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https://github.com/ROCm/composable_kernel.git
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70e4eb567f
* Add license header. * Reduce number of logged output. Add constant initialization. * Add functional tests for grouped_gemm with different kbatch value. * Add debug log informations + remove unused code. * Don't pass kbatch to CalculateKPadded. * Turn on logging in grouped gemm and gemm splitk profiler * Debug: limit number of test cases to run; * Log more information and initialize with constant value. * Turn on DEBUG_LOG * Add more debug log informations. * Limit the number of instances to compile. * Use GridwiseGemmPipeline * Use KBatch to calculate K0 * Multiple DebugLog messages. * Unit tests for multiple KBatch values. * Refactoring * Disable logging * extract out of if statement KBatch update. * Uncomment instances. * Disable DebugLog. * Use Kbatch when calculate KPadded. * Fix CGridDesc padding. * Use available helper functions. * Uncomment code commented for debuggin. * Remove unnecessary debug log messages. * Uncomment previously commented code for debug purposes. * Add KBatch info to profiler output summary log. * Add gtests for gemm splitk using ckProfiler API. * Add more test-cases for different data layout. * Add more test cases for gemm splitk * Remove old test. * Unit tests for MKNK ggemm interface. * Fix and add more unit-tests. * Constepxr everything! * Increase error threshold for fp16 and splitk. Since we're using fp16 atomic add for splitk there's a known precision loss. --------- Co-authored-by: Adam Osewski <aosewski@amd.com> Co-authored-by: zjing14 <zhangjing14@gmail.com>
79 lines
2.5 KiB
C++
79 lines
2.5 KiB
C++
// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include <string>
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#include <sstream>
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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 "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 "include/ck/utility/data_type.hpp"
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#include "profiler/profile_gemm_splitk_impl.hpp"
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namespace ck {
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namespace test {
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template <typename Tuple>
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class TestGemmSplitK : public testing::Test
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{
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using Row = ck::tensor_layout::gemm::RowMajor;
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using F32 = float;
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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 = Row;
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using ADataType = std::tuple_element_t<2, Tuple>;
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using BDataType = std::tuple_element_t<3, Tuple>;
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using CDataType = std::tuple_element_t<4, Tuple>;
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public:
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static constexpr bool verify_ = true;
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static constexpr int init_method_ = 1; // decimal value initialization
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static constexpr bool log_ = false;
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static constexpr bool bench_ = false; // measure kernel performance
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std::vector<int> k_batches_;
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void SetUp() override { k_batches_ = {1, 2, 3, 5, 8}; }
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void Run(const int M,
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const int N,
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const int K,
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const int StrideA,
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const int StrideB,
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const int StrideC)
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{
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for(auto kb : k_batches_)
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{
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RunSingle(M, N, K, StrideA, StrideB, StrideC, kb);
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}
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}
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void RunSingle(const int M,
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const int N,
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const int K,
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const int StrideA,
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const int StrideB,
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const int StrideC,
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int kbatch = 1)
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{
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bool pass = ck::profiler::profile_gemm_splitk_impl<ADataType,
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BDataType,
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F32,
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CDataType,
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ALayout,
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BLayout,
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CLayout>(
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verify_, init_method_, log_, bench_, M, N, K, StrideA, StrideB, StrideC, kbatch);
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EXPECT_TRUE(pass);
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}
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};
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} // namespace test
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} // namespace ck
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