| /* |
| * Copyright (c) 2018-2021 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/experimental/PostOps.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/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedKernel.h" |
| #include "src/gpu/cl/kernels/ClGemmReshapeLhsMatrixKernel.h" |
| #include "src/gpu/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; |
| using namespace arm_compute::opencl::kernels; |
| |
| // Create function for ClGemmReshapeLhsMatrixKernel |
| using CLGEMMReshapeLHSMatrix = CLSynthetizeOperator<ClGemmReshapeLhsMatrixKernel>; |
| |
| // Create function for ClGemmReshapeRhsMatrixKernel |
| using CLGEMMReshapeRHSMatrix = CLSynthetizeOperator<ClGemmReshapeRhsMatrixKernel>; |
| |
| // Create function for ClGemmMatrixMultiplyReshapedKernel |
| using CLGEMMMatrixMultiplyReshaped = CLSynthetizeOperator<ClGemmMatrixMultiplyReshapedKernel>; |
| |
| // Fixture for CLGEMMMatrixMultiplyReshaped |
| template <typename T> |
| using CLGEMMMatrixMultiplyReshapedFixture = GEMMMatrixMultiplyReshapedValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>; |
| |
| // Fixture for CLGEMMMatrixMultiplyReshaped with post ops |
| template <typename T> |
| using CLGEMMMatrixMultiplyReshapedWithPostOpsFixture = |
| GEMMMatrixMultiplyReshapedWithPostOpsValidationFixture<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 CLGEMMMatrixMultiplyReshaped mixed precision with post ops |
| template <typename T> |
| using CLGEMMMatrixMultiplyReshapedMixedPrecisionWithPostOpsFixture = |
| GEMMMatrixMultiplyReshapedWithPostOpsValidationFixture<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 } ); |
| |
| /** Post Ops */ |
| using PostOpArgBroadcast = CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<float>::PostOpArgBroadcast; |
| experimental::PostOpList<PostOpArgBroadcast> post_ops_1() |
| { |
| experimental::PostOpList<PostOpArgBroadcast> post_ops{}; |
| post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::LINEAR, 0.5F, 0.0F}); |
| post_ops.push_back_op<experimental::PostOpEltwiseAdd<PostOpArgBroadcast>>( |
| std::make_tuple(true, true, false), // If broadcast in dims 0, 1 and 2 |
| 0, |
| ConvertPolicy::SATURATE); |
| post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F}); |
| return post_ops; |
| } |
| experimental::PostOpList<PostOpArgBroadcast> post_ops_2() |
| { |
| experimental::PostOpList<PostOpArgBroadcast> post_ops{}; |
| post_ops.push_back_op<experimental::PostOpEltwiseAdd<PostOpArgBroadcast>>( |
| std::make_tuple(false, true, true), // If broadcast in dims 0, 1 and 2 |
| 1, |
| ConvertPolicy::SATURATE); |
| post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F}); |
| return post_ops; |
| } |
| experimental::PostOpList<PostOpArgBroadcast> post_ops_3() |
| { |
| experimental::PostOpList<PostOpArgBroadcast> post_ops{}; |
| post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F}); |
| post_ops.push_back_op<experimental::PostOpEltwiseAdd<PostOpArgBroadcast>>( |
| std::make_tuple(false, false, true), // If broadcast in dims 0, 1 and 2 |
| 1, |
| ConvertPolicy::SATURATE); |
| return post_ops; |
| } |
| // To test that the output of the main op is the first parameter in prelu post op |
| experimental::PostOpList<PostOpArgBroadcast> post_ops_4() |
| { |
| experimental::PostOpList<PostOpArgBroadcast> post_ops{}; |
| post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::LINEAR, 0.5F, 0.0F}); |
| post_ops.push_back_op<experimental::PostOpEltwisePRelu<PostOpArgBroadcast>>( |
| std::make_tuple(false, false, true), // If true, broadcast in corresponding dim: 0, 1 or 2 |
| 0, |
| ConvertPolicy::SATURATE); |
| post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F}); |
| return post_ops; |
| } |
| // To test that the output of the main op is the second parameter in prelu post op i.e. it is the alpha_param |
| experimental::PostOpList<PostOpArgBroadcast> post_ops_5() |
| { |
| experimental::PostOpList<PostOpArgBroadcast> post_ops{}; |
| post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::LINEAR, 0.5F, 0.0F}); |
| post_ops.push_back_op<experimental::PostOpEltwisePRelu<PostOpArgBroadcast>>( |
| std::make_tuple(false, false, false), // If true, broadcast in corresponding dim: 0, 1 or 2 |
| 1, |
| ConvertPolicy::SATURATE); |
| post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F}); |
| return post_ops; |
| } |
| /** Different Post Op Lists */ |
| const auto post_op_lists = framework::dataset::make("post_op_lists", { |
| post_ops_1(), |
| post_ops_2(), |
| post_ops_3(), |
| post_ops_4(), |
| post_ops_5() |
| } ); |
| |
| bool is_post_op_list_valid(unsigned int m, unsigned int n, unsigned int k, unsigned int batch, DataType data_type, const experimental::PostOpList<ITensorInfo*>& post_ops) |
| { |
| const auto lhs_info = GEMMLHSMatrixInfo(4,4,1,false,true); |
| const auto rhs_info = GEMMRHSMatrixInfo(4,4,1,true,true,false); |
| |
| // Create TensorInfo for post op arguments |
| TensorInfo input0_info(TensorShape(k, m, batch), 1, data_type); |
| TensorInfo input1_info(TensorShape(n, k, batch), 1, data_type); |
| TensorInfo input2_info(TensorShape(n), 1, data_type); |
| TensorInfo output_info(TensorShape(n, m, batch), 1, data_type); |
| |
| const TensorInfo reshaped_input0_info = input0_info.clone()->set_tensor_shape(misc::shape_calculator::compute_lhs_reshaped_shape(input0_info, lhs_info)); |
| const TensorInfo reshaped_input1_info = input1_info.clone()->set_tensor_shape(misc::shape_calculator::compute_rhs_reshaped_shape(input1_info, rhs_info)); |
| |
| GEMMKernelInfo gemm_info(m, n, k, 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::IDENTITY, |
| 1 /**< Multiplication factor for the width of the 1xW transposed block */, |
| 1 /**< Multiplication factor for the height of the 4x4 interleaved block */, |
| lhs_info, |
| rhs_info, |
| 0 /**< Offset to be added to each element of the matrix A */, |
| 0 /**< Offset to be added to each element of the matrix B */, |
| post_ops); |
| return bool(ClGemmMatrixMultiplyReshapedKernel::validate(&reshaped_input0_info.clone()->set_is_resizable(true), |
| &reshaped_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)); |
| } |
| |
| } // namespace |
| |
| TEST_SUITE(CL) |
| TEST_SUITE(GEMMMatrixMultiplyReshaped) |
| |
| // *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(ValidateFusedPostOpsConfigs) |
| TEST_SUITE(Invalid) |
| TEST_CASE(UnsupportedPostOpSequence, framework::DatasetMode::ALL) |
| { |
| const auto data_type = DataType::F32; |
| const unsigned int m = 17; |
| const unsigned int n = 1; |
| const unsigned int k = 13; |
| const unsigned int batch = 2; |
| TensorShape post_op_arg0_shape(n, m, batch); |
| TensorInfo post_op_arg_info(post_op_arg0_shape, 1, data_type); |
| auto post_op_arg1_info = post_op_arg_info.clone(); |
| |
| // Unsupported sequence of post ops |
| experimental::PostOpList<ITensorInfo*> post_ops{}; |
| post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( |
| &post_op_arg_info, |
| 1, |
| ConvertPolicy::SATURATE); |
| post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( |
| post_op_arg1_info.get(), |
| 0, |
| ConvertPolicy::SATURATE); |
| |
| ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == false, framework::LogLevel::ERRORS); |
| } |
| TEST_CASE(OutputWidened, framework::DatasetMode::ALL) |
| { |
| // Invalid broadcast: post op tensors "widen" the output tensor |
| const auto data_type = DataType::F32; |
| const unsigned int m = 17; |
| const unsigned int n = 1; |
| const unsigned int k = 13; |
| const unsigned int batch = 2; |
| TensorShape post_op_arg_shape(n + 4, m, batch); // output's X dimension (n) is "widened", which is not allowed |
| TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); |
| experimental::PostOpList<ITensorInfo*> post_ops{}; |
| post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); |
| |
| ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == false, framework::LogLevel::ERRORS); |
| } |
| TEST_CASE(BroadcastInXDimOnly, framework::DatasetMode::ALL) |
| { |
| // Invalid broadcast: post op tensors broadcast in the first dimension (X) only |
| const auto data_type = DataType::F32; |
| const unsigned int m = 22; |
| const unsigned int n = 16; |
| const unsigned int k = 15; |
| const unsigned int batch = 3; |
| TensorShape post_op_arg_shape(1, m, batch); |
| TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); |
| experimental::PostOpList<ITensorInfo*> post_ops{}; |
| post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); |
| |
| ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == false, framework::LogLevel::ERRORS); |
| } |
| TEST_SUITE_END() // Invalid |
| TEST_SUITE(Valid) |
| TEST_CASE(EmptyPostOpList, framework::DatasetMode::ALL) |
| { |
| const auto data_type = DataType::F32; |
| const unsigned int m = 22; |
| const unsigned int n = 16; |
| const unsigned int k = 15; |
| const unsigned int batch = 3; |
| experimental::PostOpList<ITensorInfo*> post_ops{}; |
| |
| ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS); |
| } |
| TEST_CASE(BroadcastInYDimOnly, framework::DatasetMode::ALL) |
| { |
| const auto data_type = DataType::F32; |
| const unsigned int m = 22; |
| const unsigned int n = 16; |
| const unsigned int k = 15; |
| const unsigned int batch = 3; |
| TensorShape post_op_arg_shape(n, 1, batch); |
| TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); |
| experimental::PostOpList<ITensorInfo*> post_ops{}; |
| post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); |
| |
| ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS); |
| } |
| TEST_CASE(BroadcastInBothXandYDims, framework::DatasetMode::ALL) |
| { |
| const auto data_type = DataType::F32; |
| const unsigned int m = 22; |
| const unsigned int n = 16; |
| const unsigned int k = 15; |
| const unsigned int batch = 3; |
| TensorShape post_op_arg_shape(1, 1, batch); |
| TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); |
| experimental::PostOpList<ITensorInfo*> post_ops{}; |
| post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); |
| |
| ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS); |
| } |
| TEST_CASE(BroadcastInAllDims, framework::DatasetMode::ALL) |
| { |
| const auto data_type = DataType::F32; |
| const unsigned int m = 22; |
| const unsigned int n = 16; |
| const unsigned int k = 15; |
| const unsigned int batch = 3; |
| TensorShape post_op_arg_shape(1, 1, 1); |
| TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); |
| experimental::PostOpList<ITensorInfo*> post_ops{}; |
| post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); |
| |
| ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS); |
| } |
| TEST_SUITE_END() // Valid |
| TEST_SUITE_END() // ValidateFusedPostOps |
| TEST_SUITE(Float) |
| TEST_SUITE(FP32) |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values, |
| n_values), |
| k_values), |
| b_values), |
| m0_values_precommit), |
| n0_values_precommit), |
| k0_values_precommit), |
| v0_values_precommit), |
| h0_values_precommit), |
| i_values_lhs), |
| i_values_rhs), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F32)), |
| a_values_precommit), |
| beta_values_precommit), |
| broadcast_bias_values), |
| lhs_transpose_values), |
| act_values)) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::DISABLED, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values, |
| n_values), |
| k_values), |
| b_values), |
| m0_values_nightly), |
| n0_values_nightly), |
| k0_values_nightly), |
| v0_values_nightly), |
| h0_values_nightly), |
| i_values_lhs), |
| i_values_rhs), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F32)), |
| a_values_nightly), |
| beta_values_nightly), |
| broadcast_bias_values), |
| lhs_transpose_values), |
| act_values)) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_w_values, |
| m_h_values), |
| n_values), |
| k_values), |
| b_values), |
| m0_values_precommit), |
| n0_values_precommit), |
| k0_values_precommit), |
| v0_values_precommit), |
| h0_values_precommit), |
| i_values_lhs), |
| i_values_rhs), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F32)), |
| a_values_precommit), |
| beta_values_precommit), |
| lhs_transpose_values), |
| act_values)) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::DISABLED, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_w_values, |
| m_h_values), |
| n_values), |
| k_values), |
| b_values), |
| m0_values_nightly), |
| n0_values_nightly), |
| k0_values_nightly), |
| v0_values_nightly), |
| h0_values_nightly), |
| i_values_lhs), |
| i_values_rhs), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F32)), |
| a_values_nightly), |
| beta_values_nightly), |
| lhs_transpose_values), |
| act_values)) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| TEST_SUITE(FusedPostOps) |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<float>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values, |
| n_values), |
| k_values), |
| b_values), |
| m0_values_precommit), |
| n0_values_precommit), |
| k0_values_precommit), |
| v0_values_precommit), |
| h0_values_precommit), |
| framework::dataset::make("interleave_lhs", { false })), |
| framework::dataset::make("interleave_rhs", { false })), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F32)), |
| a_values_precommit), |
| beta_values_precommit), |
| framework::dataset::make("broadcast_bias", { true } )), |
| lhs_transpose_values), |
| act_values), |
| post_op_lists) |
| ) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| TEST_SUITE_END() // FusedPostOps |
| |
| TEST_SUITE(ExportToCLImage) |
| DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("Input0Info", { TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32), // OK or incorrect if cl_khr_image2d_from_buffer not supported |
| TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32), // OK or incorrect if cl_khr_image2d_from_buffer not supported |
| TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32), // OK or incorrect if cl_khr_image2d_from_buffer not supported |
| TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32), // Incorrect k0 |
| TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32), // Incorrect n0 |
| |
| }), |
| framework::dataset::make("Input1Info",{ TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(512U, 8U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(128U, 32U, 2U), 1, DataType::F32), |
| |
| })), |
| framework::dataset::make("Input2Info", { TensorInfo(TensorShape(64U), 1, DataType::F32), |
| TensorInfo(TensorShape(64U), 1, DataType::F32), |
| TensorInfo(TensorShape(64U), 1, DataType::F32), |
| TensorInfo(TensorShape(64U), 1, DataType::F32), |
| TensorInfo(TensorShape(64U), 1, DataType::F32), |
| |
| })), |
| framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32), |
| |
| })), |
| framework::dataset::make("LHSMInfo",{ |
| GEMMLHSMatrixInfo(4, 4, 1, false, true), |
| GEMMLHSMatrixInfo(4, 8, 1, false, true), |
| GEMMLHSMatrixInfo(4, 4, 1, false, true), |
| GEMMLHSMatrixInfo(4, 2, 1, false, false), |
| GEMMLHSMatrixInfo(4, 4, 1, false, false), |
| |
| })), |
| framework::dataset::make("RHSMInfo",{ |
| GEMMRHSMatrixInfo(4, 4, 1, true, true, true), |
| GEMMRHSMatrixInfo(4, 8, 1, true, true, true), |
| GEMMRHSMatrixInfo(8, 4, 1, true, true, true), |
| GEMMRHSMatrixInfo(4, 2, 1, true, false, true), |
| GEMMRHSMatrixInfo(2, 4, 1, true, false, true), |
| })), |
| framework::dataset::make("GEMMInfo",{GEMMKernelInfo( 64 /**<M Number of LHS rows*/, |
| 64 /**<N Number of RHS columns*/, |
| 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */, |
| false /**< reinterpret the input as 3D */, |
| true /**< Flag used to broadcast the bias addition */, |
| false /**< wider accumm */, |
| false /**< has pad y */, |
| ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, |
| 1 /**< Multiplication factor for the width of the 1xW transposed block */, |
| 1 /**< Multiplication factor for the height of the 4x4 interleaved block */, |
| GEMMLHSMatrixInfo(), |
| GEMMRHSMatrixInfo(), |
| 0 /**< Offset to be added to each element of the matrix A */, |
| 0 /**< Offset to be added to each element of the matrix B */), |
| GEMMKernelInfo( 64 /**<M Number of LHS rows*/, |
| 64 /**<N Number of RHS columns*/, |
| 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */, |
| false /**< reinterpret the input as 3D */, |
| true /**< Flag used to broadcast the bias addition */, |
| false /**< wider accumm */, |
| false /**< has pad y */, |
| ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, |
| 1 /**< Multiplication factor for the width of the 1xW transposed block */, |
| 1 /**< Multiplication factor for the height of the 4x4 interleaved block */, |
| GEMMLHSMatrixInfo(), |
| GEMMRHSMatrixInfo(), |
| 0 /**< Offset to be added to each element of the matrix A */, |
| 0 /**< Offset to be added to each element of the matrix B */), |
| GEMMKernelInfo( 64 /**<M Number of LHS rows*/, |
| 64 /**<N Number of RHS columns*/, |
| 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */, |
| false /**< reinterpret the input as 3D */, |
| true /**< Flag used to broadcast the bias addition */, |
| false /**< wider accumm */, |
| false /**< has pad y */, |
| ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, |
| 1 /**< Multiplication factor for the width of the 1xW transposed block */, |
| 1 /**< Multiplication factor for the height of the 4x4 interleaved block */, |
| GEMMLHSMatrixInfo(), |
| GEMMRHSMatrixInfo(), |
| 0 /**< Offset to be added to each element of the matrix A */, |
| 0 /**< Offset to be added to each element of the matrix B */), |
| |
| GEMMKernelInfo( 64 /**<M Number of LHS rows*/, |
| 64 /**<N Number of RHS columns*/, |
| 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */, |
| false /**< reinterpret the input as 3D */, |
| true /**< Flag used to broadcast the bias addition */, |
| false /**< wider accumm */, |
| false /**< has pad y */, |
| ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, |
| 1 /**< Multiplication factor for the width of the 1xW transposed block */, |
| 1 /**< Multiplication factor for the height of the 4x4 interleaved block */, |
| GEMMLHSMatrixInfo(), |
| GEMMRHSMatrixInfo(), |
| 0 /**< Offset to be added to each element of the matrix A */, |
| 0 /**< Offset to be added to each element of the matrix B */), |
| GEMMKernelInfo( 64 /**<M Number of LHS rows*/, |
| 64 /**<N Number of RHS columns*/, |
| 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */, |
| false /**< reinterpret the input as 3D */, |
| true /**< Flag used to broadcast the bias addition */, |
| false /**< wider accumm */, |
| false /**< has pad y */, |
| ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, |
| 1 /**< Multiplication factor for the width of the 1xW transposed block */, |
| 1 /**< Multiplication factor for the height of the 4x4 interleaved block */, |
| GEMMLHSMatrixInfo(), |
| GEMMRHSMatrixInfo(), |
| 0 /**< Offset to be added to each element of the matrix A */, |
| 0 /**< Offset to be added to each element of the matrix B */) |
| })), |
| framework::dataset::make("Expected", { true, |
| true, |
| true, |
| false, |
| 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(FusedPostOps) |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<float>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values, |
| n_values), |
| k_values), |
| b_values), |
| m0_values_precommit), |
| n0_values_precommit), |
| k0_values_precommit), |
| v0_values_precommit), |
| h0_values_precommit), |
| framework::dataset::make("interleave_lhs", { false })), |
| framework::dataset::make("interleave_rhs", { false })), |
| framework::dataset::make("export_to_cl_image_rhs", true)), |
| framework::dataset::make("DataType", DataType::F32)), |
| a_values_precommit), |
| beta_values_precommit), |
| framework::dataset::make("broadcast_bias", { true } )), |
| lhs_transpose_values), |
| act_values), |
| post_op_lists) |
| ) |
| { |
| // Validate output only if validate() is successful |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| TEST_SUITE_END() // FusedPostOps |
| |
| TEST_SUITE_END() // ExportToCLImage |
| TEST_SUITE_END() // FP32 |
| |
| TEST_SUITE(FP16) |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values, |
| n_values), |
| k_values), |
| b_values), |
| m0_values_precommit), |
| n0_values_precommit), |
| k0_values_precommit), |
| v0_values_precommit), |
| h0_values_precommit), |
| i_values_lhs), |
| i_values_rhs), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F16)), |
| a_values_precommit), |
| beta_values_precommit), |
| broadcast_bias_values), |
| lhs_transpose_values), |
| act_values)) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::DISABLED, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values, |
| n_values), |
| k_values), |
| b_values), |
| m0_values_nightly), |
| n0_values_nightly), |
| k0_values_nightly), |
| v0_values_nightly), |
| h0_values_nightly), |
| i_values_lhs), |
| i_values_rhs), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F16)), |
| a_values_nightly), |
| beta_values_nightly), |
| broadcast_bias_values), |
| lhs_transpose_values), |
| act_values)) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_w_values, |
| m_h_values), |
| n_values), |
| k_values), |
| b_values), |
| m0_values_precommit), |
| n0_values_precommit), |
| k0_values_precommit), |
| v0_values_precommit), |
| h0_values_precommit), |
| i_values_lhs), |
| i_values_rhs), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F16)), |
| a_values_precommit), |
| beta_values_precommit), |
| lhs_transpose_values), |
| act_values)) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::DISABLED, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_w_values, |
| m_h_values), |
| n_values), |
| k_values), |
| b_values), |
| m0_values_nightly), |
| n0_values_nightly), |
| k0_values_nightly), |
| v0_values_nightly), |
| h0_values_nightly), |
| i_values_lhs), |
| i_values_rhs), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F16)), |
| a_values_nightly), |
| beta_values_nightly), |
| lhs_transpose_values), |
| act_values)) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| TEST_SUITE(FusedPostOps) |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<half>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values, |
| n_values), |
| k_values), |
| b_values), |
| m0_values_precommit), |
| n0_values_precommit), |
| k0_values_precommit), |
| v0_values_precommit), |
| h0_values_precommit), |
| framework::dataset::make("interleave_lhs", { false })), |
| framework::dataset::make("interleave_rhs", { false })), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F16)), |
| a_values_precommit), |
| beta_values_precommit), |
| framework::dataset::make("broadcast_bias", { true } )), |
| lhs_transpose_values), |
| act_values), |
| post_op_lists) |
| ) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| TEST_SUITE_END() // FusedPostOps |
| |
| TEST_SUITE(ExportToCLImage) |
| DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("Input0Info", { TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // OK or incorrect if cl_khr_image2d_from_buffer not supported |
| TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // OK or incorrect if cl_khr_image2d_from_buffer not supported |
| TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // OK or incorrect if cl_khr_image2d_from_buffer not supported |
| TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // Incorrect k0 |
| TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), // Incorrect n0 |
| |
| }), |
| framework::dataset::make("Input1Info",{ TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(512U, 8U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(128U, 32U, 2U), 1, DataType::F16), |
| |
| })), |
| framework::dataset::make("Input2Info", { TensorInfo(TensorShape(64U), 1, DataType::F16), |
| TensorInfo(TensorShape(64U), 1, DataType::F16), |
| TensorInfo(TensorShape(64U), 1, DataType::F16), |
| TensorInfo(TensorShape(64U), 1, DataType::F16), |
| TensorInfo(TensorShape(64U), 1, DataType::F16), |
| |
| })), |
| framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16), |
| |
| })), |
| framework::dataset::make("LHSMInfo",{ |
| GEMMLHSMatrixInfo(4, 4, 1, false, true), |
| GEMMLHSMatrixInfo(4, 8, 1, false, true), |
| GEMMLHSMatrixInfo(4, 4, 1, false, true), |
| GEMMLHSMatrixInfo(4, 2, 1, false, false), |
| GEMMLHSMatrixInfo(4, 4, 1, false, false), |
| |
| })), |
| framework::dataset::make("RHSMInfo",{ |
| GEMMRHSMatrixInfo(4, 4, 1, true, true, true), |
| GEMMRHSMatrixInfo(4, 8, 1, true, true, true), |
| GEMMRHSMatrixInfo(8, 4, 1, true, true, true), |
| GEMMRHSMatrixInfo(4, 2, 1, true, false, true), |
| GEMMRHSMatrixInfo(2, 4, 1, true, false, true), |
| })), |
| framework::dataset::make("GEMMInfo",{GEMMKernelInfo( 64 /**<M Number of LHS rows*/, |
| 64 /**<N Number of RHS columns*/, |
| 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */, |
| false /**< reinterpret the input as 3D */, |
| true /**< Flag used to broadcast the bias addition */, |
| false /**< wider accumm */, |
| false /**< has pad y */, |
| ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, |
| 1 /**< Multiplication factor for the width of the 1xW transposed block */, |
| 1 /**< Multiplication factor for the height of the 4x4 interleaved block */, |
| GEMMLHSMatrixInfo(), |
| GEMMRHSMatrixInfo(), |
| 0 /**< Offset to be added to each element of the matrix A */, |
| 0 /**< Offset to be added to each element of the matrix B */), |
| GEMMKernelInfo( 64 /**<M Number of LHS rows*/, |
| 64 /**<N Number of RHS columns*/, |
| 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */, |
| false /**< reinterpret the input as 3D */, |
| true /**< Flag used to broadcast the bias addition */, |
| false /**< wider accumm */, |
| false /**< has pad y */, |
| ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, |
| 1 /**< Multiplication factor for the width of the 1xW transposed block */, |
| 1 /**< Multiplication factor for the height of the 4x4 interleaved block */, |
| GEMMLHSMatrixInfo(), |
| GEMMRHSMatrixInfo(), |
| 0 /**< Offset to be added to each element of the matrix A */, |
| 0 /**< Offset to be added to each element of the matrix B */), |
| GEMMKernelInfo( 64 /**<M Number of LHS rows*/, |
| 64 /**<N Number of RHS columns*/, |
| 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */, |
| false /**< reinterpret the input as 3D */, |
| true /**< Flag used to broadcast the bias addition */, |
| false /**< wider accumm */, |
| false /**< has pad y */, |
| ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, |
| 1 /**< Multiplication factor for the width of the 1xW transposed block */, |
| 1 /**< Multiplication factor for the height of the 4x4 interleaved block */, |
| GEMMLHSMatrixInfo(), |
| GEMMRHSMatrixInfo(), |
| 0 /**< Offset to be added to each element of the matrix A */, |
| 0 /**< Offset to be added to each element of the matrix B */), |
| |
| GEMMKernelInfo( 64 /**<M Number of LHS rows*/, |
| 64 /**<N Number of RHS columns*/, |
| 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */, |
| false /**< reinterpret the input as 3D */, |
| true /**< Flag used to broadcast the bias addition */, |
| false /**< wider accumm */, |
| false /**< has pad y */, |
| ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, |
| 1 /**< Multiplication factor for the width of the 1xW transposed block */, |
| 1 /**< Multiplication factor for the height of the 4x4 interleaved block */, |
| GEMMLHSMatrixInfo(), |
| GEMMRHSMatrixInfo(), |
| 0 /**< Offset to be added to each element of the matrix A */, |
| 0 /**< Offset to be added to each element of the matrix B */), |
| GEMMKernelInfo( 64 /**<M Number of LHS rows*/, |
| 64 /**<N Number of RHS columns*/, |
| 64 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */, |
| false /**< reinterpret the input as 3D */, |
| true /**< Flag used to broadcast the bias addition */, |
| false /**< wider accumm */, |
| false /**< has pad y */, |
| ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, |
| 1 /**< Multiplication factor for the width of the 1xW transposed block */, |
| 1 /**< Multiplication factor for the height of the 4x4 interleaved block */, |
| GEMMLHSMatrixInfo(), |
| GEMMRHSMatrixInfo(), |
| 0 /**< Offset to be added to each element of the matrix A */, |
| 0 /**< Offset to be added to each element of the matrix B */) |
| })), |
| framework::dataset::make("Expected", { true, |
| true, |
| true, |
| false, |
| 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(FusedPostOps) |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<half>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values, |
| n_values), |
| k_values), |
| b_values), |
| m0_values_precommit), |
| n0_values_precommit), |
| k0_values_precommit), |
| v0_values_precommit), |
| h0_values_precommit), |
| framework::dataset::make("interleave_lhs", { false })), |
| framework::dataset::make("interleave_rhs", { false })), |
| framework::dataset::make("export_to_cl_image_rhs", true)), |
| framework::dataset::make("DataType", DataType::F16)), |
| a_values_precommit), |
| beta_values_precommit), |
| framework::dataset::make("broadcast_bias", { true } )), |
| lhs_transpose_values), |
| act_values), |
| post_op_lists) |
| ) |
| { |
| // Validate output only if validate() is successful |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| TEST_SUITE_END() // FusedPostOps |
| |
| TEST_SUITE_END() // ExportToCLImage |
| TEST_SUITE_END() // FP16 |
| |
| TEST_SUITE(MixedPrecision) |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedMixedPrecisionFixture<half>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values, |
| n_values), |
| k_values), |
| b_values), |
| m0_values_precommit), |
| n0_values_precommit), |
| k0_values_precommit), |
| v0_values_precommit), |
| h0_values_precommit), |
| i_values_lhs), |
| i_values_rhs), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F16)), |
| a_values_precommit), |
| beta_values_precommit), |
| broadcast_bias_values), |
| lhs_transpose_values), |
| act_values)) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedMixedPrecisionFixture<half>, framework::DatasetMode::DISABLED, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values, |
| n_values), |
| k_values), |
| b_values), |
| m0_values_nightly), |
| n0_values_nightly), |
| k0_values_nightly), |
| v0_values_nightly), |
| h0_values_nightly), |
| i_values_lhs), |
| i_values_rhs), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F16)), |
| a_values_nightly), |
| beta_values_nightly), |
| broadcast_bias_values), |
| lhs_transpose_values), |
| act_values)) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DMixedPrecisionFixture<half>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_w_values, |
| m_h_values), |
| n_values), |
| k_values), |
| b_values), |
| m0_values_precommit), |
| n0_values_precommit), |
| k0_values_precommit), |
| v0_values_precommit), |
| h0_values_precommit), |
| i_values_lhs), |
| i_values_rhs), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F16)), |
| a_values_precommit), |
| beta_values_precommit), |
| lhs_transpose_values), |
| act_values)) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DMixedPrecisionFixture<half>, framework::DatasetMode::DISABLED, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_w_values, |
| m_h_values), |
| n_values), |
| k_values), |
| b_values), |
| m0_values_nightly), |
| n0_values_nightly), |
| k0_values_nightly), |
| v0_values_nightly), |
| h0_values_nightly), |
| i_values_lhs), |
| i_values_rhs), |
| framework::dataset::make("export_to_cl_image_rhs", false)), |
| framework::dataset::make("DataType", DataType::F16)), |
| a_values_nightly), |
| beta_values_nightly), |
| lhs_transpose_values), |
| act_values)) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| TEST_SUITE(FusedPostOps) |
| |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedMixedPrecisionWithPostOpsFixture<half>, framework::DatasetMode::ALL, |
| combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( |
| m_values, |
| n_values), |
| k_values), |
| b_values), |
| m0_values_precommit), |
| n0_values_precommit), |
| k0_values_precommit), |
| v0_values_precommit), |
| h0_values_precommit), |
| framework::dataset::make("interleave_lhs", { false })), |
| framework::dataset::make("interleave_rhs", { false })), |
| framework::dataset::make("export_to_cl_image_rhs", { true, false })), |
| framework::dataset::make("DataType", DataType::F16)), |
| a_values_precommit), |
| beta_values_precommit), |
| framework::dataset::make("broadcast_bias", { true } )), |
| lhs_transpose_values), |
| act_values), |
| post_op_lists) |
| ) |
| { |
| // Validate output |
| if(validate_result) |
| { |
| validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision); |
| } |
| else |
| { |
| ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); |
| framework::ARM_COMPUTE_PRINT_INFO(); |
| } |
| } |
| |
| TEST_SUITE_END() // FusedPostOps |
| |
| TEST_SUITE_END() // MixedPrecision |
| TEST_SUITE_END() // Float |
| TEST_SUITE_END() // GEMMMatrixMultiplyReshaped |
| TEST_SUITE_END() // CL |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |