| /* |
| * Copyright (c) 2016-2021, 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. |
| */ |
| #include "src/gpu/cl/kernels/ClActivationKernel.h" |
| |
| #include "arm_compute/core/CL/CLHelpers.h" |
| #include "arm_compute/core/CL/ICLTensor.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/utils/ActivationFunctionUtils.h" |
| #include "arm_compute/core/utils/StringUtils.h" |
| #include "arm_compute/core/utils/helpers/AdjustVecSize.h" |
| #include "arm_compute/function_info/ActivationLayerInfo.h" |
| #include "src/core/CL/CLValidate.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| #include "support/Cast.h" |
| |
| #include "support/StringSupport.h" |
| |
| #include <set> |
| |
| namespace arm_compute |
| { |
| namespace opencl |
| { |
| namespace kernels |
| { |
| namespace |
| { |
| Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst, const ActivationLayerInfo &act_info) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM16, DataType::F16, DataType::F32); |
| |
| static std::set<ActivationLayerInfo::ActivationFunction> quantized_supported_activations = |
| { |
| ActivationLayerInfo::ActivationFunction::RELU, |
| ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, |
| ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, |
| ActivationLayerInfo::ActivationFunction::LOGISTIC, |
| ActivationLayerInfo::ActivationFunction::TANH, |
| ActivationLayerInfo::ActivationFunction::HARD_SWISH, |
| ActivationLayerInfo::ActivationFunction::LEAKY_RELU, |
| }; |
| const DataType data_type = src->data_type(); |
| const QuantizationInfo &oq_info = (dst != nullptr) ? dst->quantization_info() : src->quantization_info(); |
| const ActivationLayerInfo::ActivationFunction f_act = act_info.activation(); |
| |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_data_type_quantized(data_type) && (quantized_supported_activations.count(f_act) == 0), |
| "For Quantized data type only hard swish, leaky relu, tanh, logistic, relu and lower/upper bounded relu are supported"); |
| |
| ARM_COMPUTE_RETURN_ERROR_ON(data_type == DataType::QASYMM8 && (f_act == ActivationLayerInfo::ActivationFunction::TANH) && (oq_info != QuantizationInfo(1.f / 128.f, 128))); |
| ARM_COMPUTE_RETURN_ERROR_ON(data_type == DataType::QASYMM8 && (f_act == ActivationLayerInfo::ActivationFunction::LOGISTIC) && (oq_info != QuantizationInfo(1.f / 256.f, 0))); |
| |
| ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_symmetric(data_type) && (f_act == ActivationLayerInfo::ActivationFunction::TANH) && (oq_info != QuantizationInfo(1.f / 32768.f, 0))); |
| ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_symmetric(data_type) && (f_act == ActivationLayerInfo::ActivationFunction::LOGISTIC) && (oq_info != QuantizationInfo(1.f / 32768.f, 0))); |
| |
| ARM_COMPUTE_RETURN_ERROR_ON(data_type == DataType::QASYMM8_SIGNED && (f_act == ActivationLayerInfo::ActivationFunction::TANH) && (oq_info != QuantizationInfo(1.f / 128.f, 0))); |
| ARM_COMPUTE_RETURN_ERROR_ON(data_type == DataType::QASYMM8_SIGNED && (f_act == ActivationLayerInfo::ActivationFunction::LOGISTIC) && (oq_info != QuantizationInfo(1.f / 256.f, -128))); |
| |
| // Checks performed when destination is configured |
| if((dst != nullptr) && (dst->total_size() != 0)) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src, dst); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst); |
| } |
| |
| return Status{}; |
| } |
| } // namespace |
| |
| ClActivationKernel::ClActivationKernel() |
| { |
| _type = CLKernelType::ELEMENTWISE; |
| } |
| |
| void ClActivationKernel::configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *dst, ActivationLayerInfo act_info) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(src); |
| |
| auto padding_info = get_padding_info({ src, dst }); |
| |
| _run_in_place = (dst == nullptr) || (dst == src); |
| |
| if(dst != nullptr) |
| { |
| // Destination auto inizialitation if not yet initialized |
| auto_init_if_empty(*dst, *src->clone()); |
| } |
| |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, (dst != nullptr) ? dst : nullptr, act_info)); |
| |
| const unsigned int num_elems_processed_per_iteration = adjust_vec_size(16 / src->element_size(), src->dimension(0)); |
| |
| const DataType dt = src->data_type(); |
| float a_const = act_info.a(); |
| float b_const = act_info.b(); |
| |
| const ActivationLayerInfo::ActivationFunction f_act = act_info.activation(); |
| const bool is_quantized = is_data_type_quantized(dt); |
| const bool perform_activation_in_float = |
| (f_act == ActivationLayerInfo::ActivationFunction::LOGISTIC) |
| || (f_act == ActivationLayerInfo::ActivationFunction::TANH) |
| || (f_act == ActivationLayerInfo::ActivationFunction::HARD_SWISH) |
| || (f_act == ActivationLayerInfo::ActivationFunction::LEAKY_RELU); |
| |
| // Set build options |
| CLBuildOptions build_opts; |
| build_opts.add_option_if(perform_activation_in_float, "-DFLOAT_DOMAIN"); |
| build_opts.add_option_if(_run_in_place, "-DIN_PLACE"); |
| build_opts.add_option("-DACT=" + lower_string(string_from_activation_func(f_act))); |
| build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(dt)); |
| build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)); |
| build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(src->dimension(0) % num_elems_processed_per_iteration)); |
| |
| std::string kernel_name = std::string("activation_layer"); |
| |
| // Set quantization info build options |
| if(is_quantized) |
| { |
| const UniformQuantizationInfo iq_info = src->quantization_info().uniform(); |
| |
| if(!perform_activation_in_float) |
| { |
| int a_const_int = 0; |
| int b_const_int = 0; |
| |
| // Create quantized version of constants a, b if needed |
| switch(dt) |
| { |
| case DataType::QASYMM8: |
| { |
| a_const_int = quantize_qasymm8(a_const, iq_info); |
| b_const_int = quantize_qasymm8(b_const, iq_info); |
| } |
| break; |
| case DataType::QASYMM8_SIGNED: |
| { |
| a_const_int = quantize_qasymm8_signed(a_const, iq_info); |
| b_const_int = quantize_qasymm8_signed(b_const, iq_info); |
| } |
| break; |
| case DataType::QSYMM16: |
| { |
| a_const_int = quantize_qsymm16(a_const, iq_info); |
| b_const_int = quantize_qsymm16(b_const, iq_info); |
| } |
| break; |
| default: |
| break; |
| } |
| build_opts.add_option(("-DA_VAL=" + support::cpp11::to_string(a_const_int))); |
| build_opts.add_option(("-DB_VAL=" + support::cpp11::to_string(b_const_int))); |
| } |
| else |
| { |
| build_opts.add_option(("-DA_VAL=" + float_to_string_with_full_precision(a_const))); |
| build_opts.add_option(("-DB_VAL=" + float_to_string_with_full_precision(b_const))); |
| } |
| |
| // Quantized value of 0 corresponds to the offset o1 |
| build_opts.add_option(("-DCONST_0=" + (is_data_type_quantized_asymmetric(dt) ? support::cpp11::to_string(iq_info.offset) : "0"))); |
| build_opts.add_option(("-DS1_VAL=" + float_to_string_with_full_precision(iq_info.scale))); |
| build_opts.add_option_if(is_data_type_quantized_asymmetric(dt), "-DO1_VAL=" + support::cpp11::to_string(iq_info.offset)); |
| |
| // Set correct kernel name |
| kernel_name += perform_activation_in_float ? std::string("_quant_f32") : std::string("_quant"); |
| |
| // Set scale and offset of the source and destination if they have different quantization info |
| if(dst != nullptr) |
| { |
| const UniformQuantizationInfo oq_info = dst->quantization_info().uniform(); |
| |
| if(iq_info != oq_info) |
| { |
| build_opts.add_option(("-DS2_VAL=" + float_to_string_with_full_precision(oq_info.scale))); |
| build_opts.add_option_if(is_data_type_quantized_asymmetric(dt), "-DO2_VAL=" + support::cpp11::to_string(oq_info.offset)); |
| } |
| } |
| } |
| else |
| { |
| // Set A, B constants in build options for float types |
| build_opts.add_option(("-DA_VAL=" + float_to_string_with_full_precision(a_const))); |
| build_opts.add_option(("-DB_VAL=" + float_to_string_with_full_precision(b_const))); |
| } |
| |
| // Create kernel |
| _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*src, Steps(num_elems_processed_per_iteration)); |
| ICLKernel::configure_internal(win); |
| |
| // Set config_id for enabling LWS tuning |
| _config_id = "activation_layer_"; |
| _config_id += lower_string(string_from_data_type(dt)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(src->dimension(0)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(src->dimension(1)); |
| |
| ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); |
| } |
| |
| Status ClActivationKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const ActivationLayerInfo &act_info) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, dst, act_info)); |
| return Status{}; |
| } |
| |
| void ClActivationKernel::run_op(ITensorPack &tensors, const Window &window, ::cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); |
| |
| const auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC)); |
| auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST)); |
| ARM_COMPUTE_ERROR_ON(_run_in_place && src != dst); |
| |
| Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); |
| Window slice = collapsed.first_slice_window_3D(); |
| |
| do |
| { |
| unsigned int idx = 0; |
| add_3D_tensor_argument(idx, src, slice); |
| if(!_run_in_place) |
| { |
| add_3D_tensor_argument(idx, dst, slice); |
| } |
| enqueue(queue, *this, slice, lws_hint()); |
| } |
| while(collapsed.slide_window_slice_3D(slice)); |
| } |
| } // namespace kernels |
| } // namespace opencl |
| } // namespace arm_compute |