/* * Copyright (c) 2018-2020 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/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 "src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.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/GEMMReshapeRHSMatrixFixture.h" namespace arm_compute { namespace test { namespace validation { namespace { // *INDENT-OFF* // clang-format off /** Batch size values to test */ const auto b_values = framework::dataset::make("batchsize", 1, 3); /** N0 values to test */ const auto n0_values_nt_s32 = framework::dataset::make("N0", { 1, 2, 3 }); const auto n0_values_nt_s16 = framework::dataset::make("N0", { 4, 8 }); const auto n0_values_nt_s8 = framework::dataset::make("N0", { 16 }); const auto n0_values_t_s32 = framework::dataset::make("N0", { 4, 8 }); const auto n0_values_t_s16 = framework::dataset::make("N0", { 16 }); const auto n0_values_t_s8 = framework::dataset::make("N0", { 2, 3 }); /** K0 values to test */ const auto k0_values_nt_s32 = framework::dataset::make("K0", { 1, 2 }); const auto k0_values_nt_s16 = framework::dataset::make("K0", { 16 }); const auto k0_values_nt_s8 = framework::dataset::make("K0", { 3,4 }); const auto k0_values_t_s32 = framework::dataset::make("K0", { 2, 3 }); const auto k0_values_t_s16 = framework::dataset::make("K0", { 4, 8 }); const auto k0_values_t_s8 = framework::dataset::make("K0", { 16 }); /** H0 values to test */ const auto h0_values = framework::dataset::make("H0", 1, 4); /** Interleave values to test */ const auto i_values = framework::dataset::make("interleave", { true, false }); } // namespace using namespace arm_compute::misc::shape_calculator; // Initialize the output tensor with zero and fill the border with zero using CLGEMMReshapeRHSMatrix = CLSynthetizeFunctionInitOutputWithZeroAndWithZeroConstantBorder; template using CLGEMMReshapeRHSMatrixFixture = GEMMReshapeRHSMatrixValidationFixture; TEST_SUITE(CL) TEST_SUITE(GEMMReshapeRHSMatrix) // *INDENT-OFF* // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32), // Mismatching data types TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32), // Wrong n0 value TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32), // Wrong k0 value TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32), // Wrong h0 value TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32), // n0 > 16 TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32), // k0 > 16 TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32), // k0 == 1 && transpose }), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(64U, 2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 2U, 2U), 1, DataType::F16), TensorInfo(TensorShape(32U, 2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 2U, 2U), 1, DataType::F32), })), framework::dataset::make("N0",{ 4, 0, 4, 4, 4, 17, 4, 4 })), framework::dataset::make("K0",{ 4, 4, 0, 4, 4, 4, 17, 1 })), framework::dataset::make("H0",{ 4, 4, 4, 0, 4, 4, 4, 4 })), framework::dataset::make("Expected", { false, false, false, false, false, false, false})), input_info, output_info, n0, k0, h0, expected) { GEMMRHSMatrixInfo rhs_info; rhs_info.n0 = n0; rhs_info.k0 = k0; rhs_info.h0 = h0; rhs_info.transpose = true; rhs_info.interleave = true; bool has_error = bool(CLGEMMReshapeRHSMatrixKernel::validate(&input_info.clone()->set_is_resizable(false), (output_info.total_size() == 0) ? nullptr : &output_info.clone()->set_is_resizable(false), rhs_info)); ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS); } DATA_TEST_CASE(ValidatePadding, framework::DatasetMode::ALL, combine(combine(combine(combine( framework::dataset::make("InputShape", { TensorShape(32U, 16U, 1U), TensorShape(32U, 16U, 2U) }), framework::dataset::make("N0",{ 4 })), framework::dataset::make("K0",{ 4, 8, 16 })), framework::dataset::make("H0",{ 1, 2, 4 })), framework::dataset::make("DataType",{ DataType::F32, DataType::F16 })), input_shape, n0, k0, h0, data_type) { CLTensor input; CLTensor output; input.info()->init(input_shape, 1, data_type); unsigned int padding = 0; GEMMRHSMatrixInfo rhs_info; rhs_info.n0 = n0; rhs_info.k0 = k0; rhs_info.h0 = h0; rhs_info.transpose = true; rhs_info.interleave = true; rhs_info.export_to_cl_image = image2d_from_buffer_supported(CLKernelLibrary::get().get_device()) && (get_cl_image_pitch_alignment(CLKernelLibrary::get().get_device()) != 0); if(rhs_info.export_to_cl_image) { TensorShape output_shape = compute_rhs_reshaped_shape(*input.info(), rhs_info); constexpr unsigned int num_floats_per_pixel = 4; const unsigned int pixel_aligment = get_cl_image_pitch_alignment(CLKernelLibrary::get().get_device()); const unsigned int row_pitch_alignment = pixel_aligment * num_floats_per_pixel; const unsigned int round_up_width = ((output_shape[0] + row_pitch_alignment - 1) / row_pitch_alignment) * row_pitch_alignment; padding = round_up_width - output_shape[0]; } CLGEMMReshapeRHSMatrixKernel kernel; kernel.configure(&input, &output, rhs_info); ARM_COMPUTE_EXPECT((output.info()->padding().right == padding), framework::LogLevel::ERRORS); } // clang-format on // *INDENT-ON* // Run S32 tests only for transpose = false FIXTURE_DATA_TEST_CASE(S32_NT, CLGEMMReshapeRHSMatrixFixture, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(datasets::SmallGEMMReshape2DShapes(), b_values), framework::dataset::make("DataType", DataType::S32)), n0_values_nt_s32), k0_values_nt_s32), h0_values), i_values), framework::dataset::make("transpose", false))) { // Validate output validate(CLAccessor(_target), _reference); } // Run S32 tests only for transpose = true FIXTURE_DATA_TEST_CASE(S32_T, CLGEMMReshapeRHSMatrixFixture, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(datasets::SmallGEMMReshape2DShapes(), b_values), framework::dataset::make("DataType", DataType::S32)), n0_values_t_s32), k0_values_t_s32), h0_values), i_values), framework::dataset::make("transpose", true))) { // Validate output validate(CLAccessor(_target), _reference); } // Run S16 tests only for transpose = false FIXTURE_DATA_TEST_CASE(S16_NT, CLGEMMReshapeRHSMatrixFixture, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(datasets::SmallGEMMReshape2DShapes(), b_values), framework::dataset::make("DataType", DataType::S16)), n0_values_nt_s16), k0_values_nt_s16), h0_values), i_values), framework::dataset::make("transpose", false))) { // Validate output validate(CLAccessor(_target), _reference); } // Run S16 tests only for transpose = true FIXTURE_DATA_TEST_CASE(S16_T, CLGEMMReshapeRHSMatrixFixture, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(datasets::SmallGEMMReshape2DShapes(), b_values), framework::dataset::make("DataType", DataType::S16)), n0_values_t_s16), k0_values_t_s16), h0_values), i_values), framework::dataset::make("transpose", true))) { // Validate output validate(CLAccessor(_target), _reference); } // Run S8 tests only for transpose = false FIXTURE_DATA_TEST_CASE(S8_NT, CLGEMMReshapeRHSMatrixFixture, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(datasets::SmallGEMMReshape2DShapes(), b_values), framework::dataset::make("DataType", DataType::S8)), n0_values_nt_s8), k0_values_nt_s8), h0_values), i_values), framework::dataset::make("transpose", false))) { // Validate output validate(CLAccessor(_target), _reference); } // Run S8 tests only for transpose = true FIXTURE_DATA_TEST_CASE(S8_T, CLGEMMReshapeRHSMatrixFixture, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(datasets::SmallGEMMReshape2DShapes(), b_values), framework::dataset::make("DataType", DataType::S8)), n0_values_t_s8), k0_values_t_s8), h0_values), i_values), framework::dataset::make("transpose", true))) { // Validate output validate(CLAccessor(_target), _reference); } TEST_SUITE_END() // GEMMReshapeRHSMatrix TEST_SUITE_END() // CL } // namespace validation } // namespace test } // namespace arm_compute