||
|
||||
if constexpr(PreshuffleB && QuantType == ck_tile::QuantType::BQuantGrouped)
|
||||
{
|
||||
auto b_shuffle_host =
|
||||
ck_tile::shuffle_b<GroupedGemKernelParam_Mfma>(b_k_n_tensors[i]);
|
||||
b_k_n_dev_buf[i]->ToDevice(b_shuffle_host.data());
|
||||
}
|
||||
else
|
||||
{
|
||||
b_k_n_dev_buf[i]->ToDevice(b_k_n_tensors[i].data());
|
||||
}
|
||||
|
||||
aq_dev_buf[i]->ToDevice(aq_tensors[i].data());
|
||||
bq_dev_buf[i]->ToDevice(bq_tensors[i].data());
|
||||
c_m_n_dev_buf[i]->SetZero();
|
||||
@@ -485,3 +518,13 @@ class TestCkTileGroupedGemmQuant : public ::testing::Test
|
||||
EXPECT_TRUE(pass);
|
||||
}
|
||||
};
|
||||
|
||||
// Aliases for split test files
|
||||
template <typename Tuple>
|
||||
using TestCkTileGroupedGemmQuant_RowCol = TestCkTileGroupedGemmQuant<Tuple>;
|
||||
|
||||
template <typename Tuple>
|
||||
using TestCkTileGroupedGemmQuant_Tensor = TestCkTileGroupedGemmQuant<Tuple>;
|
||||
|
||||
template <typename Tuple>
|
||||
using TestCkTileGroupedGemmQuant_BQuant = TestCkTileGroupedGemmQuant<Tuple>;
|
||||
|
||||
Reference in New Issue
Block a user