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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 | 391 |
1 files changed, 391 insertions, 0 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 new file mode 100644 index 0000000000..4acb316a3c --- /dev/null +++ b/examples/gemm_tuner/cl_gemmlowp_reshaped_rhs_only_fused_output_stage_fixedpoint.cpp @@ -0,0 +1,391 @@ +/* + * Copyright (c) 2020-2021, 2023 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. + */ +#ifndef ARM_COMPUTE_CL /* Needed by Utils.cpp to handle OpenCL exceptions properly */ +#error "This example needs to be built with -DARM_COMPUTE_CL" +#endif /* ARM_COMPUTE_CL */ + +#include "arm_compute/core/Helpers.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/gpu/cl/kernels/ClGemmLowpMatrixMultiplyReshapedOnlyRhsKernel.h" +#include "src/gpu/cl/kernels/ClGemmLowpReductionKernel.h" +#include "tests/CL/Helper.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; + +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 */ +}; + +/** Formatted output of the GemmConfigs type + * + * @param[out] os Output stream. + * @param[in] configs Tunable configurations to output + * + * @return Modified output stream. + */ +::std::ostream &operator<<(::std::ostream &os, const GemmConfigs &configs) +{ + std::string false_str = std::string("false"); + std::string true_str = std::string("true"); + + os << "m0 : " << configs.m0 << std::endl; + os << "n0 : " << configs.n0 << std::endl; + os << "k0 : " << configs.k0 << std::endl; + os << "h0 : " << configs.h0 << std::endl; + os << "interleave_rhs : " << (configs.interleave_rhs ? true_str : false_str) << std::endl; + os << "transpose_rhs : " << (configs.transpose_rhs ? true_str : false_str) << std::endl; + return os; +} + +/** Command line options for gemm configs */ +class GemmConfigOptions +{ +public: + /** Constructor + * + * @param[in,out] parser A parser on which "parse()" hasn't been called yet. + */ + GemmConfigOptions(CommandLineParser &parser) + : m0(parser.add_positional_option<SimpleOption<size_t>>("m0", 4)), + n0(parser.add_positional_option<SimpleOption<size_t>>("n0", 4)), + k0(parser.add_positional_option<SimpleOption<size_t>>("k0", 4)), + h0(parser.add_positional_option<SimpleOption<size_t>>("h0", 1)), + interleave_rhs(parser.add_positional_option<SimpleOption<size_t>>("interleave_rhs", 1)), + transpose_rhs(parser.add_positional_option<SimpleOption<size_t>>("transpose_rhs", 1)) + { + m0->set_help("Number of rows processed by the matrix multiplication"); + n0->set_help("Number of columns processed by the matrix multiplication"); + k0->set_help("Number of partial accumulations performed by the matrix multiplication"); + h0->set_help("Number of horizontal blocks of size (k0xn0) stored on the same output row"); + interleave_rhs->set_help("Interleave rhs matrix (1) / Do not interleave rhs matrix (0)"); + transpose_rhs->set_help("Transpose rhs matrix (1) / Do not transpose rhs matrix (0)"); + } + /** Prevent instances of this class from being copied (As this class contains pointers) */ + GemmConfigOptions(const GemmConfigOptions &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + GemmConfigOptions &operator=(const GemmConfigOptions &) = delete; + /** Allow instances of this class to be moved */ + GemmConfigOptions(GemmConfigOptions &&) = default; + /** Allow instances of this class to be moved */ + GemmConfigOptions &operator=(GemmConfigOptions &&) = default; + /** 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> *interleave_rhs; /**< Interleave rhs matrix option (1 enable; 0 disable) */ + SimpleOption<size_t> *transpose_rhs; /**< Transpose rhs matrix option (1 enable; 0 disable) */ +}; + +/** Consumes the gemm configuration options and creates a structure containing all information + * + * @param[in] options Options to consume + * + * @return Structure containing the gemm configurations + */ +GemmConfigs consume_gemm_configs(const GemmConfigOptions &options) +{ + GemmConfigs configs; + configs.m0 = options.m0->value(); + configs.n0 = options.n0->value(); + configs.k0 = options.k0->value(); + configs.h0 = options.h0->value(); + configs.interleave_rhs = options.interleave_rhs->value() != 0; + configs.transpose_rhs = options.transpose_rhs->value() != 0; + return configs; +} + +} // namespace + +using ClGemmLowpMatrixMultiplyReshapedOnlyRhs = + test::CLSynthetizeOperator<ClGemmLowpMatrixMultiplyReshapedOnlyRhsKernel>; +using ClGemmLowpMatrixAReduction = test::CLSynthetizeOperator<ClGemmLowpMatrixAReductionKernel>; + +class CLGEMMLowpMatrixMultiplyReshapedOnlyRHSFusedOutputStageFixedpointExample : public Example +{ +public: + bool do_setup(int argc, char **argv) override + { + // Default parameters + CommonGemmExampleParams params; + GemmConfigs configs; + + // Parse command line options + CommandLineParser parser; + CommonGemmExampleOptions param_options(parser, DataType::QASYMM8); + GemmConfigOptions config_options(parser); + + parser.parse(argc, argv); + if (param_options.help->is_set() && param_options.help->value()) + { + parser.print_help(argv[0]); + return false; + } + if (!parser.validate()) + { + // Invalid arguments. Use default parameters and configs + std::cerr << "Invalid arguments." << std::endl; + parser.print_help(argv[0]); + std::cerr << "Falling back to default parameters and configs" << std::endl; + } + else + { + params = consume_common_gemm_example_parameters(param_options); + configs = consume_gemm_configs(config_options); + } + + std::cout << "Gemm parameters:" << std::endl; + std::cout << params << std::endl; + std::cout << "Gemm configurations:" << std::endl; + std::cout << configs << std::endl; + + tuner.set_tuner_mode(params.tuner_mode); + + CLScheduler::get().default_init(&tuner); + + lhs.allocator()->init(TensorInfo(TensorShape(params.K, params.M, params.B), 1, params.data_type)); + rhs.allocator()->init(TensorInfo(TensorShape(params.N, params.K, params.B), 1, params.data_type)); + bias.allocator()->init(TensorInfo(TensorShape(params.N), 1, DataType::S32)); + dst.allocator()->init(TensorInfo(TensorShape(params.N, params.M, params.B), 1, params.data_type)); + + // 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}; + lhs.info()->set_quantization_info(q_info); + rhs.info()->set_quantization_info(q_info); + bias.info()->set_quantization_info(q_info); + dst.info()->set_quantization_info(q_info); + + GEMMLHSMatrixInfo lhs_info; + lhs_info.m0 = configs.m0; + lhs_info.k0 = configs.k0; + + GEMMRHSMatrixInfo rhs_info; + rhs_info.n0 = configs.n0; + rhs_info.k0 = configs.k0; + rhs_info.h0 = configs.h0; + rhs_info.interleave = configs.interleave_rhs; + rhs_info.transpose = configs.transpose_rhs; + rhs_info.export_to_cl_image = false; // CL image not supported for quantized cases yet + + 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 (!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; + } + } + + // Configure output stage for quantized case + GEMMLowpOutputStageInfo gemmlowp_output_stage; + gemmlowp_output_stage.type = GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT; + gemmlowp_output_stage.output_data_type = dst.info()->data_type(); + gemmlowp_output_stage.gemmlowp_offset = 0; + { + 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; + + dst_multipliers.allocator()->init(TensorInfo(TensorShape(num_filters), 1, DataType::S32)); + dst_shifts.allocator()->init(TensorInfo(TensorShape(num_filters), 1, DataType::S32)); + + 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(), + gemmlowp_output_stage.gemmlowp_multipliers.data(), + gemmlowp_output_stage.gemmlowp_shifts.data()); + gemmlowp_output_stage.gemmlowp_multiplier = gemmlowp_output_stage.gemmlowp_multipliers[0]; + gemmlowp_output_stage.gemmlowp_shift = gemmlowp_output_stage.gemmlowp_shifts[0]; + + // No fused activation + PixelValue min_val{}; + PixelValue max_val{}; + std::tie(min_val, max_val) = get_min_max(dst.info()->data_type()); + + auto min_activation = min_val.get<int32_t>(); + auto max_activation = max_val.get<int32_t>(); + + // Set the GEMMLowp output stage info + gemmlowp_output_stage.gemmlowp_offset = dst.info()->quantization_info().uniform().offset; + gemmlowp_output_stage.gemmlowp_min_bound = min_activation; + gemmlowp_output_stage.gemmlowp_max_bound = max_activation; + } + + GEMMKernelInfo gemm_info; + gemm_info.m = params.M; + gemm_info.n = params.N; + gemm_info.k = params.K; + gemm_info.depth_output_gemm3d = 0; + gemm_info.reinterpret_input_as_3d = false; + gemm_info.broadcast_bias = true; + gemm_info.fp_mixed_precision = false; + gemm_info.has_pad_y = false; + gemm_info.mult_transpose1xW_width = configs.h0; + gemm_info.lhs_info = lhs_info; + gemm_info.rhs_info = rhs_info; + gemm_info.a_offset = lhs.info()->quantization_info().uniform().offset; + gemm_info.b_offset = rhs.info()->quantization_info().uniform().offset; + 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) + { + 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>(); + + 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.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) + { + const TensorInfo info_vector_sum_col(compute_reductionA_shape(*rhs.info()), 1, DataType::S32); + vector_sum_col.allocator()->init(info_vector_sum_col); + // There's no need for a Matrix B reduction kernel as this is assumed to be run only once in the prepare stage + } + + // 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())) + { + std::cerr << "Invalid arguments for ClGemmLowpMatrixMultiplyReshapedOnlyRhsKernel." << std::endl; + return false; + } + + // Configure function + 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(); + rhs.allocator()->allocate(); + rhs_reshaped.allocator()->allocate(); + bias.allocator()->allocate(); + dst.allocator()->allocate(); + vector_sum_col.allocator()->allocate(); + vector_sum_row.allocator()->allocate(); + dst_multipliers.allocator()->allocate(); + dst_shifts.allocator()->allocate(); + + return true; + } + void do_run() override + { + if (mtx_a_reduction != nullptr) + { + ITensorPack red_pack({{ACL_SRC, &lhs}, {ACL_DST, &dst}}); + mtx_a_reduction->run(red_pack); + } + + 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(); + } + + void do_teardown() override + { + } + +private: + CLTensor lhs{}; + CLTensor rhs{}; + CLTensor rhs_reshaped{}; + CLTensor bias{}; + CLTensor dst{}; + CLTensor vector_sum_col{}; + CLTensor vector_sum_row{}; + CLTensor dst_multipliers{}; + CLTensor dst_shifts{}; + CLTuner tuner{}; + ClGemmLowpMatrixMultiplyReshapedOnlyRhs gemm{}; + std::unique_ptr<ClGemmLowpMatrixAReduction> mtx_a_reduction{nullptr}; +}; + +/** Main test program for gemmlowp reshaped rhs only with fused output stage fixedpoint + * + * @param[in] argc Number of arguments + * @param[in] argv Arguments ( [optional] M, [optional] N, [optional] K, [optional] B, [optional] m0, [optional] n0, [optional] k0, [optional] h0, [optional] interleave_rhs, [optional] transpose_rhs ) + */ +int main(int argc, char **argv) +{ + return run_example<CLGEMMLowpMatrixMultiplyReshapedOnlyRHSFusedOutputStageFixedpointExample>(argc, argv); +} |