diff options
Diffstat (limited to 'examples/gemm_tuner/cl_gemmlowp_reshaped_rhs_only_fused_output_stage_fixedpoint.cpp')
| -rw-r--r-- | examples/gemm_tuner/cl_gemmlowp_reshaped_rhs_only_fused_output_stage_fixedpoint.cpp | 110 |
1 files changed, 63 insertions, 47 deletions
diff --git a/examples/gemm_tuner/cl_gemmlowp_reshaped_rhs_only_fused_output_stage_fixedpoint.cpp b/examples/gemm_tuner/cl_gemmlowp_reshaped_rhs_only_fused_output_stage_fixedpoint.cpp index d8f8f1498a..4acb316a3c 100644 --- a/examples/gemm_tuner/cl_gemmlowp_reshaped_rhs_only_fused_output_stage_fixedpoint.cpp +++ b/examples/gemm_tuner/cl_gemmlowp_reshaped_rhs_only_fused_output_stage_fixedpoint.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2020-2021 Arm Limited. + * Copyright (c) 2020-2021, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -25,28 +25,29 @@ #error "This example needs to be built with -DARM_COMPUTE_CL" #endif /* ARM_COMPUTE_CL */ -#include "CommonGemmExampleOptions.h" -#include "GemmTunerHelpers.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/KernelDescriptors.h" -#include "arm_compute/core/KernelDescriptors.h" #include "arm_compute/core/Types.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/core/utils/quantization/AsymmHelpers.h" #include "arm_compute/runtime/CL/CLScheduler.h" #include "arm_compute/runtime/CL/CLTuner.h" -#include "src/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel.h" -#include "src/core/CL/kernels/CLGEMMLowpReductionKernel.h" + +#include "src/gpu/cl/kernels/ClGemmLowpMatrixMultiplyReshapedOnlyRhsKernel.h" +#include "src/gpu/cl/kernels/ClGemmLowpReductionKernel.h" #include "tests/CL/Helper.h" -#include "utils/Utils.h" #include "utils/command_line/CommandLineOptions.h" #include "utils/command_line/CommandLineParser.h" +#include "utils/Utils.h" +#include "CommonGemmExampleOptions.h" +#include "GemmTunerHelpers.h" #include <cstdlib> #include <memory> using namespace arm_compute; using namespace utils; +using namespace arm_compute::opencl::kernels; using namespace arm_compute::misc::shape_calculator; using namespace gemm_tuner; @@ -55,12 +56,12 @@ namespace /** Structure holding all tunable gemm configs specific to this example/strategy */ struct GemmConfigs { - size_t m0{ 4 }; /**< Number of rows processed by the matrix multiplication */ - size_t n0{ 4 }; /**< Number of columns processed by the matrix multiplication */ - size_t k0{ 4 }; /**< Number of partial accumulations performed by the matrix multiplication */ - size_t h0{ 1 }; /**< Number of horizontal blocks of size (k0xn0) stored on the same output row */ - bool interleave_rhs{ true }; /**< Interleave rhs matrix */ - bool transpose_rhs{ true }; /**< Transpose rhs matrix */ + size_t m0{4}; /**< Number of rows processed by the matrix multiplication */ + size_t n0{4}; /**< Number of columns processed by the matrix multiplication */ + size_t k0{4}; /**< Number of partial accumulations performed by the matrix multiplication */ + size_t h0{1}; /**< Number of horizontal blocks of size (k0xn0) stored on the same output row */ + bool interleave_rhs{true}; /**< Interleave rhs matrix */ + bool transpose_rhs{true}; /**< Transpose rhs matrix */ }; /** Formatted output of the GemmConfigs type @@ -118,10 +119,10 @@ public: /** Default destructor */ ~GemmConfigOptions() = default; - SimpleOption<size_t> *m0; /**< Number of rows processed by the matrix multiplication option */ - SimpleOption<size_t> *n0; /**< Number of columns processed by the matrix multiplication option */ - SimpleOption<size_t> *k0; /**< Number of partial accumulations performed by the matrix multiplication option */ - SimpleOption<size_t> *h0; /**< Number of horizontal blocks of size (k0xn0) stored on the same output row option */ + SimpleOption<size_t> *m0; /**< Number of rows processed by the matrix multiplication option */ + SimpleOption<size_t> *n0; /**< Number of columns processed by the matrix multiplication option */ + SimpleOption<size_t> *k0; /**< Number of partial accumulations performed by the matrix multiplication option */ + SimpleOption<size_t> *h0; /**< Number of horizontal blocks of size (k0xn0) stored on the same output row option */ SimpleOption<size_t> *interleave_rhs; /**< Interleave rhs matrix option (1 enable; 0 disable) */ SimpleOption<size_t> *transpose_rhs; /**< Transpose rhs matrix option (1 enable; 0 disable) */ }; @@ -146,8 +147,9 @@ GemmConfigs consume_gemm_configs(const GemmConfigOptions &options) } // namespace -using CLGEMMLowpMatrixMultiplyReshapedOnlyRHS = test::CLSynthetizeFunction<CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel>; -using CLGEMMLowpMatrixAReduction = test::CLSynthetizeFunction<CLGEMMLowpMatrixAReductionKernel>; +using ClGemmLowpMatrixMultiplyReshapedOnlyRhs = + test::CLSynthetizeOperator<ClGemmLowpMatrixMultiplyReshapedOnlyRhsKernel>; +using ClGemmLowpMatrixAReduction = test::CLSynthetizeOperator<ClGemmLowpMatrixAReductionKernel>; class CLGEMMLowpMatrixMultiplyReshapedOnlyRHSFusedOutputStageFixedpointExample : public Example { @@ -164,12 +166,12 @@ public: GemmConfigOptions config_options(parser); parser.parse(argc, argv); - if(param_options.help->is_set() && param_options.help->value()) + if (param_options.help->is_set() && param_options.help->value()) { parser.print_help(argv[0]); return false; } - if(!parser.validate()) + if (!parser.validate()) { // Invalid arguments. Use default parameters and configs std::cerr << "Invalid arguments." << std::endl; @@ -198,10 +200,7 @@ public: // Set arbitrary quantization information (non-zero offset to ensure offset contribution stage is included) // Could be extended in the future to include a user-controlled option for offset == 0 - const QuantizationInfo q_info - { - 0.012, 3 - }; + const QuantizationInfo q_info{0.012, 3}; lhs.info()->set_quantization_info(q_info); rhs.info()->set_quantization_info(q_info); bias.info()->set_quantization_info(q_info); @@ -219,11 +218,17 @@ public: rhs_info.transpose = configs.transpose_rhs; rhs_info.export_to_cl_image = false; // CL image not supported for quantized cases yet - rhs_reshaped.allocator()->init(TensorInfo(compute_rhs_reshaped_shape(*rhs.info(), rhs_info), 1, params.data_type)); + if (rhs_info.h0 == 0) + { + rhs_info.h0 = std::max(static_cast<unsigned int>(params.N) / rhs_info.n0, 1U); + } + + rhs_reshaped.allocator()->init( + TensorInfo(compute_rhs_reshaped_shape(*rhs.info(), rhs_info), 1, params.data_type)); rhs_reshaped.info()->set_quantization_info(q_info); - if(rhs_info.export_to_cl_image) + if (rhs_info.export_to_cl_image) { - if(!examples::gemm_tuner_helpers::update_padding_for_cl_image(rhs_reshaped.info())) + if (!examples::gemm_tuner_helpers::update_padding_for_cl_image(rhs_reshaped.info())) { std::cerr << "cl_image is not supported on the device, disable export_to_cl_image" << std::endl; return false; @@ -236,7 +241,6 @@ public: gemmlowp_output_stage.output_data_type = dst.info()->data_type(); gemmlowp_output_stage.gemmlowp_offset = 0; { - const int idx_kernels = get_data_layout_dimension_index(lhs.info()->data_layout(), DataLayoutDimension::BATCHES); gemmlowp_output_stage.is_quantized_per_channel = false; // Num_filters is 1 unless quantized type is of per_channel type. Could be extended in the future to support per-channel quantization. const unsigned int num_filters = 1; @@ -246,10 +250,7 @@ public: gemmlowp_output_stage.gemmlowp_multipliers.resize(num_filters); gemmlowp_output_stage.gemmlowp_shifts.resize(num_filters); - quantization::compute_quantized_multipliers_and_shifts(lhs.info(), - rhs.info(), - dst.info(), - idx_kernels, + quantization::compute_quantized_multipliers_and_shifts(lhs.info(), rhs.info(), dst.info(), gemmlowp_output_stage.gemmlowp_multipliers.data(), gemmlowp_output_stage.gemmlowp_shifts.data()); gemmlowp_output_stage.gemmlowp_multiplier = gemmlowp_output_stage.gemmlowp_multipliers[0]; @@ -286,23 +287,23 @@ public: gemm_info.output_stage = gemmlowp_output_stage; // Initialize Matrix A reduction kernel only if _b_offset is not equal to 0 - if(gemm_info.b_offset != 0) + if (gemm_info.b_offset != 0) { const TensorInfo info_vector_sum_row(compute_reductionB_shape(*lhs.info()), 1, DataType::S32); vector_sum_row.allocator()->init(info_vector_sum_row); - mtx_a_reduction = std::make_unique<CLGEMMLowpMatrixAReduction>(); + mtx_a_reduction = std::make_unique<ClGemmLowpMatrixAReduction>(); - if(!mtx_a_reduction->validate(lhs.info(), vector_sum_row.info(), GEMMLowpReductionKernelInfo{})) + if (!mtx_a_reduction->validate(lhs.info(), vector_sum_row.info(), GEMMLowpReductionKernelInfo{})) { std::cerr << "Invalid arguments for CLGEMMLowpMatrixAReductionKernel." << std::endl; return false; } - mtx_a_reduction->configure(&lhs, &vector_sum_row, GEMMLowpReductionKernelInfo{}); + mtx_a_reduction->configure(lhs.info(), vector_sum_row.info(), GEMMLowpReductionKernelInfo{}); } // Initialize matrix B reduction kernel only if _a_offset is not equal to 0 - if(gemm_info.a_offset != 0) + if (gemm_info.a_offset != 0) { const TensorInfo info_vector_sum_col(compute_reductionA_shape(*rhs.info()), 1, DataType::S32); vector_sum_col.allocator()->init(info_vector_sum_col); @@ -310,15 +311,20 @@ public: } // Validate argments - if(!gemm.validate(lhs.info(), rhs_reshaped.info(), dst.info(), gemm_info, gemm_info.a_offset == 0 ? nullptr : vector_sum_col.info(), - gemm_info.b_offset == 0 ? nullptr : vector_sum_row.info(), bias.info(), dst_multipliers.info(), dst_shifts.info())) + if (!gemm.validate(lhs.info(), rhs_reshaped.info(), dst.info(), gemm_info, + gemm_info.a_offset == 0 ? nullptr : vector_sum_col.info(), + gemm_info.b_offset == 0 ? nullptr : vector_sum_row.info(), bias.info(), + dst_multipliers.info(), dst_shifts.info())) { - std::cerr << "Invalid arguments for CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel." << std::endl; + std::cerr << "Invalid arguments for ClGemmLowpMatrixMultiplyReshapedOnlyRhsKernel." << std::endl; return false; } // Configure function - gemm.configure(&lhs, &rhs_reshaped, &dst, gemm_info, gemm_info.a_offset == 0 ? nullptr : &vector_sum_col, gemm_info.b_offset == 0 ? nullptr : &vector_sum_row, &bias, &dst_multipliers, &dst_shifts); + gemm.configure(lhs.info(), rhs_reshaped.info(), dst.info(), gemm_info, + gemm_info.a_offset == 0 ? nullptr : vector_sum_col.info(), + gemm_info.b_offset == 0 ? nullptr : vector_sum_row.info(), bias.info(), dst_multipliers.info(), + dst_shifts.info()); // Allocate tensors lhs.allocator()->allocate(); @@ -335,11 +341,21 @@ public: } void do_run() override { - if(mtx_a_reduction != nullptr) + if (mtx_a_reduction != nullptr) { - mtx_a_reduction->run(); + ITensorPack red_pack({{ACL_SRC, &lhs}, {ACL_DST, &dst}}); + mtx_a_reduction->run(red_pack); } - gemm.run(); + + ITensorPack gemm_pack({{ACL_SRC_0, &lhs}, + {ACL_SRC_1, &rhs}, + {ACL_BIAS, &bias}, + {ACL_VEC_COL_SUM, &vector_sum_col}, + {ACL_VEC_ROW_SUM, &vector_sum_row}, + {ACL_SHIFTS, &dst_shifts}, + {ACL_MULTIPLIERS, &dst_multipliers}, + {ACL_DST, &dst}}); + gemm.run(gemm_pack); // Make sure all the OpenCL jobs are done executing: CLScheduler::get().sync(); @@ -360,8 +376,8 @@ private: CLTensor dst_multipliers{}; CLTensor dst_shifts{}; CLTuner tuner{}; - CLGEMMLowpMatrixMultiplyReshapedOnlyRHS gemm{}; - std::unique_ptr<CLGEMMLowpMatrixAReduction> mtx_a_reduction{ nullptr }; + ClGemmLowpMatrixMultiplyReshapedOnlyRhs gemm{}; + std::unique_ptr<ClGemmLowpMatrixAReduction> mtx_a_reduction{nullptr}; }; /** Main test program for gemmlowp reshaped rhs only with fused output stage fixedpoint |