1188 lines
89 KiB
C++
1188 lines
89 KiB
C++
/*
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* Copyright (c) 2018-2020 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/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/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h"
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#include "src/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.h"
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#include "src/core/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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// Create function for CLGEMMReshapeLHSMatrixKernel
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using CLGEMMReshapeLHSMatrix = CLSynthetizeFunction<CLGEMMReshapeLHSMatrixKernel>;
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// Create function for CLGEMMReshapeRHSMatrixKernel
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using CLGEMMReshapeRHSMatrix = CLSynthetizeFunction<CLGEMMReshapeRHSMatrixKernel>;
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// Create function for CLGEMMMatrixMultiplyReshapedKernel
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using CLGEMMMatrixMultiplyReshaped = CLSynthetizeFunction<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 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 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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});
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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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} // 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 */,
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1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
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GEMMLHSMatrixInfo(4,4,1,false,true),
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GEMMRHSMatrixInfo(4,4,1,true,true,false),
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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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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 */,
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1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
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GEMMLHSMatrixInfo(4,4,1,false,true),
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GEMMRHSMatrixInfo(4,4,1,true,true,false),
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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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GEMMKernelInfo(),
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GEMMKernelInfo(),
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GEMMKernelInfo(),
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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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false /**< 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 */,
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1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
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GEMMLHSMatrixInfo(4,4,1,false,true),
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GEMMRHSMatrixInfo(4,4,1,true,true,false),
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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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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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false /**< Flag used to broadcast the bias addition */,
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true /**< wider accumm */,
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true /**< 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 */,
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1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
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GEMMLHSMatrixInfo(4,4,1,false,true),
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GEMMRHSMatrixInfo(4,4,1,true,true,false),
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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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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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false /**< 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 */,
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1 /**< Multiplication factor for the height of the 4x4 interleaved block */,
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GEMMLHSMatrixInfo(4,4,1,false,true),
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GEMMRHSMatrixInfo(4,4,2,true,false,false),
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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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})),
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framework::dataset::make("Expected", { true, true, false, false, false, true, true,true})),
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input0_info ,input1_info, input2_info, output_info, lhs_info, rhs_info, gemm_info, expected)
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{
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ARM_COMPUTE_EXPECT(bool(CLGEMMMatrixMultiplyReshapedKernel::validate(&input0_info.clone()->set_is_resizable(true),
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&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)) == expected, framework::LogLevel::ERRORS);
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}
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TEST_SUITE(Float)
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TEST_SUITE(FP32)
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FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::ALL,
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combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
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m_values,
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n_values),
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k_values),
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b_values),
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m0_values_precommit),
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n0_values_precommit),
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k0_values_precommit),
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v0_values_precommit),
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h0_values_precommit),
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i_values_lhs),
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i_values_rhs),
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framework::dataset::make("export_to_cl_image_rhs", false)),
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framework::dataset::make("DataType", DataType::F32)),
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a_values_precommit),
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beta_values_precommit),
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broadcast_bias_values),
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lhs_transpose_values),
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act_values))
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{
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// Validate output
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validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
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}
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FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::DISABLED,
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combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
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m_values,
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n_values),
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k_values),
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b_values),
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m0_values_nightly),
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n0_values_nightly),
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k0_values_nightly),
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v0_values_nightly),
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h0_values_nightly),
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i_values_lhs),
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i_values_rhs),
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framework::dataset::make("export_to_cl_image_rhs", false)),
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framework::dataset::make("DataType", DataType::F32)),
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a_values_nightly),
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beta_values_nightly),
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broadcast_bias_values),
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lhs_transpose_values),
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act_values))
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{
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// Validate output
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validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
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}
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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
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
|
|
}
|
|
|
|
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
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
|
|
}
|
|
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,
|
|
false})),
|
|
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_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
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
|
|
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
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
|
|
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
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
|
|
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
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
|
|
}
|
|
|
|
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,
|
|
false})),
|
|
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_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
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
|
|
}
|
|
|
|
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
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
|
|
}
|
|
|
|
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
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
|
|
}
|
|
|
|
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
|
|
validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
|
|
}
|
|
TEST_SUITE_END() // MixedPrecision
|
|
TEST_SUITE_END() // Float
|
|
TEST_SUITE_END() // GEMMMatrixMultiplyReshaped
|
|
TEST_SUITE_END() // CL
|
|
} // namespace validation
|
|
} // namespace test
|
|
} // namespace arm_compute
|