| /* |
| * 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/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 "src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h" |
| #include "src/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.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/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 CLGEMMMatrixMultiplyReshapedKernel |
| using CLGEMMMatrixMultiplyReshaped = CLSynthetizeFunction<CLGEMMMatrixMultiplyReshapedKernel>; |
| |
| // Fixture for CLGEMMMatrixMultiplyReshaped |
| template <typename T> |
| using CLGEMMMatrixMultiplyReshapedFixture = GEMMMatrixMultiplyReshapedValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>; |
| |
| // Fixture for CLGEMMMatrixMultiplyReshaped mixed precision |
| template <typename T> |
| using CLGEMMMatrixMultiplyReshapedMixedPrecisionFixture = |
| GEMMMatrixMultiplyReshapedValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped, true>; |
| |
| // Fixture for CLGEMMMatrixMultiplyReshaped3D |
| template <typename T> |
| using CLGEMMMatrixMultiplyReshaped3DFixture = GEMMMatrixMultiplyReshaped3DValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>; |
| |
| // Fixture for CLGEMMMatrixMultiplyReshaped3D mixed precision |
| template <typename T> |
| using CLGEMMMatrixMultiplyReshaped3DMixedPrecisionFixture = |
| GEMMMatrixMultiplyReshaped3DValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped, true>; |
| |
| namespace |
| { |
| // *INDENT-OFF* |
| // clang-format off |
| RelativeTolerance<float> rel_tolerance_f32(0.001f); |
| constexpr float abs_tolerance_f32(0.0001f); |
| |
| RelativeTolerance<float> rel_tolerance_f16_mixed_precision(0.001f); |
| constexpr float abs_tolerance_f16_mixed_precision(0.01f); |
| |
| RelativeTolerance<float> rel_tolerance_f16(0.001f); |
| constexpr float abs_tolerance_f16(0.01f); |
| |
| /** M values to test */ |
| const auto m_values = framework::dataset::make("M", 17); |
| |
| /** M_W values to test */ |
| const auto m_w_values = framework::dataset::make("M_W", 5); |
| |
| /** M_H values to test */ |
| const auto m_h_values = framework::dataset::make("M_H", 7); |
| |
| /** N values to test */ |
| const auto n_values = framework::dataset::make("N", 21); |
| |
| /** K values to test */ |
| const auto k_values = framework::dataset::make("K", 13); |
| |
| /** Batch size values to test */ |
| const auto b_values = framework::dataset::make("batch_size", 2, 3); |
| |
| /** Activation values to test */ |
| const auto act_values = framework::dataset::make("Activation", |
| { |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f), |
| }); |
| |
| /** Alpha values to test - Precommit */ |
| const auto a_values_precommit = framework::dataset::make("alpha", {-0.75f} ); |
| |
| /** Beta values to test - Precommit */ |
| const auto beta_values_precommit = framework::dataset::make("beta", {-0.35f} ); |
| |
| /** M0 values to test - Precommit */ |
| const auto m0_values_precommit = framework::dataset::make("M0", { 4 }); |
| |
| /** N0 values to test - Precommit */ |
| const auto n0_values_precommit = framework::dataset::make("N0", { 4 }); |
| |
| /** K0 values to test - Precommit */ |
| const auto k0_values_precommit = framework::dataset::make("K0", { 4 }); |
| |
| /** V0 values to test - Precommit */ |
| const auto v0_values_precommit = framework::dataset::make("V0", 1, 3); |
| |
| /** H0 values to test - Precommit */ |
| const auto h0_values_precommit = framework::dataset::make("H0", 1, 3); |
| |
| /** Alpha values to test - Nightly */ |
| const auto a_values_nightly = framework::dataset::make("alpha", {1.0f} ); |
| |
| /** Beta values to test - Nightly */ |
| const auto beta_values_nightly = framework::dataset::make("beta", {1.0f} ); |
| |
| /** M0 values to test - Nightly */ |
| const auto m0_values_nightly = framework::dataset::make("M0", { 8 }); |
| |
| /** N0 values to test - Nightly */ |
| const auto n0_values_nightly = framework::dataset::make("N0", { 8 }); |
| |
| /** K0 values to test - Nightly */ |
| const auto k0_values_nightly = framework::dataset::make("K0", { 4 }); |
| |
| /** N0 values to test with export to OpenCL image object - Nightly */ |
| const auto n0_export_to_cl_image_values_nightly = framework::dataset::make("N0", { 4, 8, 16 }); |
| |
| /** K0 values to test with export to OpenCL image object - Nightly */ |
| const auto k0_export_to_cl_image_values_nightly = framework::dataset::make("K0", { 4, 8, 16 }); |
| |
| /** V0 values to test - Nightly */ |
| const auto v0_values_nightly = framework::dataset::make("V0", 1, 3); |
| |
| /** H0 values to test - Nightly */ |
| const auto h0_values_nightly = framework::dataset::make("H0", 1, 3); |
| |
| /** Interleave values to test with LHS matrix */ |
| const auto i_values_lhs = framework::dataset::make("interleave_lhs", { true, false }); |
| |
| /** Interleave values to test with RHS matrix */ |
| const auto i_values_rhs = framework::dataset::make("interleave_rhs", { true, false }); |
| |
| /** Broadcast bias from vector to matrix */ |
| const auto broadcast_bias_values = framework::dataset::make("broadcast_bias", { false, true } ); |
| |
| /** LHS transposed values */ |
| const auto lhs_transpose_values = framework::dataset::make("lhs_transpose", { false, true } ); |
| |
| /** Zero padding test */ |
| bool validate_zero_padding(unsigned int m_value, unsigned int n_value, unsigned int k_value, unsigned int b_value, |
| unsigned int m0_value, unsigned int n0_value, unsigned int k0_value, unsigned int h0_value, |
| bool i_value_rhs, bool t_value_rhs, bool export_to_cl_image, bool broadcast_bias, unsigned int depth_output_gemm3d, const ActivationLayerInfo &act_info, |
| DataType dt_input0, DataType dt_input1, DataType dt_input2, DataType dt_output, float alpha, float beta) |
| { |
| const unsigned int M = m_value; |
| const unsigned int N = n_value; |
| const unsigned int K = k_value; |
| |
| GEMMLHSMatrixInfo lhs_info; |
| lhs_info.m0 = m0_value; |
| lhs_info.k0 = k0_value; |
| |
| GEMMRHSMatrixInfo rhs_info; |
| rhs_info.n0 = n0_value; |
| rhs_info.k0 = k0_value; |
| rhs_info.h0 = h0_value; |
| rhs_info.interleave = i_value_rhs; |
| rhs_info.transpose = t_value_rhs; |
| rhs_info.export_to_cl_image = export_to_cl_image; |
| |
| GEMMKernelInfo kernel_info; |
| kernel_info.m = M; |
| kernel_info.n = N; |
| kernel_info.k = K; |
| kernel_info.depth_output_gemm3d = depth_output_gemm3d; |
| kernel_info.reinterpret_input_as_3d = false; |
| kernel_info.broadcast_bias = broadcast_bias; |
| kernel_info.activation_info = act_info; |
| |
| const TensorShape lhs_shape(K, M, b_value); |
| const TensorShape rhs_shape(N, K, b_value); |
| const TensorShape lhs_shape_reshaped = compute_lhs_reshaped_shape(TensorInfo(lhs_shape, 1, dt_input0), |
| lhs_info); |
| const TensorShape rhs_shape_reshaped = compute_rhs_reshaped_shape(TensorInfo(rhs_shape, 1, dt_input1), |
| rhs_info); |
| |
| const TensorShape dst_shape = compute_mm_shape(TensorInfo(lhs_shape_reshaped, 1, dt_input0), |
| TensorInfo(rhs_shape_reshaped, 1, dt_input1), |
| kernel_info); |
| |
| const TensorShape bias_shape(N, |
| M, // Correct calculation should be: broadcast_bias? 1 : M, it's wrong here on purpose just for validation test |
| broadcast_bias? 1 : b_value); |
| |
| // Create tensors |
| CLTensor lhs_reshaped = create_tensor<CLTensor>(lhs_shape_reshaped, dt_input0); |
| CLTensor rhs_reshaped = create_tensor<CLTensor>(rhs_shape_reshaped, dt_input1); |
| CLTensor bias = create_tensor<CLTensor>(bias_shape, dt_input2); |
| CLTensor dst = create_tensor<CLTensor>(dst_shape, dt_output); |
| |
| 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); |
| |
| // Validate zero-padding |
| CLGEMMMatrixMultiplyReshaped gemm; |
| |
| gemm.configure(&lhs_reshaped, &rhs_reshaped, &bias, &dst, alpha, beta, lhs_info, rhs_info, kernel_info); |
| |
| // Padding can be added along rhs and bias's X/Y dimension |
| return dst.info()->padding().empty() && lhs_reshaped.info()->padding().empty(); |
| } |
| } // namespace |
| |
| TEST_SUITE(CL) |
| TEST_SUITE(GEMMMatrixMultiplyReshaped) |
| |
| /** Validate zero padding tests |
| * |
| * A series of validation tests to check the zero padding requirement |
| * |
| * Checks performed in order: |
| * - No partial blocks in both x and y dimensions |
| * - Partial blocks in x dimension |
| * - Partial blocks in y dimension |
| * - Partial blocks in both x and y dimensions |
| * - Special case: partial_n0 == 9 (vstore1 should be invoked instead of vstore_partial_1) |
| */ |
| DATA_TEST_CASE(ValidateZeroPadding, framework::DatasetMode::ALL, zip(zip(zip( |
| framework::dataset::make("M", { 24, 64, 101, 1, 103 }), |
| framework::dataset::make("N", { 48, 29, 16, 121, 41 })), |
| framework::dataset::make("M0", { 4, 8, 4, 2, 4 })), |
| framework::dataset::make("N0", { 4, 4, 16, 2, 16 })), |
| m_value, n_value, m0_value, n0_value) |
| { |
| constexpr DataType dt = DataType::F32; |
| |
| bool status = validate_zero_padding(m_value, n_value, 23, 1, m0_value, n0_value, 4, 1, false, false, false, 0, 0, ActivationLayerInfo(), dt, dt, dt, dt, 1.0f, 1.0f); |
| ARM_COMPUTE_EXPECT(status, framework::LogLevel::ERRORS); |
| } |
| |
| // *INDENT-OFF* |
| // clang-format off |
| DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("Input0Info", { TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F32), // OK |
| TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16), // OK |
| TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::QASYMM8), // Data type not supported |
| TensorInfo(TensorShape(10U, 5U, 2U), 1, DataType::F32), // Incorrect dimension bias |
| TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F32), // Mismatching shapes |
| TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16), // OK, do not broadcast bias |
| TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16), // OK, wider accummulation |
| TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16), // OK, RHS 4,4,2 |
| |
| }), |
| framework::dataset::make("Input1Info",{ TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::QASYMM8), |
| TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(128U, 3U, 2U), 1, DataType::F16), |
| |
| })), |
| framework::dataset::make("Input2Info", { TensorInfo(TensorShape(21U), 1, DataType::F32), |
| TensorInfo(TensorShape(21U), 1, DataType::F16), |
| TensorInfo(TensorShape(21U), 1, DataType::QASYMM8), |
| TensorInfo(TensorShape(21U), 1, DataType::F32), |
| TensorInfo(TensorShape(21U), 1, DataType::F32), |
| TensorInfo(TensorShape(21U,17U), 1, DataType::F16), |
| TensorInfo(TensorShape(21U,17U), 1, DataType::F16), |
| TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16), |
| |
| })), |
| framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F32), |
| TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16), |
| TensorInfo(TensorShape(21U,17U,2U), 1, DataType::QASYMM8), |
| TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F32), |
| TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F32), |
| TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16), |
| TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16), |
| TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16), |
| |
| })), |
| framework::dataset::make("LHSMInfo",{ |
| GEMMLHSMatrixInfo(4,4,1,false,true), |
| GEMMLHSMatrixInfo(4,4,1,false,true), |
| GEMMLHSMatrixInfo(4,4,1,false,true), |
| GEMMLHSMatrixInfo(4,2,4,false,false), |
| GEMMLHSMatrixInfo(4,2,4,false,false), |
| GEMMLHSMatrixInfo(4,4,1,false,true), |
| GEMMLHSMatrixInfo(4,4,1,false,true), |
| GEMMLHSMatrixInfo(4,4,1,false,true), |
| |
| })), |
| framework::dataset::make("RHSMInfo",{ |
| GEMMRHSMatrixInfo(4,4,1,true,true,false), |
| GEMMRHSMatrixInfo(4,4,1,true,true,false), |
| GEMMRHSMatrixInfo(4,4,1,true,true,false), |
| GEMMRHSMatrixInfo(2,2,1,true,false,false), |
| GEMMRHSMatrixInfo(2,2,1,true,false,false), |
| GEMMRHSMatrixInfo(4,4,1,true,true,false), |
| GEMMRHSMatrixInfo(4,4,1,true,true,false), |
| GEMMRHSMatrixInfo(4,4,2,true,false,false), |
| |
| |
| })), |
| |
| |
| framework::dataset::make("GEMMInfo",{ |
| 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( 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(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 |
| validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); |
| } |
| |
| 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 |
| 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(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 the target platform supports the OpenCL cl_khr_image2d_from_buffer extension |
| if(image2d_from_buffer_supported(CLKernelLibrary::get().get_device())) |
| { |
| 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 the target platform supports the OpenCL cl_khr_image2d_from_buffer extension |
| if(image2d_from_buffer_supported(CLKernelLibrary::get().get_device())) |
| { |
| 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 the target platform supports the OpenCL cl_khr_image2d_from_buffer extension |
| if(image2d_from_buffer_supported(CLKernelLibrary::get().get_device())) |
| { |
| 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 the target platform supports the OpenCL cl_khr_image2d_from_buffer extension |
| if(image2d_from_buffer_supported(CLKernelLibrary::get().get_device())) |
| { |
| 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 the target platform supports the OpenCL cl_khr_image2d_from_buffer extension |
| if(image2d_from_buffer_supported(CLKernelLibrary::get().get_device())) |
| { |
| 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 the target platform supports the OpenCL cl_khr_image2d_from_buffer extension |
| if(image2d_from_buffer_supported(CLKernelLibrary::get().get_device())) |
| { |
| 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 the target platform supports the OpenCL cl_khr_image2d_from_buffer extension |
| if(image2d_from_buffer_supported(CLKernelLibrary::get().get_device())) |
| { |
| 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 the target platform supports the OpenCL cl_khr_image2d_from_buffer extension |
| if(image2d_from_buffer_supported(CLKernelLibrary::get().get_device())) |
| { |
| 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 |