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* convnd_fwd fp16 example * update example * update example * update instance * updating refernce conv * update reference conv * update conv fwd profiler * update conv 1d and 3d instance * update include path * clean * update profiler for conv bwd data and weight * update conv bwd weight * clean * update conv example * update profiler for conv bwd weight * update ckprofiler for conv bwd data * fix reference conv bwd data bug; update conv bwd data test * update examples * fix initialization issue * update test for conv fwd * clean * clean * remove test case too sensitive to error threshhold * fix test * clean * fix build * adding conv multiple d * adding conv multiple D * add matrix padder * add gemm padding to convnd * adding group conv * update gemm multi-d * refactor * refactor * refactor * clean * clean * refactor * refactor * reorg * add ds * add bias * clean * add G * adding group * adding group * adding group * update Tensor * clean * update example * update DeviceGemmMultipleD_Xdl_CShuffle * update conv bwd-data and bwd-weight * upate contraction example * update gemm and batch gemm with e permute * fix example build * instance for grouped conv1d * update example * adding group conv instance * update gemm bilinear instance * update gemm+add+add+fastgelu instance * update profiler * update profiler * update test * update test and client example * clean * add grouped conv into profiler * update profiler * clean * add test grouped conv, update all conv test to gtest * update test
80 lines
3.1 KiB
C++
80 lines
3.1 KiB
C++
// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
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#include <algorithm>
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#include <cstdlib>
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#include <iostream>
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#include <numeric>
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#include <tuple>
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#include <vector>
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#include "ck/ck.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
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#include "ck/tensor_operation/gpu/device/device_gemm.hpp"
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#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
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#include "ck/library/tensor_operation_instance/gpu/gemm.hpp"
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#include "ck/library/utility/check_err.hpp"
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#include "ck/library/utility/device_memory.hpp"
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#include "ck/library/utility/host_tensor.hpp"
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#include "ck/library/utility/host_tensor_generator.hpp"
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#include "ck/library/reference_tensor_operation/cpu/reference_gemm.hpp"
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#include "test/gemm/gemm_util.hpp"
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int main()
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{
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using ADataType = int8_t;
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using BDataType = int8_t;
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using CDataType = int8_t;
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using AccDataType = int32_t;
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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 PassThrough = ck::tensor_operation::element_wise::PassThrough;
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auto test = [&](auto a_layout, auto b_layout, auto c_layout) {
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bool pass = true;
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using DeviceOp = ck::tensor_operation::device::DeviceGemm<decltype(a_layout),
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decltype(b_layout),
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decltype(c_layout),
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ADataType,
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BDataType,
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CDataType,
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PassThrough,
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PassThrough,
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PassThrough>;
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const auto gemmPtrs =
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ck::tensor_operation::device::instance::DeviceOperationInstanceFactory<
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DeviceOp>::GetInstances();
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for(auto& gemmPtr : gemmPtrs)
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{
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pass &= ck::gemm_util::TestGemm<std::unique_ptr<DeviceOp>,
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ADataType,
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BDataType,
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CDataType,
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AccDataType,
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decltype(a_layout),
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decltype(b_layout),
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decltype(c_layout),
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PassThrough,
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PassThrough,
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PassThrough>{}(gemmPtr);
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}
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return pass;
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};
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bool pass = test(Row{}, Row{}, Row{}) && test(Row{}, Col{}, Row{}) &&
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test(Col{}, Row{}, Row{}) && test(Col{}, Col{}, Row{});
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std::cout << "TestGemm ..... " << (pass ? "SUCCESS" : "FAILURE") << std::endl;
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return pass ? 0 : 1;
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}
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