| /* |
| * Copyright (c) 2017-2018 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/quantization/AsymmHelpers.h" |
| #include "arm_compute/runtime/CL/CLFunctions.h" |
| #include "arm_compute/runtime/CL/CLScheduler.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 "ValidateExample.h" |
| |
| #include "utils/Utils.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 */ |
| |
| class CLGEMMValidateExample : public ValidateExample |
| { |
| public: |
| void do_setup(int argc, char **argv) override |
| { |
| CLScheduler::get().default_init(); |
| if(argc == 2) |
| { |
| size_t dt = strtol(argv[1], nullptr, 10); |
| switch(dt) |
| { |
| case 1: |
| { |
| data_type = DataType::F16; |
| std::cout << "Usage: " << argv[0] << "1 M N K [alpha = 1.0f] [beta = 0.0f]\n"; |
| std::cout << "Using default values: Datatype=FP16 M=7, N=3, K=5, alpha=1.0f and beta=0.0f\n"; |
| break; |
| } |
| case 2: |
| { |
| data_type = DataType::QASYMM8; |
| std::cout << "Usage: " << argv[0] << "2 M N K [scale_src0 = 0.1f] [offset_scr0 = f] [scale_scr1 = 0.1f] [offset_scr1 = 10] [scale_dst = 0.1f] [offset_dst = 10] [bias = 1]\n"; |
| std::cout << |
| "Using default values: Datatype=QASYMM8 M=7, N=3, K=5, scale_src0 =(1.0f/255), offset_src0 = 10, scale_src1 =(1.0f/255), offset_src1 = 10, scale_dst =(1.0f/255), offset_dst = 10, bias=1\n\n"; |
| break; |
| } |
| case 0: |
| default: |
| { |
| data_type = DataType::F32; |
| std::cout << "Usage: " << argv[0] << "0 M N K [alpha = 1.0f] [beta = 0.0f]\n"; |
| std::cout << "Using default values: Datatype=FP32 M=7, N=3, K=5, alpha=1.0f and beta=0.0f\n"; |
| } |
| } |
| } |
| else if(argc < 5) |
| { |
| // Print help |
| std::cout << "Usage with datatype = FP32 : " << argv[0] << "0 M N K [alpha = 1.0f] [beta = 0.0f]\n"; |
| std::cout << " datatype = FP16 : " << argv[0] << "1 M N K [alpha = 1.0f] [beta = 0.0f]\n"; |
| std::cout << " datatype = QASYMM8 : " << argv[0] << "2 M N K [scale_src0 = 0.1f] [offset_scr0 = f] [scale_scr1 = 0.1f] [offset_scr1 = 10] [scale_dst = 0.1f] [offset_dst = 10] [bias = 1]\n"; |
| std::cout << "Too few or no arguments provided.\n"; |
| std::cout << "Using default values: Datatype=FP32 M=7, N=3, K=5, alpha=1.0f and beta=0.0f\n"; |
| } |
| else |
| { |
| size_t dt = strtol(argv[1], nullptr, 10); |
| switch(dt) |
| { |
| case 1: |
| { |
| data_type = DataType::F16; |
| break; |
| } |
| case 2: |
| { |
| data_type = DataType::QASYMM8; |
| break; |
| } |
| case 0: |
| default: |
| data_type = DataType::F32; |
| } |
| M = strtol(argv[2], nullptr, 10); |
| N = strtol(argv[3], nullptr, 10); |
| K = strtol(argv[4], nullptr, 10); |
| } |
| |
| switch(data_type) |
| { |
| case DataType::F16: |
| case DataType::F32: |
| { |
| if(argc > 5) |
| { |
| alpha = strtof(argv[5], nullptr); |
| if(argc > 6) |
| { |
| beta = strtof(argv[6], nullptr); |
| } |
| } |
| break; |
| } |
| case DataType::QASYMM8: |
| { |
| if(argc > 5) |
| { |
| scale_src0 = strtof(argv[5], nullptr); |
| if(argc > 6) |
| { |
| offset_src0 = strtol(argv[6], nullptr, 10); |
| if(argc > 7) |
| { |
| scale_src1 = strtof(argv[7], nullptr); |
| if(argc > 8) |
| { |
| offset_src1 = strtol(argv[8], nullptr, 10); |
| if(argc > 9) |
| { |
| scale_dst = strtof(argv[9], nullptr); |
| if(argc > 10) |
| { |
| offset_dst = strtol(argv[10], nullptr, 10); |
| if(argc > 11) |
| { |
| add_bias = (strtol(argv[11], nullptr, 10) == 1); |
| } |
| } |
| } |
| } |
| } |
| } |
| } |
| float multiplier = scale_src0 * scale_src1 / scale_dst; |
| quantization::calculate_quantized_multiplier_less_than_one(multiplier, &dst_multiplier, &dst_shift); |
| break; |
| } |
| default: |
| break; |
| } |
| |
| src0.allocator()->init(TensorInfo(TensorShape(K, M), 1, data_type)); |
| src1.allocator()->init(TensorInfo(TensorShape(N, K), 1, data_type)); |
| src2.allocator()->init(TensorInfo(TensorShape(N, M), 1, data_type)); |
| init_sgemm_output(dst, src0, src1, data_type); |
| |
| // Configure function |
| if(data_type == DataType::QASYMM8) |
| { |
| 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, &tmp_dst); |
| |
| // Configure GEMMlowp output stage |
| mm_gemmlowp_output_stage.configure(&tmp_dst, add_bias ? &biases : nullptr, &dst, dst_multiplier, dst_shift, offset_dst); |
| 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); |
| } |
| |
| void print_parameters(framework::Printer &printer) override |
| { |
| printer.print_entry("Datatype", string_from_data_type(data_type)); |
| printer.print_entry("M", support::cpp11::to_string(M)); |
| printer.print_entry("N", support::cpp11::to_string(N)); |
| printer.print_entry("K", support::cpp11::to_string(K)); |
| if(data_type == DataType::QASYMM8) |
| { |
| printer.print_entry("Scale_Src0", support::cpp11::to_string(scale_src0)); |
| printer.print_entry("Offset_Src0", support::cpp11::to_string(offset_src0)); |
| printer.print_entry("Scale_Scr1", support::cpp11::to_string(scale_src1)); |
| printer.print_entry("Offset_Src1", support::cpp11::to_string(offset_src1)); |
| printer.print_entry("Scale_Dst", support::cpp11::to_string(scale_dst)); |
| printer.print_entry("Offset_Dst", support::cpp11::to_string(offset_dst)); |
| printer.print_entry("Bias", support::cpp11::to_string(add_bias)); |
| } |
| else |
| { |
| printer.print_entry("Alpha", support::cpp11::to_string(alpha)); |
| printer.print_entry("Beta", support::cpp11::to_string(beta)); |
| } |
| } |
| |
| void do_validate() override |
| { |
| switch(data_type) |
| { |
| case DataType::F16: |
| { |
| SimpleTensor<half> ref_src0 = { TensorShape(K, M), data_type, 1 }; |
| SimpleTensor<half> ref_src1 = { TensorShape(N, K), data_type, 1 }; |
| SimpleTensor<half> ref_src2 = { TensorShape(N, M), 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), data_type, 1 }; |
| SimpleTensor<float> ref_src1 = { TensorShape(N, K), data_type, 1 }; |
| SimpleTensor<float> ref_src2 = { TensorShape(N, M), 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), data_type, 1 }; |
| SimpleTensor<uint8_t> ref_src1{ TensorShape(N, K), 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, offset_src0, offset_src1); |
| |
| if(add_bias) |
| { |
| SimpleTensor<int32_t> biases{ TensorShape(N), DataType::S32, 1 }; |
| // Fill bias |
| fill(biases, 3); |
| ref_dst = reference::gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint<int32_t>(ref_tmp_dst, biases, dst_multiplier, dst_shift, offset_dst); |
| } |
| else |
| { |
| ref_dst = reference::gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint<int32_t>(ref_tmp_dst, dst_multiplier, dst_shift, 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: |
| case DataType::F32: |
| { |
| std::uniform_real_distribution<> 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); |
| } |
| } |
| |
| CLTensor src0{}, src1{}, src2{}, dst{}; |
| CLTensor tmp_dst{}, biases{}; |
| |
| CLGEMM mm_gemm{}; |
| CLGEMMLowpMatrixMultiplyCore mm_gemmlowp{}; |
| CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint mm_gemmlowp_output_stage{}; |
| |
| size_t M{ 7 }, N{ 3 }, K{ 5 }; |
| 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 ( [optional] datatype, [optional] M, [optional] N, [optional] K, [optional] scale_src0, [optional] offset_src0, [optional] scale_src1, [optional] offset_src1, [optional] scale_dst, [optional] offset_dst, [optional] bias, [optional] alpha, [optional] beta ) |
| * |
| */ |
| int main(int argc, char **argv) |
| { |
| return utils::run_example<CLGEMMValidateExample>(argc, argv); |
| } |