| /* |
| * Copyright (c) 2017-2022 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/Types.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/utils/quantization/AsymmHelpers.h" |
| #include "arm_compute/runtime/CL/CLScheduler.h" |
| #include "arm_compute/runtime/CL/functions/CLGEMM.h" |
| #include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h" |
| #include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h" |
| #include "src/core/CL/kernels/CLFillBorderKernel.h" |
| #include "src/gpu/cl/kernels/ClCastKernel.h" |
| #include "src/gpu/cl/kernels/ClGemmLowpMatrixMultiplyNativeKernel.h" |
| #include "src/gpu/cl/kernels/ClGemmLowpMatrixMultiplyReshapedOnlyRhsKernel.h" |
| #include "src/gpu/cl/kernels/ClGemmLowpOffsetContributionKernel.h" |
| #include "src/gpu/cl/kernels/ClGemmLowpOffsetContributionOutputStageKernel.h" |
| #include "src/gpu/cl/kernels/ClGemmLowpReductionKernel.h" |
| #include "src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedKernel.h" |
| #include "src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedOnlyRhsKernel.h" |
| #include "src/gpu/cl/kernels/ClGemmReshapeLhsMatrixKernel.h" |
| #include "src/gpu/cl/kernels/ClGemmReshapeRhsMatrixKernel.h" |
| #include "src/gpu/cl/kernels/ClIm2ColKernel.h" |
| #include "src/gpu/cl/kernels/ClWeightsReshapeKernel.h" |
| #include "tests/AssetsLibrary.h" |
| #include "tests/CL/CLAccessor.h" |
| #include "tests/Globals.h" |
| #include "tests/IAccessor.h" |
| #include "tests/SimpleTensor.h" |
| #include "tests/validation/Validation.h" |
| #include "tests/validation/reference/GEMM.h" |
| #include "tests/validation/reference/GEMMLowp.h" |
| |
| #include "utils/TypePrinter.h" |
| #include "utils/Utils.h" |
| #include "utils/command_line/CommandLineOptions.h" |
| #include "utils/command_line/CommandLineParser.h" |
| |
| #include "ValidateExample.h" |
| |
| #include <cstdlib> |
| |
| using namespace arm_compute; |
| using namespace utils; |
| using namespace arm_compute::test; |
| using namespace arm_compute::test::validation; |
| |
| constexpr float abs_tolerance_f32(0.0001f); /**< F32 Absolute tolerance value for comparing reference's output against implementation's output for |
| * floating point data types in case using relative tolerance fails because of small values */ |
| RelativeTolerance<float> tolerance_f32(0.001f); /**< F32 Tolerance value for comparing reference's output against implementation's output for floating point data types */ |
| RelativeTolerance<half_float::half> tolerance_f16(half(0.2)); /**< F16 Tolerance value for comparing reference's output against implementation's output for floating point data types */ |
| constexpr float tolerance_num_f16 = 0.02f; /**< F16 Tolerance number */ |
| |
| namespace |
| { |
| class GEMMCommandLineOptions final |
| { |
| public: |
| explicit GEMMCommandLineOptions(CommandLineParser &parser) noexcept |
| : help(parser.add_option<ToggleOption>("help")), |
| add_bias(parser.add_option<ToggleOption>("add_bias")), |
| M(parser.add_option<SimpleOption<int>>("m", 7)), |
| N(parser.add_option<SimpleOption<int>>("n", 3)), |
| K(parser.add_option<SimpleOption<int>>("k", 5)), |
| B(parser.add_option<SimpleOption<int>>("b", 1)), |
| alpha(parser.add_option<SimpleOption<float>>("alpha", 1.f)), |
| beta(parser.add_option<SimpleOption<float>>("beta", 0.f)), |
| offset_src0(parser.add_option<SimpleOption<int>>("offset_i0", 10)), |
| offset_src1(parser.add_option<SimpleOption<int>>("offset_i1", 10)), |
| offset_dst(parser.add_option<SimpleOption<int>>("offset_o", 10)), |
| scale_src0(parser.add_option<SimpleOption<float>>("scale_i0", 1.f / 255)), |
| scale_src1(parser.add_option<SimpleOption<float>>("scale_i1", 1.f / 255)), |
| scale_dst(parser.add_option<SimpleOption<float>>("scale_o", 1.f / 255)), |
| data_type() |
| { |
| // Setup data type |
| const std::set<arm_compute::DataType> supported_data_types |
| { |
| DataType::F16, |
| DataType::F32, |
| DataType::QASYMM8, |
| }; |
| data_type = parser.add_option<EnumOption<DataType>>("type", supported_data_types, DataType::F32); |
| |
| // Setup help strings |
| help->set_help("Show this help message"); |
| add_bias->set_help("Add bias to the GEMM. Used when running in QASYMM8"); |
| M->set_help("M value"); |
| N->set_help("N value"); |
| K->set_help("K value"); |
| B->set_help("B value - number of batches"); |
| alpha->set_help("Alpha value"); |
| beta->set_help("Beta value"); |
| offset_src0->set_help("Offset of first input. Used when running in QASYMM8"); |
| offset_src1->set_help("Offset of second input. Used when running in QASYMM8"); |
| offset_dst->set_help("Offset of output. Used when running in QASYMM8"); |
| scale_src0->set_help("Scale of first input. Used when running in QASYMM8"); |
| scale_src1->set_help("Scale of second input. Used when running in QASYMM8"); |
| scale_dst->set_help("Scale of output. Used when running in QASYMM8"); |
| data_type->set_help("Data type to use"); |
| } |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| GEMMCommandLineOptions(const GEMMCommandLineOptions &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| GEMMCommandLineOptions &operator=(const GEMMCommandLineOptions &) = delete; |
| /** Allow instances of this class to be moved */ |
| GEMMCommandLineOptions(GEMMCommandLineOptions &&) noexcept(true) = default; |
| /** Allow instances of this class to be moved */ |
| GEMMCommandLineOptions &operator=(GEMMCommandLineOptions &&) noexcept(true) = default; |
| /** Default destructor */ |
| ~GEMMCommandLineOptions() = default; |
| |
| public: |
| ToggleOption *help; |
| ToggleOption *add_bias; |
| SimpleOption<int> *M; |
| SimpleOption<int> *N; |
| SimpleOption<int> *K; |
| SimpleOption<int> *B; |
| SimpleOption<float> *alpha; |
| SimpleOption<float> *beta; |
| SimpleOption<int> *offset_src0; |
| SimpleOption<int> *offset_src1; |
| SimpleOption<int> *offset_dst; |
| SimpleOption<float> *scale_src0; |
| SimpleOption<float> *scale_src1; |
| SimpleOption<float> *scale_dst; |
| EnumOption<arm_compute::DataType> *data_type; |
| }; |
| } // namespace |
| |
| class CLGEMMValidateExample : public ValidateExample |
| { |
| public: |
| bool do_setup(int argc, char **argv) override |
| { |
| CLScheduler::get().default_init(); |
| |
| // Parse options |
| CommandLineParser parser; |
| GEMMCommandLineOptions gemm_options(parser); |
| parser.parse(argc, argv); |
| |
| // Print help |
| const bool print_help = gemm_options.help->is_set() ? gemm_options.help->value() : false; |
| if(print_help) |
| { |
| parser.print_help(argv[0]); |
| return false; |
| } |
| |
| // Consume parameters |
| consume_params(gemm_options); |
| print_parameters_internal(); |
| |
| const bool is_quantized = is_data_type_quantized(data_type); |
| |
| // Calculate re-quantization parameters |
| if(is_quantized) |
| { |
| float multiplier = scale_src0 * scale_src1 / scale_dst; |
| quantization::calculate_quantized_multiplier(multiplier, &dst_multiplier, &dst_shift); |
| } |
| |
| // Initialize GEMM inputs/outputs |
| src0.allocator()->init(TensorInfo(TensorShape(K, M, B), 1, data_type)); |
| src1.allocator()->init(TensorInfo(TensorShape(N, K, B), 1, data_type)); |
| src2.allocator()->init(TensorInfo(TensorShape(N, M, B), 1, data_type)); |
| init_sgemm_output(dst, src0, src1, data_type); |
| |
| // Configure function |
| if(is_quantized) |
| { |
| src0.info()->set_quantization_info(QuantizationInfo(scale_src0, offset_src0)); |
| src1.info()->set_quantization_info(QuantizationInfo(scale_src1, offset_src1)); |
| dst.info()->set_quantization_info(QuantizationInfo(scale_dst, offset_dst)); |
| biases.allocator()->init(TensorInfo(TensorShape(N), 1, DataType::S32)); |
| init_sgemm_output(tmp_dst, src0, src1, DataType::S32); |
| |
| // Configure GEMMlowp matrix multiply function |
| mm_gemmlowp.configure(&src0, &src1, nullptr, &tmp_dst); |
| |
| // Configure GEMMlowp output stage |
| GEMMLowpOutputStageInfo gemm_info{}; |
| gemm_info.gemmlowp_multiplier = dst_multiplier; |
| gemm_info.gemmlowp_shift = dst_shift; |
| gemm_info.gemmlowp_offset = offset_dst; |
| mm_gemmlowp_output_stage.configure(&tmp_dst, add_bias ? &biases : nullptr, &dst, gemm_info); |
| tmp_dst.allocator()->allocate(); |
| biases.allocator()->allocate(); |
| fill(CLAccessor(biases), 3); |
| } |
| else |
| { |
| // Configure matrix multiply function |
| mm_gemm.configure(&src0, &src1, &src2, &dst, alpha, beta); |
| } |
| |
| // Allocate all the tensors |
| src0.allocator()->allocate(); |
| src1.allocator()->allocate(); |
| dst.allocator()->allocate(); |
| src2.allocator()->allocate(); |
| |
| fill(CLAccessor(src0), 0); |
| fill(CLAccessor(src1), 1); |
| fill(CLAccessor(src2), 2); |
| |
| return true; |
| } |
| |
| void print_parameters_internal() |
| { |
| std::cout << "Datatype : " << string_from_data_type(data_type) << "\n"; |
| std::cout << "M : " << support::cpp11::to_string(M) << "\n"; |
| std::cout << "N : " << support::cpp11::to_string(N) << "\n"; |
| std::cout << "K : " << support::cpp11::to_string(K) << "\n"; |
| std::cout << "B : " << support::cpp11::to_string(B) << "\n"; |
| if(data_type == DataType::QASYMM8) |
| { |
| std::cout << "Scale_Src0 : " << support::cpp11::to_string(scale_src0) << "\n"; |
| std::cout << "Offset_Src0 : " << support::cpp11::to_string(offset_src0) << "\n"; |
| std::cout << "Scale_Scr1 : " << support::cpp11::to_string(scale_src1) << "\n"; |
| std::cout << "Offset_Src1 : " << support::cpp11::to_string(offset_src1) << "\n"; |
| std::cout << "Scale_Dst : " << support::cpp11::to_string(scale_dst) << "\n"; |
| std::cout << "Offset_Dst : " << support::cpp11::to_string(offset_dst) << "\n"; |
| std::cout << "Bias : " << support::cpp11::to_string(add_bias) << "\n"; |
| } |
| else |
| { |
| std::cout << "Alpha : " << support::cpp11::to_string(alpha) << "\n"; |
| std::cout << "Beta : " << support::cpp11::to_string(beta) << "\n"; |
| } |
| } |
| |
| void do_validate() override |
| { |
| switch(data_type) |
| { |
| case DataType::F16: |
| { |
| SimpleTensor<half> ref_src0 = { TensorShape(K, M, B), data_type, 1 }; |
| SimpleTensor<half> ref_src1 = { TensorShape(N, K, B), data_type, 1 }; |
| SimpleTensor<half> ref_src2 = { TensorShape(N, M, B), data_type, 1 }; |
| |
| fill(ref_src0, 0); |
| fill(ref_src1, 1); |
| fill(ref_src2, 2); |
| |
| SimpleTensor<half> ref_dst = reference::gemm<half>(ref_src0, ref_src1, ref_src2, alpha, beta); |
| validate(CLAccessor(dst), ref_dst, tolerance_f16, tolerance_num_f16); |
| break; |
| } |
| case DataType::F32: |
| { |
| SimpleTensor<float> ref_src0 = { TensorShape(K, M, B), data_type, 1 }; |
| SimpleTensor<float> ref_src1 = { TensorShape(N, K, B), data_type, 1 }; |
| SimpleTensor<float> ref_src2 = { TensorShape(N, M, B), data_type, 1 }; |
| |
| fill(ref_src0, 0); |
| fill(ref_src1, 1); |
| fill(ref_src2, 2); |
| |
| SimpleTensor<float> ref_dst = reference::gemm<float>(ref_src0, ref_src1, ref_src2, alpha, beta); |
| validate(CLAccessor(dst), ref_dst, tolerance_f32, 0.f, abs_tolerance_f32); |
| break; |
| } |
| case DataType::QASYMM8: |
| { |
| SimpleTensor<uint8_t> ref_src0{ TensorShape(K, M, B), data_type, 1 }; |
| SimpleTensor<uint8_t> ref_src1{ TensorShape(N, K, B), data_type, 1 }; |
| SimpleTensor<uint8_t> ref_dst; |
| |
| // Fill reference |
| fill(ref_src0, 0); |
| fill(ref_src1, 1); |
| |
| SimpleTensor<int32_t> ref_tmp_dst = reference::gemmlowp_matrix_multiply_core<int32_t, uint8_t>(ref_src0, ref_src1, TensorShape(N, M, B), offset_src0, offset_src1); |
| |
| const std::vector<int32_t> dst_multiplier_vec = { dst_multiplier }; |
| const std::vector<int32_t> dst_shift_vec = { dst_shift }; |
| |
| if(add_bias) |
| { |
| SimpleTensor<int32_t> biases{ TensorShape(N), DataType::S32, 1 }; |
| // Fill bias |
| fill(biases, 3); |
| ref_dst = reference::gemmlowp_quantize_down_scale_by_fixedpoint<int32_t, uint8_t>(ref_tmp_dst, biases, dst_multiplier_vec, dst_shift_vec, offset_dst); |
| } |
| else |
| { |
| ref_dst = reference::gemmlowp_quantize_down_scale_by_fixedpoint<int32_t, uint8_t>(ref_tmp_dst, dst_multiplier_vec, dst_shift_vec, offset_dst); |
| } |
| validate(CLAccessor(dst), ref_dst); |
| break; |
| } |
| default: |
| break; |
| } |
| } |
| void do_run() override |
| { |
| // Execute the function |
| if(data_type == DataType::QASYMM8) |
| { |
| // Run gemmlowp |
| mm_gemmlowp.run(); |
| // Run output stage |
| mm_gemmlowp_output_stage.run(); |
| } |
| else |
| { |
| // Run gemm |
| mm_gemm.run(); |
| } |
| |
| // Make sure all the OpenCL jobs are done executing: |
| CLScheduler::get().sync(); |
| } |
| |
| private: |
| template <typename U> |
| void fill(U &&tensor, int i) |
| { |
| switch(tensor.data_type()) |
| { |
| case DataType::F16: |
| { |
| arm_compute::utils::uniform_real_distribution_16bit<half> distribution{ -1.0f, 1.0f }; |
| library->fill(tensor, distribution, i); |
| break; |
| } |
| case DataType::F32: |
| { |
| std::uniform_real_distribution<float> distribution(-1.0f, 1.0f); |
| library->fill(tensor, distribution, i); |
| break; |
| } |
| case DataType::S32: |
| case DataType::QASYMM8: |
| { |
| std::uniform_int_distribution<> distribution(-6000, 6000); |
| library->fill(tensor, distribution, i); |
| break; |
| } |
| default: |
| library->fill_tensor_uniform(tensor, i); |
| } |
| } |
| |
| void consume_params(const GEMMCommandLineOptions &opts) |
| { |
| ARM_COMPUTE_ERROR_ON(opts.M->value() <= 0); |
| ARM_COMPUTE_ERROR_ON(opts.N->value() <= 0); |
| ARM_COMPUTE_ERROR_ON(opts.K->value() <= 0); |
| ARM_COMPUTE_ERROR_ON(opts.B->value() <= 0); |
| M = opts.M->value(); |
| N = opts.N->value(); |
| K = opts.K->value(); |
| B = opts.B->value(); |
| alpha = opts.alpha->value(); |
| beta = opts.beta->value(); |
| offset_src0 = opts.offset_src0->value(); |
| offset_src1 = opts.offset_src1->value(); |
| offset_dst = opts.offset_dst->value(); |
| scale_src0 = opts.scale_src0->value(); |
| scale_src1 = opts.scale_src1->value(); |
| scale_dst = opts.scale_dst->value(); |
| add_bias = opts.add_bias->is_set() ? opts.add_bias->value() : true; |
| data_type = opts.data_type->value(); |
| } |
| |
| CLTensor src0{}, src1{}, src2{}, dst{}; |
| CLTensor tmp_dst{}, biases{}; |
| |
| CLGEMM mm_gemm{}; |
| CLGEMMLowpMatrixMultiplyCore mm_gemmlowp{}; |
| CLGEMMLowpOutputStage mm_gemmlowp_output_stage{}; |
| |
| size_t M{ 7 }, N{ 3 }, K{ 5 }, B{ 1 }; |
| DataType data_type{ DataType::F32 }; |
| float alpha{ 1.0 }, beta{ 0.0 }; |
| int offset_src0{ 10 }, offset_src1{ 10 }, offset_dst{ 10 }; |
| float scale_src0{ 1.0f / 255 }, scale_src1{ 1.0f / 255 }, scale_dst{ 1.0f / 255 }; |
| int32_t dst_multiplier{ 0 }, dst_shift{ 0 }; |
| bool add_bias{ true }; |
| }; |
| |
| /** Main program for gemm test |
| * |
| * @param[in] argc Number of arguments |
| * @param[in] argv Arguments |
| * |
| */ |
| int main(int argc, char **argv) |
| { |
| return utils::run_example<CLGEMMValidateExample>(argc, argv); |
| } |