| /* |
| * Copyright (c) 2019 ARM Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * Permission is hereby granted, free of charge, to any person obtaining a copy |
| * of this software and associated documentation files (the "Software"), to |
| * deal in the Software without restriction, including without limitation the |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| * sell copies of the Software, and to permit persons to whom the Software is |
| * furnished to do so, subject to the following conditions: |
| * |
| * The above copyright notice and this permission notice shall be included in all |
| * copies or substantial portions of the Software. |
| * |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| #include "arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h" |
| #include "arm_compute/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.h" |
| #include "arm_compute/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h" |
| #include "arm_compute/core/KernelDescriptors.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "arm_compute/runtime/CL/CLTensor.h" |
| #include "arm_compute/runtime/CL/CLTensorAllocator.h" |
| #include "tests/CL/CLAccessor.h" |
| #include "tests/CL/Helper.h" |
| #include "tests/PaddingCalculator.h" |
| #include "tests/datasets/ShapeDatasets.h" |
| #include "tests/framework/Asserts.h" |
| #include "tests/framework/Macros.h" |
| #include "tests/framework/datasets/Datasets.h" |
| #include "tests/validation/Validation.h" |
| #include "tests/validation/fixtures/GEMMFixture.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| using namespace arm_compute::misc::shape_calculator; |
| |
| // Create function for CLGEMMReshapeLHSMatrixKernel |
| using CLGEMMReshapeLHSMatrix = CLSynthetizeFunction<CLGEMMReshapeLHSMatrixKernel>; |
| |
| // Create function for CLGEMMReshapeRHSMatrixKernel |
| using CLGEMMReshapeRHSMatrix = CLSynthetizeFunction<CLGEMMReshapeRHSMatrixKernel>; |
| |
| // Create function for CLGEMMMatrixMultiplyKernel |
| using CLGEMMMatrixMultiplyReshaped = CLSynthetizeFunction<CLGEMMMatrixMultiplyKernel>; |
| |
| // Fixture for GEMMMatrixMultiplyInterleavedTransposedValidationFixture |
| template <typename T> |
| using CLGEMMMatrixMultiplyReshapedFixture = |
| GEMMMatrixMultiplyInterleavedTransposedValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>; |
| |
| // Fixture for GEMMMatrixMultiplyInterleavedTransposed3DValidationFixture |
| template <typename T> |
| using CLGEMMMatrixMultiplyReshaped3DFixture = |
| GEMMMatrixMultiplyInterleavedTransposed3DValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>; |
| |
| namespace |
| { |
| // *INDENT-OFF* |
| // clang-format off |
| RelativeTolerance<float> rel_tolerance_f32(0.001f); |
| constexpr float abs_tolerance_f32(0.0001f); |
| |
| RelativeTolerance<half> rel_tolerance_f16(half(0.2)); |
| constexpr float tolerance_num_f16 = 0.02f; |
| |
| /** Alpha values to test - Precommit */ |
| const auto alpha_values = framework::dataset::make("alpha", {1.0f, -0.75f} ); |
| |
| /** Beta values to test - Precommit */ |
| const auto beta_values = framework::dataset::make("beta", {-0.35f, 0.0f} ); |
| |
| /** M values to test - Precommit */ |
| const auto m_values_precommit = framework::dataset::make("M", 37); |
| |
| /** N values to test - Precommit */ |
| const auto n_values_precommit = framework::dataset::make("N", 51); |
| |
| /** K values to test - Precommit */ |
| const auto k_values_precommit = framework::dataset::make("K", 23); |
| |
| /** M values to test - Nightly */ |
| const auto m_values_nightly = framework::dataset::make("M", {421, 1}); |
| |
| /** N values to test - Nightly */ |
| const auto n_values_nightly = framework::dataset::make("N", 323); |
| |
| /** K values to test - Nightly */ |
| const auto k_values_nightly = framework::dataset::make("K", 207); |
| |
| /** M_W values to test - Precommit */ |
| const auto m_w_values_precommit = framework::dataset::make("M_W", 5); |
| |
| /** M_H values to test - Precommit */ |
| const auto m_h_values_precommit = framework::dataset::make("M_H", 7); |
| |
| /** M_W values to test - Nightly */ |
| const auto m_w_values_nightly = framework::dataset::make("M_W", 13); |
| |
| /** M_H values to test - Nightly */ |
| const auto m_h_values_nightly = framework::dataset::make("M_H", 27); |
| |
| /** Batch size values to test */ |
| const auto b_values = framework::dataset::make("batch_size", 1, 3); |
| |
| /** Activation values to test */ |
| const auto act_values = framework::dataset::make("Activation", |
| { |
| ActivationLayerInfo(), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f), |
| }); |
| |
| /** V0 values to test - Precommit */ |
| const auto v0_values_precommit = framework::dataset::make("V0", 2); |
| |
| /** H0 values to test - Precommit */ |
| const auto h0_values_precommit = framework::dataset::make("H0", 4); |
| |
| /** V0 values to test - Nightly */ |
| const auto v0_values_nightly = framework::dataset::make("V0", {2, 4}); |
| |
| /** H0 values to test - Nightly */ |
| const auto h0_values_nightly = framework::dataset::make("H0", { 2, 4 }); |
| |
| /** Broadcast bias from vector to matrix */ |
| const auto broadcast_bias_values = framework::dataset::make("broadcast_bias", {false, true} ); |
| |
| /** GPU architectures values to test */ |
| const auto gpu_arch_values = framework::dataset::make("GPUArch", |
| { |
| GPUTarget::MIDGARD, |
| GPUTarget::BIFROST |
| }); |
| |
| /** Data types values to test in the configuration */ |
| const auto data_type_values = framework::dataset::make("DataType", |
| { |
| DataType::F32, |
| DataType::F16 |
| }); |
| |
| /** M values to test */ |
| const auto fp16_mixed_precision_values = framework::dataset::make("fp16_mixed_precision", {true, false}); |
| |
| /** Configuration test */ |
| void validate_configuration(unsigned int m_value, unsigned int n_value, unsigned int k_value, unsigned int b_value, unsigned int v0_value, unsigned int h0_value, bool broadcast_bias, bool fp16_mixed_precision, const ActivationLayerInfo &act_info, DataType data_type, GPUTarget gpu_arch_value) |
| { |
| GEMMLHSMatrixInfo lhs_info; |
| lhs_info.m0 = 4; |
| lhs_info.k0 = 4; |
| lhs_info.v0 = v0_value; |
| lhs_info.interleave = true; |
| lhs_info.transpose = true; |
| |
| GEMMRHSMatrixInfo rhs_info; |
| rhs_info.n0 = data_type == DataType::F32? 4 : 8; |
| rhs_info.k0 = 1; |
| rhs_info.h0 = h0_value; |
| rhs_info.interleave = false; |
| rhs_info.transpose = false; |
| |
| GEMMReshapeInfo reshape_info(m_value, n_value, k_value, rhs_info.h0, lhs_info.v0, 0, false, broadcast_bias); |
| |
| const TensorShape lhs_shape(k_value, m_value, b_value); |
| const TensorShape lhs_shape_reshaped = compute_lhs_reshaped_shape(TensorInfo(lhs_shape, 1, data_type), |
| lhs_info, |
| false); |
| |
| const TensorShape rhs_shape(n_value, k_value, b_value); |
| const TensorShape rhs_shape_reshaped = compute_rhs_reshaped_shape(TensorInfo(rhs_shape, 1, data_type), |
| rhs_info); |
| |
| const TensorShape dst_shape = compute_mm_shape(TensorInfo(lhs_shape_reshaped, 1, data_type), |
| TensorInfo(rhs_shape_reshaped, 1, data_type), |
| reshape_info); |
| |
| const TensorShape bias_shape(n_value, |
| broadcast_bias? 1 : m_value, |
| broadcast_bias? 1 : b_value); |
| |
| // Create tensors |
| CLTensor lhs_reshaped = create_tensor<CLTensor>(lhs_shape_reshaped, data_type); |
| CLTensor rhs_reshaped = create_tensor<CLTensor>(rhs_shape_reshaped, data_type); |
| CLTensor bias = create_tensor<CLTensor>(bias_shape, data_type); |
| CLTensor dst = create_tensor<CLTensor>(dst_shape, data_type); |
| |
| ARM_COMPUTE_EXPECT(lhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(rhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| // Create and configure function |
| CLGEMMMatrixMultiplyReshaped gemm; |
| gemm.configure(gpu_arch_value, &lhs_reshaped, &rhs_reshaped, &bias, &dst, 1.0f, 2.0f, true, reshape_info, fp16_mixed_precision, act_info); |
| } |
| } // namespace |
| |
| TEST_SUITE(CL) |
| TEST_SUITE(GEMMMatrixMultiplyInterleavedTransposed) |
| TEST_SUITE(Float) |
| TEST_SUITE(FP32) |
| DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values_precommit, |
| n_values_precommit), |
| k_values_precommit), |
| framework::dataset::make("batch_size", 1)), |
| v0_values_precommit), |
| h0_values_precommit), |
| broadcast_bias_values), |
| framework::dataset::make("fp16_mixed_precision", false)), |
| act_values), |
| data_type_values), |
| gpu_arch_values), |
| m_value, n_value, k_value, b_value, v0_value, h0_value, broadcast_bias, fp16_mixed_precision_value, act_value, data_type_value, gpu_arch_value) |
| { |
| validate_configuration(m_value, n_value, k_value, b_value, v0_value, h0_value, broadcast_bias, fp16_mixed_precision_value, act_value, data_type_value, gpu_arch_value); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values_precommit, |
| n_values_precommit), |
| k_values_precommit), |
| b_values), |
| alpha_values), |
| beta_values), |
| v0_values_precommit), |
| h0_values_precommit), |
| broadcast_bias_values), |
| framework::dataset::make("fp16_mixed_precision", false)), |
| act_values), |
| framework::dataset::make("DataType", DataType::F32)), |
| gpu_arch_values)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::NIGHTLY, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values_nightly, |
| n_values_nightly), |
| k_values_nightly), |
| b_values), |
| alpha_values), |
| beta_values), |
| v0_values_nightly), |
| h0_values_nightly), |
| broadcast_bias_values), |
| framework::dataset::make("fp16_mixed_precision", false)), |
| act_values), |
| framework::dataset::make("DataType", DataType::F32)), |
| gpu_arch_values)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_w_values_precommit, |
| m_h_values_precommit), |
| n_values_precommit), |
| k_values_precommit), |
| b_values), |
| alpha_values), |
| beta_values), |
| v0_values_precommit), |
| h0_values_precommit), |
| broadcast_bias_values), |
| framework::dataset::make("fp16_mixed_precision", false)), |
| act_values), |
| framework::dataset::make("DataType", DataType::F32)), |
| gpu_arch_values)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::NIGHTLY, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_w_values_nightly, |
| m_h_values_nightly), |
| n_values_nightly), |
| k_values_nightly), |
| b_values), |
| alpha_values), |
| beta_values), |
| v0_values_nightly), |
| h0_values_nightly), |
| broadcast_bias_values), |
| framework::dataset::make("fp16_mixed_precision", false)), |
| act_values), |
| framework::dataset::make("DataType", DataType::F32)), |
| gpu_arch_values)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); |
| } |
| |
| 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( |
| m_values_precommit, |
| n_values_precommit), |
| k_values_precommit), |
| b_values), |
| alpha_values), |
| beta_values), |
| v0_values_precommit), |
| h0_values_precommit), |
| broadcast_bias_values), |
| fp16_mixed_precision_values), |
| act_values), |
| framework::dataset::make("DataType", DataType::F16)), |
| gpu_arch_values)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::NIGHTLY, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values_nightly, |
| n_values_nightly), |
| k_values_nightly), |
| b_values), |
| alpha_values), |
| beta_values), |
| v0_values_nightly), |
| h0_values_nightly), |
| broadcast_bias_values), |
| fp16_mixed_precision_values), |
| act_values), |
| framework::dataset::make("DataType", DataType::F16)), |
| gpu_arch_values)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_w_values_precommit, |
| m_h_values_precommit), |
| n_values_precommit), |
| k_values_precommit), |
| b_values), |
| alpha_values), |
| beta_values), |
| v0_values_precommit), |
| h0_values_precommit), |
| broadcast_bias_values), |
| fp16_mixed_precision_values), |
| act_values), |
| framework::dataset::make("DataType", DataType::F16)), |
| gpu_arch_values)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::NIGHTLY, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_w_values_nightly, |
| m_h_values_nightly), |
| n_values_nightly), |
| k_values_nightly), |
| b_values), |
| alpha_values), |
| beta_values), |
| v0_values_nightly), |
| h0_values_nightly), |
| broadcast_bias_values), |
| fp16_mixed_precision_values), |
| act_values), |
| framework::dataset::make("DataType", DataType::F16)), |
| gpu_arch_values)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16); |
| } |
| |
| TEST_SUITE_END() // FP16 |
| TEST_SUITE_END() // Float |
| TEST_SUITE_END() // GEMMMatrixMulipltyInterleavedTransposed |
| TEST_SUITE_END() // CL |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
