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Add contraction profiler and tests (#701)
* Add contraction profiler and tests * Build and style fixes * Allow to use any elementwise operator for ref_contraction * Introduce profile_contraction_scale and profile_contraction_bilinear * Make ref_contraction generic and extend interface tests * Stylistic minor fixes * Extend test_contraction_interface
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include <iostream>
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#include <sstream>
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#include "ck/tensor_operation/gpu/device/device_base.hpp"
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#include "ck/library/utility/host_tensor.hpp"
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#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
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namespace ck {
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namespace tensor_operation {
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namespace host {
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// hardcoded for NumDimM == NumDimN == NumDimK == 2
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template <ck::index_t NumDimM,
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ck::index_t NumDimN,
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ck::index_t NumDimK,
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typename ADataType,
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typename BDataType,
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typename CDataType,
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typename AccDataType,
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typename AElementwiseOperation,
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typename BElementwiseOperation,
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ck::enable_if_t<NumDimM == 2 && NumDimN == 2 && NumDimK == 2, bool> = false>
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struct ReferenceContraction_M2_N2_K2 : public ck::tensor_operation::device::BaseOperator
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{
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// Argument
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struct Argument : public ck::tensor_operation::device::BaseArgument
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{
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Argument(const Tensor<ADataType>& a_ms_ks,
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const Tensor<BDataType>& b_ns_ks,
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Tensor<CDataType>& c_ms_ns,
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AElementwiseOperation a_element_op,
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BElementwiseOperation b_element_op)
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: a_ms_ks_{a_ms_ks},
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b_ns_ks_{b_ns_ks},
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c_ms_ns_{c_ms_ns},
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a_element_op_{a_element_op},
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b_element_op_{b_element_op}
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{
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}
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const Tensor<ADataType>& a_ms_ks_;
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const Tensor<BDataType>& b_ns_ks_;
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Tensor<CDataType>& c_ms_ns_;
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AElementwiseOperation a_element_op_;
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BElementwiseOperation b_element_op_;
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};
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// Invoker
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struct Invoker : public ck::tensor_operation::device::BaseInvoker
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{
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using Argument = ReferenceContraction_M2_N2_K2::Argument;
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float Run(const Argument& arg)
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{
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auto f_ms_ns = [&](auto m0, auto m1, auto n0, auto n1) {
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const ck::index_t K0 = arg.a_ms_ks_.mDesc.GetLengths()[2];
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const ck::index_t K1 = arg.a_ms_ks_.mDesc.GetLengths()[3];
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AccDataType v_acc = 0;
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for(ck::index_t k0 = 0; k0 < K0; ++k0)
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{
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for(ck::index_t k1 = 0; k1 < K1; ++k1)
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{
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AccDataType v_a;
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AccDataType v_b;
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arg.a_element_op_(
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v_a, ck::type_convert<const AccDataType>(arg.a_ms_ks_(m0, m1, k0, k1)));
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arg.b_element_op_(
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v_b, ck::type_convert<const AccDataType>(arg.b_ns_ks_(n0, n1, k0, k1)));
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v_acc += v_a * v_b;
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}
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}
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arg.c_ms_ns_(m0, m1, n0, n1) = v_acc;
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};
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make_ParallelTensorFunctor(f_ms_ns,
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arg.c_ms_ns_.mDesc.GetLengths()[0],
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arg.c_ms_ns_.mDesc.GetLengths()[1],
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arg.c_ms_ns_.mDesc.GetLengths()[2],
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arg.c_ms_ns_.mDesc.GetLengths()[3])(
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std::thread::hardware_concurrency());
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return 0;
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}
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float Run(const ck::tensor_operation::device::BaseArgument* p_arg,
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const StreamConfig& /* stream_config */ = StreamConfig{}) override
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{
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return Run(*dynamic_cast<const Argument*>(p_arg));
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}
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};
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static constexpr bool IsValidCompilationParameter()
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{
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// TODO: properly implement this check
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return true;
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}
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bool IsSupportedArgument(const ck::tensor_operation::device::BaseArgument*) override
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{
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return true;
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}
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static auto MakeArgument(const Tensor<ADataType>& a_ms_ks,
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const Tensor<BDataType>& b_ns_ks,
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Tensor<CDataType>& c_ms_ns,
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AElementwiseOperation a_element_op,
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BElementwiseOperation b_element_op)
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{
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return Argument{a_ms_ks, b_ns_ks, c_ms_ns, a_element_op, b_element_op};
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}
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static auto MakeInvoker() { return Invoker{}; }
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virtual std::unique_ptr<ck::tensor_operation::device::BaseInvoker> MakeInvokerPointer()
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{
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return std::make_unique<Invoker>(Invoker{});
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}
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std::string GetTypeString() const override
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{
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auto str = std::stringstream();
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// clang-format off
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str << "ReferenceContraction_M2_N2_K2"
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<< std::endl;
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// clang-format on
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return str.str();
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}
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};
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} // namespace host
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} // namespace tensor_operation
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} // namespace ck
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