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219 lines
8.4 KiB
C++
219 lines
8.4 KiB
C++
/*******************************************************************************
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*
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* MIT License
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*
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* Copyright (c) 2022 Advanced Micro Devices, Inc.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*
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*******************************************************************************/
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#include <gtest/gtest.h>
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#include <gtest/gtest_common.hpp>
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#include <miopen/generic_search.hpp>
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#include <miopen/miopen.h>
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#include <miopen/search_options.hpp>
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#include <miopen/solver_id.hpp>
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#include <serialize.hpp>
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#include <fusionHost.hpp>
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#include <miopen/fusion.hpp>
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#include <miopen/fusion/solvers.hpp>
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#include <miopen/fusion/fusion_invoke_params.hpp>
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#include "tensor_util.hpp"
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#include "get_handle.hpp"
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#include "cba_find2.hpp"
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namespace cba_find2_infer {
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bool IsTestSupportedForDevice()
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{
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using e_mask = enabled<Gpu::gfx94X, Gpu::gfx103X, Gpu::gfx110X, Gpu::gfx115X>;
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// gfx120X is not enabled due to WORKAROUND_SWDEV_479810
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using d_mask = disabled<Gpu::None>;
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return ::IsTestSupportedForDevMask<d_mask, e_mask>();
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}
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struct GPU_ConvBiasActivFind2Infer_FP32 : ConvBiasActivInferFind2Test<float>
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{
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};
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struct GPU_ConvBiasActivFind2InferFusionFind_FP32 : ConvBiasActivInferFind2Test<float>
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{
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};
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struct GPU_ConvBiasActivFind2Infer_FP16 : ConvBiasActivInferFind2Test<half_float::half>
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{
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};
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template <typename Solver, typename TestCase>
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void RunSolver(miopen::FusedProblem& problem,
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const miopen::AnyInvokeParams& invoke_ctx,
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const TestCase& conv_config,
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bool& test_skipped)
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{
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auto& handle = get_handle();
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Solver solv{};
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const auto plan = problem.AsFusionPlan();
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const auto fusion_desc = miopen::FusionDescription{&plan};
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auto fusion_ctx = miopen::FusionContext{handle};
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if(!solv.IsApplicable(fusion_ctx, fusion_desc))
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{
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test_skipped = true;
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GTEST_SKIP() << solv.SolverDbId() << " Not Applicable" << conv_config;
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}
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ASSERT_TRUE(solv.IsApplicable(fusion_ctx, fusion_desc));
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auto sol = solv.GetSolution(fusion_ctx, fusion_desc);
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ASSERT_TRUE(sol.Succeeded());
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ASSERT_TRUE(sol.invoker_factory);
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const auto invoker = handle.PrepareInvoker(*sol.invoker_factory, sol.construction_params);
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(invoker)(handle, invoke_ctx);
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handle.Finish();
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}
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template <typename Solver>
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void RunTunableSolver(miopen::FusedProblem& problem,
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const miopen::AnyInvokeParams& invoke_ctx,
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const ConvTestCaseBase& conv_config,
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bool& test_skipped)
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{
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auto& handle = get_handle();
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Solver solv{};
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const auto plan = problem.AsFusionPlan();
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const auto fusion_desc = miopen::FusionDescription{&plan};
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auto fusion_ctx = miopen::FusionContext{handle};
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if(!solv.IsApplicable(fusion_ctx, fusion_desc))
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{
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test_skipped = true;
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GTEST_SKIP() << solv.SolverDbId() << " Not Applicable" << conv_config;
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}
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ASSERT_TRUE(solv.IsApplicable(fusion_ctx, fusion_desc));
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auto sol = solv.GetSolution(
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fusion_ctx, fusion_desc, solv.GetDefaultPerformanceConfig(fusion_ctx, fusion_desc));
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ASSERT_TRUE(sol.Succeeded());
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ASSERT_TRUE(sol.invoker_factory);
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const auto invoker = handle.PrepareInvoker(*sol.invoker_factory, sol.construction_params);
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(invoker)(handle, invoke_ctx);
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handle.Finish();
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}
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bool SkipTest() { return get_handle_xnack(); }
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} // namespace cba_find2_infer
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using namespace cba_find2_infer;
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TEST_P(GPU_ConvBiasActivFind2Infer_FP32, ConvBiasActivAsm1x1UFind2Float)
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{
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RunTunableSolver<miopen::solver::fusion::ConvBiasActivAsm1x1U>(
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fused_problem, invoke_params, conv_config, test_skipped);
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}
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TEST_P(GPU_ConvBiasActivFind2Infer_FP32, ConvHipDirectFwdFind2Fused)
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{
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RunTunableSolver<miopen::solver::fusion::ConvHipDirectFwdFused>(
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fused_problem, invoke_params, conv_config, test_skipped);
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}
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TEST_P(GPU_ConvBiasActivFind2Infer_FP32, ConvBinWinogradRxSFind2Fused)
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{
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RunSolver<miopen::solver::fusion::ConvBinWinogradRxSFused>(
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fused_problem, invoke_params, conv_config, test_skipped);
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}
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TEST_P(GPU_ConvBiasActivFind2Infer_FP32, ConvBinWinogradRxSf2x3g1Find2Fused)
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{
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RunSolver<miopen::solver::fusion::ConvBinWinogradRxSf2x3g1Fused>(
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fused_problem, invoke_params, conv_config, test_skipped);
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}
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TEST_P(GPU_ConvBiasActivFind2Infer_FP16, ConvWinoFuryRxSf2x3Find2Fused)
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{
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RunSolver<miopen::solver::fusion::ConvWinoFuryRxSFused<2, 3>>(
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fused_problem, invoke_params, conv_config, test_skipped);
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}
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TEST_P(GPU_ConvBiasActivFind2Infer_FP16, ConvWinoRageRxSf2x3Find2Fused)
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{
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RunSolver<miopen::solver::fusion::ConvWinoRageRxSFused<2, 3>>(
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fused_problem, invoke_params, conv_config, test_skipped);
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}
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TEST_P(GPU_ConvBiasActivFind2Infer_FP16, ConvCKIgemmFwdBiasActivFind2Fused)
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{
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RunTunableSolver<miopen::solver::fusion::ConvCKIgemmFwdBiasActivFused>(
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fused_problem, invoke_params, conv_config, test_skipped);
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}
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#if MIOPEN_BACKEND_HIP
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TEST_P(GPU_ConvBiasActivFind2InferFusionFind_FP32, ConvBiasActivFind2Float_testFind)
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{
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if(SkipTest())
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{
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test_skipped = true;
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GTEST_SKIP() << "Fusion does not support xnack";
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}
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if(!IsTestSupportedForDevice())
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{
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test_skipped = true;
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GTEST_SKIP() << "Fusion not supported for this device";
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}
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miopen::solver::debug::TuningIterationScopedLimiter tuning_limit{5};
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std::vector<miopen::Solution> solutions;
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auto options = miopen::FindOptions{};
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options.find_enforce = miopen::FindEnforce{miopen::FindEnforceAction::SearchDbUpdate};
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ASSERT_NO_THROW(solutions = fused_problem.FindSolutions(get_handle(), options, 10));
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auto tensors = std::unordered_map<miopenTensorArgumentId_t, miopen::Solution::RunInput>{
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{miopenTensorConvolutionX, in_dev.get()},
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{miopenTensorConvolutionW, wei_dev.get()},
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{miopenTensorActivationY, out_dev.get()},
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{miopenTensorBias, bias_dev.get()},
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};
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Workspace wspace;
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for(auto& solution : solutions)
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{
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auto cur_sol_ws = solution.GetWorkspaceSize();
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wspace.resize(cur_sol_ws);
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ASSERT_NO_THROW(solution.Run(get_handle(), tensors, wspace.ptr(), cur_sol_ws));
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ValidateResult();
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}
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}
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INSTANTIATE_TEST_SUITE_P(
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Full,
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GPU_ConvBiasActivFind2InferFusionFind_FP32,
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testing::Combine(testing::Values(miopenActivationRELU),
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testing::ValuesIn(GetNetworkForFusionCompileStepTest<ConvTestCaseBase>()),
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testing::Values(miopenTensorNCHW)));
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#endif
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INSTANTIATE_TEST_SUITE_P(Full,
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GPU_ConvBiasActivFind2Infer_FP32,
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testing::Combine(testing::Values(miopenActivationRELU),
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testing::ValuesIn(GetNetwork1<ConvTestCaseBase>()),
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testing::Values(miopenTensorNCHW)));
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INSTANTIATE_TEST_SUITE_P(Full,
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GPU_ConvBiasActivFind2Infer_FP16,
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testing::Combine(testing::Values(miopenActivationPASTHRU,
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miopenActivationLOGISTIC,
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miopenActivationTANH,
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miopenActivationRELU,
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miopenActivationLEAKYRELU),
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testing::ValuesIn(GetNetwork1<ConvTestCaseBase>()),
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testing::Values(miopenTensorNCHW)));
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