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1708 lines
115 KiB
1708 lines
115 KiB
/*
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* Copyright (c) 2018-2022 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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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
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell 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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#include "arm_compute/core/KernelDescriptors.h"
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#include "arm_compute/core/Types.h"
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#include "arm_compute/core/experimental/PostOps.h"
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#include "arm_compute/core/utils/misc/ShapeCalculator.h"
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#include "arm_compute/runtime/CL/CLTensor.h"
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#include "arm_compute/runtime/CL/CLTensorAllocator.h"
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#include "src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedKernel.h"
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#include "src/gpu/cl/kernels/ClGemmReshapeLhsMatrixKernel.h"
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#include "src/gpu/cl/kernels/ClGemmReshapeRhsMatrixKernel.h"
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#include "tests/CL/CLAccessor.h"
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#include "tests/CL/Helper.h"
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#include "tests/PaddingCalculator.h"
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#include "tests/datasets/ShapeDatasets.h"
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#include "tests/framework/Asserts.h"
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#include "tests/framework/Macros.h"
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#include "tests/framework/datasets/Datasets.h"
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#include "tests/validation/Validation.h"
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#include "tests/validation/fixtures/GEMMFixture.h"
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namespace arm_compute
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{
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namespace test
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{
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namespace validation
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{
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using namespace arm_compute::misc::shape_calculator;
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using namespace arm_compute::opencl::kernels;
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// Create function for ClGemmReshapeLhsMatrixKernel
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using CLGEMMReshapeLHSMatrix = CLSynthetizeOperator<ClGemmReshapeLhsMatrixKernel>;
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// Create function for ClGemmReshapeRhsMatrixKernel
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using CLGEMMReshapeRHSMatrix = CLSynthetizeOperator<ClGemmReshapeRhsMatrixKernel>;
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// Create function for ClGemmMatrixMultiplyReshapedKernel
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using CLGEMMMatrixMultiplyReshaped = CLSynthetizeOperator<ClGemmMatrixMultiplyReshapedKernel>;
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// Fixture for CLGEMMMatrixMultiplyReshaped
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template <typename T>
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using CLGEMMMatrixMultiplyReshapedFixture = GEMMMatrixMultiplyReshapedValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>;
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// Fixture for CLGEMMMatrixMultiplyReshaped with post ops
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template <typename T>
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using CLGEMMMatrixMultiplyReshapedWithPostOpsFixture =
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GEMMMatrixMultiplyReshapedWithPostOpsValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>;
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// Fixture for CLGEMMMatrixMultiplyReshaped mixed precision
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template <typename T>
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using CLGEMMMatrixMultiplyReshapedMixedPrecisionFixture =
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GEMMMatrixMultiplyReshapedValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped, true>;
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// Fixture for CLGEMMMatrixMultiplyReshaped mixed precision with post ops
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template <typename T>
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using CLGEMMMatrixMultiplyReshapedMixedPrecisionWithPostOpsFixture =
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GEMMMatrixMultiplyReshapedWithPostOpsValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped, true>;
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// Fixture for CLGEMMMatrixMultiplyReshaped3D
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template <typename T>
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using CLGEMMMatrixMultiplyReshaped3DFixture = GEMMMatrixMultiplyReshaped3DValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>;
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// Fixture for CLGEMMMatrixMultiplyReshaped3D mixed precision
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template <typename T>
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using CLGEMMMatrixMultiplyReshaped3DMixedPrecisionFixture =
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GEMMMatrixMultiplyReshaped3DValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped, true>;
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namespace
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{
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// *INDENT-OFF*
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// clang-format off
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RelativeTolerance<float> rel_tolerance_f32(0.001f);
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constexpr float abs_tolerance_f32(0.0001f);
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RelativeTolerance<float> rel_tolerance_f16_mixed_precision(0.001f);
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constexpr float abs_tolerance_f16_mixed_precision(0.01f);
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RelativeTolerance<float> rel_tolerance_f16(0.001f);
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constexpr float abs_tolerance_f16(0.01f);
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/** M values to test */
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const auto m_values = framework::dataset::make("M", 17);
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/** M_W values to test */
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const auto m_w_values = framework::dataset::make("M_W", 5);
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/** M_H values to test */
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const auto m_h_values = framework::dataset::make("M_H", 7);
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/** N values to test */
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const auto n_values = framework::dataset::make("N", 21);
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/** K values to test */
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const auto k_values = framework::dataset::make("K", 13);
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/** Batch size values to test */
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const auto b_values = framework::dataset::make("batch_size", 2, 3);
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/** Activation values to test */
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const auto act_values = framework::dataset::make("Activation",
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{
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
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ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ELU),
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});
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/** Alpha values to test - Precommit */
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const auto a_values_precommit = framework::dataset::make("alpha", {-0.75f} );
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/** Beta values to test - Precommit */
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const auto beta_values_precommit = framework::dataset::make("beta", {-0.35f} );
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/** M0 values to test - Precommit */
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const auto m0_values_precommit = framework::dataset::make("M0", { 4 });
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/** N0 values to test - Precommit */
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const auto n0_values_precommit = framework::dataset::make("N0", { 4 });
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/** K0 values to test - Precommit */
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const auto k0_values_precommit = framework::dataset::make("K0", { 4 });
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/** V0 values to test - Precommit */
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const auto v0_values_precommit = framework::dataset::make("V0", 1, 3);
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/** H0 values to test - Precommit */
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const auto h0_values_precommit = framework::dataset::make("H0", 1, 3);
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/** Alpha values to test - Nightly */
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const auto a_values_nightly = framework::dataset::make("alpha", {1.0f} );
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/** Beta values to test - Nightly */
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const auto beta_values_nightly = framework::dataset::make("beta", {1.0f} );
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/** M0 values to test - Nightly */
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const auto m0_values_nightly = framework::dataset::make("M0", { 8 });
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/** N0 values to test - Nightly */
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const auto n0_values_nightly = framework::dataset::make("N0", { 8 });
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/** K0 values to test - Nightly */
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const auto k0_values_nightly = framework::dataset::make("K0", { 4 });
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/** N0 values to test with export to OpenCL image object - Nightly */
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const auto n0_export_to_cl_image_values_nightly = framework::dataset::make("N0", { 4, 8, 16 });
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/** K0 values to test with export to OpenCL image object - Nightly */
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const auto k0_export_to_cl_image_values_nightly = framework::dataset::make("K0", { 4, 8, 16 });
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/** V0 values to test - Nightly */
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const auto v0_values_nightly = framework::dataset::make("V0", 1, 3);
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/** H0 values to test - Nightly */
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const auto h0_values_nightly = framework::dataset::make("H0", 1, 3);
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/** Interleave values to test with LHS matrix */
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const auto i_values_lhs = framework::dataset::make("interleave_lhs", { true, false });
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/** Interleave values to test with RHS matrix */
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const auto i_values_rhs = framework::dataset::make("interleave_rhs", { true, false });
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/** Broadcast bias from vector to matrix */
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const auto broadcast_bias_values = framework::dataset::make("broadcast_bias", { false, true } );
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/** LHS transposed values */
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const auto lhs_transpose_values = framework::dataset::make("lhs_transpose", { false, true } );
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/** Post Ops */
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using PostOpArgBroadcast = CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<float>::PostOpArgBroadcast;
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experimental::PostOpList<PostOpArgBroadcast> post_ops_1()
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{
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experimental::PostOpList<PostOpArgBroadcast> post_ops{};
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post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::LINEAR, 0.5F, 0.0F});
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post_ops.push_back_op<experimental::PostOpEltwiseAdd<PostOpArgBroadcast>>(
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std::make_tuple(true, true, false), // If broadcast in dims 0, 1 and 2
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0,
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ConvertPolicy::SATURATE);
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post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F});
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return post_ops;
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}
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experimental::PostOpList<PostOpArgBroadcast> post_ops_2()
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{
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experimental::PostOpList<PostOpArgBroadcast> post_ops{};
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post_ops.push_back_op<experimental::PostOpEltwiseAdd<PostOpArgBroadcast>>(
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std::make_tuple(false, true, true), // If broadcast in dims 0, 1 and 2
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1,
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ConvertPolicy::SATURATE);
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post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F});
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return post_ops;
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}
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experimental::PostOpList<PostOpArgBroadcast> post_ops_3()
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{
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experimental::PostOpList<PostOpArgBroadcast> post_ops{};
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post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F});
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post_ops.push_back_op<experimental::PostOpEltwiseAdd<PostOpArgBroadcast>>(
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std::make_tuple(false, false, true), // If broadcast in dims 0, 1 and 2
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1,
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ConvertPolicy::SATURATE);
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return post_ops;
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}
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// To test that the output of the main op is the first parameter in prelu post op
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experimental::PostOpList<PostOpArgBroadcast> post_ops_4()
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{
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experimental::PostOpList<PostOpArgBroadcast> post_ops{};
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post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::LINEAR, 0.5F, 0.0F});
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post_ops.push_back_op<experimental::PostOpEltwisePRelu<PostOpArgBroadcast>>(
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std::make_tuple(false, false, true), // If true, broadcast in corresponding dim: 0, 1 or 2
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0,
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ConvertPolicy::SATURATE);
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post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F});
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return post_ops;
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}
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// To test that the output of the main op is the second parameter in prelu post op i.e. it is the alpha_param
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experimental::PostOpList<PostOpArgBroadcast> post_ops_5()
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{
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experimental::PostOpList<PostOpArgBroadcast> post_ops{};
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post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::LINEAR, 0.5F, 0.0F});
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post_ops.push_back_op<experimental::PostOpEltwisePRelu<PostOpArgBroadcast>>(
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std::make_tuple(false, false, false), // If true, broadcast in corresponding dim: 0, 1 or 2
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1,
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ConvertPolicy::SATURATE);
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post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F});
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return post_ops;
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}
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/** Different Post Op Lists */
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const auto post_op_lists = framework::dataset::make("post_op_lists", {
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post_ops_1(),
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post_ops_2(),
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post_ops_3(),
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post_ops_4(),
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post_ops_5()
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} );
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bool is_post_op_list_valid(unsigned int m, unsigned int n, unsigned int k, unsigned int batch, DataType data_type, const experimental::PostOpList<ITensorInfo*>& post_ops)
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{
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const auto lhs_info = GEMMLHSMatrixInfo(4,4,1,false,true);
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const auto rhs_info = GEMMRHSMatrixInfo(4,4,1,true,true,false);
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// Create TensorInfo for post op arguments
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TensorInfo input0_info(TensorShape(k, m, batch), 1, data_type);
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TensorInfo input1_info(TensorShape(n, k, batch), 1, data_type);
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TensorInfo input2_info(TensorShape(n), 1, data_type);
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TensorInfo output_info(TensorShape(n, m, batch), 1, data_type);
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const TensorInfo reshaped_input0_info = input0_info.clone()->set_tensor_shape(misc::shape_calculator::compute_lhs_reshaped_shape(input0_info, lhs_info));
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const TensorInfo reshaped_input1_info = input1_info.clone()->set_tensor_shape(misc::shape_calculator::compute_rhs_reshaped_shape(input1_info, rhs_info));
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GEMMKernelInfo gemm_info(m, n, k, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
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false /**< reinterpret the input as 3D */,
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true /**< Flag used to broadcast the bias addition */,
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false /**< wider accumm */,
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false /**< has pad y */,
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ActivationLayerInfo::ActivationFunction::IDENTITY,
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1 /**< Multiplication factor for the width of the 1xW transposed block */,
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1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
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lhs_info,
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rhs_info,
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0 /**< Offset to be added to each element of the matrix A */,
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0 /**< Offset to be added to each element of the matrix B */,
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post_ops);
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return bool(ClGemmMatrixMultiplyReshapedKernel::validate(&reshaped_input0_info.clone()->set_is_resizable(true),
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&reshaped_input1_info.clone()->set_is_resizable(true),
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&input2_info.clone()->set_is_resizable(true),
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&output_info.clone()->set_is_resizable(true),1.f,1.f,
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lhs_info,
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rhs_info,
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gemm_info));
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}
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} // namespace
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TEST_SUITE(CL)
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TEST_SUITE(GEMMMatrixMultiplyReshaped)
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// *INDENT-OFF*
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// clang-format off
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DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
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framework::dataset::make("Input0Info", { TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F32), // OK
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TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16), // OK
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TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::QASYMM8), // Data type not supported
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TensorInfo(TensorShape(10U, 5U, 2U), 1, DataType::F32), // Incorrect dimension bias
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TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F32), // Mismatching shapes
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TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16), // OK, do not broadcast bias
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TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16), // OK, wider accummulation
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TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16), // OK, RHS 4,4,2
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}),
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framework::dataset::make("Input1Info",{ TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F16),
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TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::QASYMM8),
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TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F16),
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TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F16),
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TensorInfo(TensorShape(128U, 3U, 2U), 1, DataType::F16),
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})),
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framework::dataset::make("Input2Info", { TensorInfo(TensorShape(21U), 1, DataType::F32),
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TensorInfo(TensorShape(21U), 1, DataType::F16),
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TensorInfo(TensorShape(21U), 1, DataType::QASYMM8),
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TensorInfo(TensorShape(21U), 1, DataType::F32),
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TensorInfo(TensorShape(21U), 1, DataType::F32),
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TensorInfo(TensorShape(21U,17U), 1, DataType::F16),
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TensorInfo(TensorShape(21U,17U), 1, DataType::F16),
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TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),
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})),
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framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F32),
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TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),
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TensorInfo(TensorShape(21U,17U,2U), 1, DataType::QASYMM8),
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TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F32),
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TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F32),
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TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),
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TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),
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TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),
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})),
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framework::dataset::make("LHSMInfo",{
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GEMMLHSMatrixInfo(4,4,1,false,true),
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GEMMLHSMatrixInfo(4,4,1,false,true),
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GEMMLHSMatrixInfo(4,4,1,false,true),
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GEMMLHSMatrixInfo(4,2,4,false,false),
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GEMMLHSMatrixInfo(4,2,4,false,false),
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GEMMLHSMatrixInfo(4,4,1,false,true),
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GEMMLHSMatrixInfo(4,4,1,false,true),
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GEMMLHSMatrixInfo(4,4,1,false,true),
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})),
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framework::dataset::make("RHSMInfo",{
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GEMMRHSMatrixInfo(4,4,1,true,true,false),
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GEMMRHSMatrixInfo(4,4,1,true,true,false),
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GEMMRHSMatrixInfo(4,4,1,true,true,false),
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GEMMRHSMatrixInfo(2,2,1,true,false,false),
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GEMMRHSMatrixInfo(2,2,1,true,false,false),
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GEMMRHSMatrixInfo(4,4,1,true,true,false),
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GEMMRHSMatrixInfo(4,4,1,true,true,false),
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GEMMRHSMatrixInfo(4,4,2,true,false,false),
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})),
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framework::dataset::make("GEMMInfo",{
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GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
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21 /**<N Number of RHS columns*/,
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13 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
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false /**< reinterpret the input as 3D */,
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true /**< Flag used to broadcast the bias addition */,
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false /**< wider accumm */,
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false /**< has pad y */,
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ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
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1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(4,4,1,false,true),
|
|
GEMMRHSMatrixInfo(4,4,1,true,true,false),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */),
|
|
|
|
GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
|
|
21 /**<N Number of RHS columns*/,
|
|
13 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
true /**< Flag used to broadcast the bias addition */,
|
|
false /**< wider accumm */,
|
|
false /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(4,4,1,false,true),
|
|
GEMMRHSMatrixInfo(4,4,1,true,true,false),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */),
|
|
GEMMKernelInfo(),
|
|
GEMMKernelInfo(),
|
|
GEMMKernelInfo(),
|
|
|
|
GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
|
|
21 /**<N Number of RHS columns*/,
|
|
13 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
false /**< Flag used to broadcast the bias addition */,
|
|
false /**< wider accumm */,
|
|
false /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(4,4,1,false,true),
|
|
GEMMRHSMatrixInfo(4,4,1,true,true,false),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */),
|
|
|
|
|
|
GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
|
|
21 /**<N Number of RHS columns*/,
|
|
13 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
false /**< Flag used to broadcast the bias addition */,
|
|
true /**< wider accumm */,
|
|
true /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(4,4,1,false,true),
|
|
GEMMRHSMatrixInfo(4,4,1,true,true,false),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */),
|
|
|
|
GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
|
|
21 /**<N Number of RHS columns*/,
|
|
13 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
false /**< Flag used to broadcast the bias addition */,
|
|
false /**< wider accumm */,
|
|
false /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(4,4,1,false,true),
|
|
GEMMRHSMatrixInfo(4,4,2,true,false,false),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */),
|
|
})),
|
|
framework::dataset::make("Expected", { true, true, false, false, false, true, true,true})),
|
|
input0_info ,input1_info, input2_info, output_info, lhs_info, rhs_info, gemm_info, expected)
|
|
{
|
|
ARM_COMPUTE_EXPECT(bool(ClGemmMatrixMultiplyReshapedKernel::validate(&input0_info.clone()->set_is_resizable(true),
|
|
&input1_info.clone()->set_is_resizable(true),
|
|
&input2_info.clone()->set_is_resizable(true),
|
|
&output_info.clone()->set_is_resizable(true),1.f,1.f,
|
|
lhs_info,
|
|
rhs_info,
|
|
gemm_info)) == expected, framework::LogLevel::ERRORS);
|
|
}
|
|
TEST_SUITE(ValidateFusedPostOpsConfigs)
|
|
TEST_SUITE(Invalid)
|
|
TEST_CASE(UnsupportedPostOpSequence, framework::DatasetMode::ALL)
|
|
{
|
|
const auto data_type = DataType::F32;
|
|
const unsigned int m = 17;
|
|
const unsigned int n = 1;
|
|
const unsigned int k = 13;
|
|
const unsigned int batch = 2;
|
|
TensorShape post_op_arg0_shape(n, m, batch);
|
|
TensorInfo post_op_arg_info(post_op_arg0_shape, 1, data_type);
|
|
auto post_op_arg1_info = post_op_arg_info.clone();
|
|
|
|
// Unsupported sequence of post ops
|
|
experimental::PostOpList<ITensorInfo*> post_ops{};
|
|
post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>(
|
|
&post_op_arg_info,
|
|
1,
|
|
ConvertPolicy::SATURATE);
|
|
post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>(
|
|
post_op_arg1_info.get(),
|
|
0,
|
|
ConvertPolicy::SATURATE);
|
|
|
|
ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == false, framework::LogLevel::ERRORS);
|
|
}
|
|
TEST_CASE(OutputWidened, framework::DatasetMode::ALL)
|
|
{
|
|
// Invalid broadcast: post op tensors "widen" the output tensor
|
|
const auto data_type = DataType::F32;
|
|
const unsigned int m = 17;
|
|
const unsigned int n = 1;
|
|
const unsigned int k = 13;
|
|
const unsigned int batch = 2;
|
|
TensorShape post_op_arg_shape(n + 4, m, batch); // output's X dimension (n) is "widened", which is not allowed
|
|
TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type);
|
|
experimental::PostOpList<ITensorInfo*> post_ops{};
|
|
post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE);
|
|
|
|
ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == false, framework::LogLevel::ERRORS);
|
|
}
|
|
TEST_CASE(BroadcastInXDimOnly, framework::DatasetMode::ALL)
|
|
{
|
|
// Invalid broadcast: post op tensors broadcast in the first dimension (X) only
|
|
const auto data_type = DataType::F32;
|
|
const unsigned int m = 22;
|
|
const unsigned int n = 16;
|
|
const unsigned int k = 15;
|
|
const unsigned int batch = 3;
|
|
TensorShape post_op_arg_shape(1, m, batch);
|
|
TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type);
|
|
experimental::PostOpList<ITensorInfo*> post_ops{};
|
|
post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE);
|
|
|
|
ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == false, framework::LogLevel::ERRORS);
|
|
}
|
|
TEST_SUITE_END() // Invalid
|
|
TEST_SUITE(Valid)
|
|
TEST_CASE(EmptyPostOpList, framework::DatasetMode::ALL)
|
|
{
|
|
const auto data_type = DataType::F32;
|
|
const unsigned int m = 22;
|
|
const unsigned int n = 16;
|
|
const unsigned int k = 15;
|
|
const unsigned int batch = 3;
|
|
experimental::PostOpList<ITensorInfo*> post_ops{};
|
|
|
|
ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS);
|
|
}
|
|
TEST_CASE(BroadcastInYDimOnly, framework::DatasetMode::ALL)
|
|
{
|
|
const auto data_type = DataType::F32;
|
|
const unsigned int m = 22;
|
|
const unsigned int n = 16;
|
|
const unsigned int k = 15;
|
|
const unsigned int batch = 3;
|
|
TensorShape post_op_arg_shape(n, 1, batch);
|
|
TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type);
|
|
experimental::PostOpList<ITensorInfo*> post_ops{};
|
|
post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE);
|
|
|
|
ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS);
|
|
}
|
|
TEST_CASE(BroadcastInBothXandYDims, framework::DatasetMode::ALL)
|
|
{
|
|
const auto data_type = DataType::F32;
|
|
const unsigned int m = 22;
|
|
const unsigned int n = 16;
|
|
const unsigned int k = 15;
|
|
const unsigned int batch = 3;
|
|
TensorShape post_op_arg_shape(1, 1, batch);
|
|
TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type);
|
|
experimental::PostOpList<ITensorInfo*> post_ops{};
|
|
post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE);
|
|
|
|
ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS);
|
|
}
|
|
TEST_CASE(BroadcastInAllDims, framework::DatasetMode::ALL)
|
|
{
|
|
const auto data_type = DataType::F32;
|
|
const unsigned int m = 22;
|
|
const unsigned int n = 16;
|
|
const unsigned int k = 15;
|
|
const unsigned int batch = 3;
|
|
TensorShape post_op_arg_shape(1, 1, 1);
|
|
TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type);
|
|
experimental::PostOpList<ITensorInfo*> post_ops{};
|
|
post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE);
|
|
|
|
ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS);
|
|
}
|
|
TEST_SUITE_END() // Valid
|
|
TEST_SUITE_END() // ValidateFusedPostOps
|
|
TEST_SUITE(Float)
|
|
TEST_SUITE(FP32)
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F32)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
broadcast_bias_values),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::DISABLED,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_nightly),
|
|
n0_values_nightly),
|
|
k0_values_nightly),
|
|
v0_values_nightly),
|
|
h0_values_nightly),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F32)),
|
|
a_values_nightly),
|
|
beta_values_nightly),
|
|
broadcast_bias_values),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_w_values,
|
|
m_h_values),
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F32)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::DISABLED,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_w_values,
|
|
m_h_values),
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_nightly),
|
|
n0_values_nightly),
|
|
k0_values_nightly),
|
|
v0_values_nightly),
|
|
h0_values_nightly),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F32)),
|
|
a_values_nightly),
|
|
beta_values_nightly),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
TEST_SUITE(FusedPostOps)
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<float>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
framework::dataset::make("interleave_lhs", { false })),
|
|
framework::dataset::make("interleave_rhs", { false })),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F32)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
framework::dataset::make("broadcast_bias", { true } )),
|
|
lhs_transpose_values),
|
|
act_values),
|
|
post_op_lists)
|
|
)
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
TEST_SUITE_END() // FusedPostOps
|
|
|
|
TEST_SUITE(ExportToCLImage)
|
|
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
|
|
framework::dataset::make("Input0Info", { TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32), // OK or incorrect if cl_khr_image2d_from_buffer not supported
|
|
TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32), // OK or incorrect if cl_khr_image2d_from_buffer not supported
|
|
TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32), // OK or incorrect if cl_khr_image2d_from_buffer not supported
|
|
TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32), // Incorrect k0
|
|
TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32), // Incorrect n0
|
|
|
|
}),
|
|
framework::dataset::make("Input1Info",{ TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(512U, 8U, 2U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(128U, 32U, 2U), 1, DataType::F32),
|
|
|
|
})),
|
|
framework::dataset::make("Input2Info", { TensorInfo(TensorShape(64U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(64U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(64U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(64U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(64U), 1, DataType::F32),
|
|
|
|
})),
|
|
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32),
|
|
TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32),
|
|
|
|
})),
|
|
framework::dataset::make("LHSMInfo",{
|
|
GEMMLHSMatrixInfo(4, 4, 1, false, true),
|
|
GEMMLHSMatrixInfo(4, 8, 1, false, true),
|
|
GEMMLHSMatrixInfo(4, 4, 1, false, true),
|
|
GEMMLHSMatrixInfo(4, 2, 1, false, false),
|
|
GEMMLHSMatrixInfo(4, 4, 1, false, false),
|
|
|
|
})),
|
|
framework::dataset::make("RHSMInfo",{
|
|
GEMMRHSMatrixInfo(4, 4, 1, true, true, true),
|
|
GEMMRHSMatrixInfo(4, 8, 1, true, true, true),
|
|
GEMMRHSMatrixInfo(8, 4, 1, true, true, true),
|
|
GEMMRHSMatrixInfo(4, 2, 1, true, false, true),
|
|
GEMMRHSMatrixInfo(2, 4, 1, true, false, true),
|
|
})),
|
|
framework::dataset::make("GEMMInfo",{GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
|
|
64 /**<N Number of RHS columns*/,
|
|
64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
true /**< Flag used to broadcast the bias addition */,
|
|
false /**< wider accumm */,
|
|
false /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(),
|
|
GEMMRHSMatrixInfo(),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */),
|
|
GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
|
|
64 /**<N Number of RHS columns*/,
|
|
64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
true /**< Flag used to broadcast the bias addition */,
|
|
false /**< wider accumm */,
|
|
false /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(),
|
|
GEMMRHSMatrixInfo(),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */),
|
|
GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
|
|
64 /**<N Number of RHS columns*/,
|
|
64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
true /**< Flag used to broadcast the bias addition */,
|
|
false /**< wider accumm */,
|
|
false /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(),
|
|
GEMMRHSMatrixInfo(),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */),
|
|
|
|
GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
|
|
64 /**<N Number of RHS columns*/,
|
|
64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
true /**< Flag used to broadcast the bias addition */,
|
|
false /**< wider accumm */,
|
|
false /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(),
|
|
GEMMRHSMatrixInfo(),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */),
|
|
GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
|
|
64 /**<N Number of RHS columns*/,
|
|
64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
true /**< Flag used to broadcast the bias addition */,
|
|
false /**< wider accumm */,
|
|
false /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(),
|
|
GEMMRHSMatrixInfo(),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */)
|
|
})),
|
|
framework::dataset::make("Expected", { true,
|
|
true,
|
|
true,
|
|
false,
|
|
true})),
|
|
input0_info ,input1_info, input2_info, output_info, lhs_info, rhs_info, gemm_info, expected)
|
|
{
|
|
ARM_COMPUTE_EXPECT(bool(ClGemmMatrixMultiplyReshapedKernel::validate(&input0_info.clone()->set_is_resizable(true),
|
|
&input1_info.clone()->set_is_resizable(true),
|
|
&input2_info.clone()->set_is_resizable(true),
|
|
&output_info.clone()->set_is_resizable(true),1.f,1.f,
|
|
lhs_info,
|
|
rhs_info,
|
|
gemm_info)) == (expected && image2d_from_buffer_supported(CLKernelLibrary::get().get_device())), framework::LogLevel::ERRORS);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", true)),
|
|
framework::dataset::make("DataType", DataType::F32)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
broadcast_bias_values),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output only if validate() is successful
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_nightly),
|
|
n0_export_to_cl_image_values_nightly),
|
|
k0_export_to_cl_image_values_nightly),
|
|
v0_values_nightly),
|
|
h0_values_nightly),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", true)),
|
|
framework::dataset::make("DataType", DataType::F32)),
|
|
a_values_nightly),
|
|
beta_values_nightly),
|
|
broadcast_bias_values),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output only if validate() is successful
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_w_values,
|
|
m_h_values),
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", true)),
|
|
framework::dataset::make("DataType", DataType::F32)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output only if validate() is successful
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_w_values,
|
|
m_h_values),
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_nightly),
|
|
n0_export_to_cl_image_values_nightly),
|
|
k0_export_to_cl_image_values_nightly),
|
|
v0_values_nightly),
|
|
h0_values_nightly),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", true)),
|
|
framework::dataset::make("DataType", DataType::F32)),
|
|
a_values_nightly),
|
|
beta_values_nightly),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output only if validate() is successful
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
TEST_SUITE(FusedPostOps)
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<float>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
framework::dataset::make("interleave_lhs", { false })),
|
|
framework::dataset::make("interleave_rhs", { false })),
|
|
framework::dataset::make("export_to_cl_image_rhs", true)),
|
|
framework::dataset::make("DataType", DataType::F32)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
framework::dataset::make("broadcast_bias", { true } )),
|
|
lhs_transpose_values),
|
|
act_values),
|
|
post_op_lists)
|
|
)
|
|
{
|
|
// Validate output only if validate() is successful
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
TEST_SUITE_END() // FusedPostOps
|
|
|
|
TEST_SUITE_END() // ExportToCLImage
|
|
TEST_SUITE_END() // FP32
|
|
|
|
TEST_SUITE(FP16)
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
broadcast_bias_values),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::DISABLED,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_nightly),
|
|
n0_values_nightly),
|
|
k0_values_nightly),
|
|
v0_values_nightly),
|
|
h0_values_nightly),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_nightly),
|
|
beta_values_nightly),
|
|
broadcast_bias_values),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_w_values,
|
|
m_h_values),
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::DISABLED,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_w_values,
|
|
m_h_values),
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_nightly),
|
|
n0_values_nightly),
|
|
k0_values_nightly),
|
|
v0_values_nightly),
|
|
h0_values_nightly),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_nightly),
|
|
beta_values_nightly),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
TEST_SUITE(FusedPostOps)
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<half>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
framework::dataset::make("interleave_lhs", { false })),
|
|
framework::dataset::make("interleave_rhs", { false })),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
framework::dataset::make("broadcast_bias", { true } )),
|
|
lhs_transpose_values),
|
|
act_values),
|
|
post_op_lists)
|
|
)
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
TEST_SUITE_END() // FusedPostOps
|
|
|
|
TEST_SUITE(ExportToCLImage)
|
|
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
|
|
framework::dataset::make("Input0Info", { TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // OK or incorrect if cl_khr_image2d_from_buffer not supported
|
|
TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // OK or incorrect if cl_khr_image2d_from_buffer not supported
|
|
TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // OK or incorrect if cl_khr_image2d_from_buffer not supported
|
|
TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // Incorrect k0
|
|
TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // Incorrect n0
|
|
|
|
}),
|
|
framework::dataset::make("Input1Info",{ TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(512U, 8U, 2U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(128U, 32U, 2U), 1, DataType::F16),
|
|
|
|
})),
|
|
framework::dataset::make("Input2Info", { TensorInfo(TensorShape(64U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(64U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(64U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(64U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(64U), 1, DataType::F16),
|
|
|
|
})),
|
|
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
|
|
TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
|
|
|
|
})),
|
|
framework::dataset::make("LHSMInfo",{
|
|
GEMMLHSMatrixInfo(4, 4, 1, false, true),
|
|
GEMMLHSMatrixInfo(4, 8, 1, false, true),
|
|
GEMMLHSMatrixInfo(4, 4, 1, false, true),
|
|
GEMMLHSMatrixInfo(4, 2, 1, false, false),
|
|
GEMMLHSMatrixInfo(4, 4, 1, false, false),
|
|
|
|
})),
|
|
framework::dataset::make("RHSMInfo",{
|
|
GEMMRHSMatrixInfo(4, 4, 1, true, true, true),
|
|
GEMMRHSMatrixInfo(4, 8, 1, true, true, true),
|
|
GEMMRHSMatrixInfo(8, 4, 1, true, true, true),
|
|
GEMMRHSMatrixInfo(4, 2, 1, true, false, true),
|
|
GEMMRHSMatrixInfo(2, 4, 1, true, false, true),
|
|
})),
|
|
framework::dataset::make("GEMMInfo",{GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
|
|
64 /**<N Number of RHS columns*/,
|
|
64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
true /**< Flag used to broadcast the bias addition */,
|
|
false /**< wider accumm */,
|
|
false /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(),
|
|
GEMMRHSMatrixInfo(),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */),
|
|
GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
|
|
64 /**<N Number of RHS columns*/,
|
|
64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
true /**< Flag used to broadcast the bias addition */,
|
|
false /**< wider accumm */,
|
|
false /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(),
|
|
GEMMRHSMatrixInfo(),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */),
|
|
GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
|
|
64 /**<N Number of RHS columns*/,
|
|
64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
true /**< Flag used to broadcast the bias addition */,
|
|
false /**< wider accumm */,
|
|
false /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(),
|
|
GEMMRHSMatrixInfo(),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */),
|
|
|
|
GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
|
|
64 /**<N Number of RHS columns*/,
|
|
64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
true /**< Flag used to broadcast the bias addition */,
|
|
false /**< wider accumm */,
|
|
false /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(),
|
|
GEMMRHSMatrixInfo(),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */),
|
|
GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
|
|
64 /**<N Number of RHS columns*/,
|
|
64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
|
|
false /**< reinterpret the input as 3D */,
|
|
true /**< Flag used to broadcast the bias addition */,
|
|
false /**< wider accumm */,
|
|
false /**< has pad y */,
|
|
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
|
|
1 /**< Multiplication factor for the width of the 1xW transposed block */,
|
|
1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
|
|
GEMMLHSMatrixInfo(),
|
|
GEMMRHSMatrixInfo(),
|
|
0 /**< Offset to be added to each element of the matrix A */,
|
|
0 /**< Offset to be added to each element of the matrix B */)
|
|
})),
|
|
framework::dataset::make("Expected", { true,
|
|
true,
|
|
true,
|
|
false,
|
|
true})),
|
|
input0_info ,input1_info, input2_info, output_info, lhs_info, rhs_info, gemm_info, expected)
|
|
{
|
|
ARM_COMPUTE_EXPECT(bool(ClGemmMatrixMultiplyReshapedKernel::validate(&input0_info.clone()->set_is_resizable(true),
|
|
&input1_info.clone()->set_is_resizable(true),
|
|
&input2_info.clone()->set_is_resizable(true),
|
|
&output_info.clone()->set_is_resizable(true),1.f,1.f,
|
|
lhs_info,
|
|
rhs_info,
|
|
gemm_info)) == (expected && image2d_from_buffer_supported(CLKernelLibrary::get().get_device())), framework::LogLevel::ERRORS);
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", true)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
broadcast_bias_values),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output only if validate() is successful
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_nightly),
|
|
n0_export_to_cl_image_values_nightly),
|
|
k0_export_to_cl_image_values_nightly),
|
|
v0_values_nightly),
|
|
h0_values_nightly),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", true)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_nightly),
|
|
beta_values_nightly),
|
|
broadcast_bias_values),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output only if validate() is successful
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_w_values,
|
|
m_h_values),
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", true)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output only if validate() is successful
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::NIGHTLY,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_w_values,
|
|
m_h_values),
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_nightly),
|
|
n0_export_to_cl_image_values_nightly),
|
|
k0_export_to_cl_image_values_nightly),
|
|
v0_values_nightly),
|
|
h0_values_nightly),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", true)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_nightly),
|
|
beta_values_nightly),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output only if validate() is successful
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
TEST_SUITE(FusedPostOps)
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<half>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
framework::dataset::make("interleave_lhs", { false })),
|
|
framework::dataset::make("interleave_rhs", { false })),
|
|
framework::dataset::make("export_to_cl_image_rhs", true)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
framework::dataset::make("broadcast_bias", { true } )),
|
|
lhs_transpose_values),
|
|
act_values),
|
|
post_op_lists)
|
|
)
|
|
{
|
|
// Validate output only if validate() is successful
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
TEST_SUITE_END() // FusedPostOps
|
|
|
|
TEST_SUITE_END() // ExportToCLImage
|
|
TEST_SUITE_END() // FP16
|
|
|
|
TEST_SUITE(MixedPrecision)
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedMixedPrecisionFixture<half>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
broadcast_bias_values),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedMixedPrecisionFixture<half>, framework::DatasetMode::DISABLED,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_nightly),
|
|
n0_values_nightly),
|
|
k0_values_nightly),
|
|
v0_values_nightly),
|
|
h0_values_nightly),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_nightly),
|
|
beta_values_nightly),
|
|
broadcast_bias_values),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DMixedPrecisionFixture<half>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_w_values,
|
|
m_h_values),
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DMixedPrecisionFixture<half>, framework::DatasetMode::DISABLED,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_w_values,
|
|
m_h_values),
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_nightly),
|
|
n0_values_nightly),
|
|
k0_values_nightly),
|
|
v0_values_nightly),
|
|
h0_values_nightly),
|
|
i_values_lhs),
|
|
i_values_rhs),
|
|
framework::dataset::make("export_to_cl_image_rhs", false)),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_nightly),
|
|
beta_values_nightly),
|
|
lhs_transpose_values),
|
|
act_values))
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
TEST_SUITE(FusedPostOps)
|
|
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedMixedPrecisionWithPostOpsFixture<half>, framework::DatasetMode::ALL,
|
|
combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
|
|
m_values,
|
|
n_values),
|
|
k_values),
|
|
b_values),
|
|
m0_values_precommit),
|
|
n0_values_precommit),
|
|
k0_values_precommit),
|
|
v0_values_precommit),
|
|
h0_values_precommit),
|
|
framework::dataset::make("interleave_lhs", { false })),
|
|
framework::dataset::make("interleave_rhs", { false })),
|
|
framework::dataset::make("export_to_cl_image_rhs", { true, false })),
|
|
framework::dataset::make("DataType", DataType::F16)),
|
|
a_values_precommit),
|
|
beta_values_precommit),
|
|
framework::dataset::make("broadcast_bias", { true } )),
|
|
lhs_transpose_values),
|
|
act_values),
|
|
post_op_lists)
|
|
)
|
|
{
|
|
// Validate output
|
|
if(validate_result)
|
|
{
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
|
|
}
|
|
else
|
|
{
|
|
ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped");
|
|
framework::ARM_COMPUTE_PRINT_INFO();
|
|
}
|
|
}
|
|
|
|
TEST_SUITE_END() // FusedPostOps
|
|
|
|
TEST_SUITE_END() // MixedPrecision
|
|
TEST_SUITE_END() // Float
|
|
TEST_SUITE_END() // GEMMMatrixMultiplyReshaped
|
|
TEST_SUITE_END() // CL
|
|
} // namespace validation
|
|
} // namespace test
|
|
} // namespace arm_compute
|