diff options
Diffstat (limited to 'src/core/gpu/cl/kernels/ClSoftmaxKernel.cpp')
| -rw-r--r-- | src/core/gpu/cl/kernels/ClSoftmaxKernel.cpp | 355 |
1 files changed, 0 insertions, 355 deletions
diff --git a/src/core/gpu/cl/kernels/ClSoftmaxKernel.cpp b/src/core/gpu/cl/kernels/ClSoftmaxKernel.cpp deleted file mode 100644 index 000c9ad04d..0000000000 --- a/src/core/gpu/cl/kernels/ClSoftmaxKernel.cpp +++ /dev/null @@ -1,355 +0,0 @@ -/* - * Copyright (c) 2017-2021 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/core/gpu/cl/kernels/ClSoftmaxKernel.h" -#include "arm_compute/core/CL/ICLTensor.h" -#include "arm_compute/core/Utils.h" -#include "arm_compute/core/experimental/Types.h" -#include "arm_compute/core/utils/quantization/AsymmHelpers.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" - -namespace arm_compute -{ -namespace opencl -{ -namespace kernels -{ -namespace -{ -/** Calculates softmax parameters from the quantized input scale and scaling factor for the exponent and places them as build options. - * - * Prepares these build options: - * -INPUT_BETA_MULTIPLIER, INPUT_BETA_LEFT_SHIFT - quantized representation of beta multiplier. - * -DIFF_MIN - threshold difference between maximum value of input data and current processed value, - * it defines whether the value will be taken into account or not. - * - * @param[in] build_opts Build options to extend - * @param[in] input_scale Input scaling factor - * @param[in] beta Exponent scaling factor beta - */ -CLBuildOptions prepare_quantized_softmax_build_options(float input_scale, float beta) -{ - // Number of integer bits in temporary fixed-point representation of current-to-max difference - static const int scaled_diff_int_bits = 5; - // Number of integer bits used in temporary fixed-point representation of exponent accumulator - static const int exp_accumulation_in_bits = 12; - - const double beta_multiplier = std::min( - 1.0 * beta * input_scale * (1 << (31 - scaled_diff_int_bits)), - (1LL << 31) - 1.0); - int input_beta_multiplier; - int input_beta_left_shift; - quantization::calculate_quantized_multiplier_greater_than_one(beta_multiplier, &input_beta_multiplier, &input_beta_left_shift); - - const double max_input_rescaled = 1.0 * ((1 << scaled_diff_int_bits) - 1) * (1LL << (31 - scaled_diff_int_bits)) / (1LL << input_beta_left_shift); - const int diff_min = -1.f * std::floor(max_input_rescaled); - - CLBuildOptions build_opts; - build_opts.add_option("-DSCALED_DIFF_INT_BITS=" + support::cpp11::to_string(scaled_diff_int_bits)); - build_opts.add_option("-DEXP_ACCUMULATION_INT_BITS=" + support::cpp11::to_string(exp_accumulation_in_bits)); - build_opts.add_option("-DINPUT_BETA_MULTIPLIER=" + support::cpp11::to_string(input_beta_multiplier)); - build_opts.add_option("-DINPUT_BETA_LEFT_SHIFT=" + support::cpp11::to_string(input_beta_left_shift)); - build_opts.add_option("-DDIFF_MIN=" + support::cpp11::to_string(diff_min)); - - return build_opts; -} - -Status validate_arguments_1DMaxShiftExpSum(const ITensorInfo &src, const ITensorInfo &max, const ITensorInfo &dst, const ITensorInfo &sum) -{ - 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::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src, &max); - - const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(src.data_type()); - - // Checks performed when output is configured - if(dst.total_size() != 0) - { - if(is_quantized_asymmetric) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&dst, 1, DataType::S32); - } - else - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src, &dst); - } - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&src, &dst); - } - - // Checks performed when sum is configured - if(sum.total_size() != 0) - { - if(is_quantized_asymmetric) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&sum, 1, DataType::S32); - } - else - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&max, &sum); - } - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&max, &sum); - } - - return Status{}; -} - -Status validate_arguments_1DNorm(const ITensorInfo &src, const ITensorInfo &sum, const ITensorInfo &dst, const SoftmaxKernelInfo &info) -{ - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&src); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&src, 1, DataType::S32, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src, &sum); - ARM_COMPUTE_RETURN_ERROR_ON(info.is_log && !is_data_type_float(info.input_data_type)); - - // Note: output should always have a scale of 1/256 and offset 0 - const QuantizationInfo allowed_quantization_info = get_softmax_output_quantization_info(info.input_data_type, info.is_log); - const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(info.input_data_type); - - // Checks performed when output is configured - if(dst.total_size() != 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&src, &dst); - if(!is_quantized_asymmetric) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src, &dst); - } - else - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&dst, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED); - ARM_COMPUTE_RETURN_ERROR_ON(dst.quantization_info() != allowed_quantization_info); - } - } - - return Status{}; -} -} // namespace - -/**< Grid size (obtained through auto-tuning) */ -const unsigned int ClLogits1DMaxShiftExpSumKernel::_grid_size = 64; -/**< Vector size in the serial case (obtained through auto-tuning) */ -const unsigned int ClLogits1DMaxShiftExpSumKernel::_serial_vector_size = 8; -/**< Vector size in the parallel case (obtained through auto-tuning, enables the best memory access pattern for Bifrost) .*/ -const unsigned int ClLogits1DMaxShiftExpSumKernel::_parallel_vector_size = 4; - -void ClLogits1DMaxShiftExpSumKernel::configure(const CLCompileContext &compile_context, const ITensorInfo &src, ITensorInfo &max, ITensorInfo &dst, ITensorInfo &sum, const SoftmaxKernelInfo &info) -{ - auto padding_info = get_padding_info({ &src, &max, &dst, &sum }); - - // Output auto initialization if not yet initialized - auto_init_if_empty(sum, src.clone()->set_tensor_shape(max.tensor_shape())); - auto_init_if_empty(dst, *src.clone()); - - // Perform validation step - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_1DMaxShiftExpSum(src, max, dst, sum)); - - const DataType dt = src.data_type(); - const UniformQuantizationInfo qinfo = src.quantization_info().uniform(); - const size_t reduction_dim_size = src.dimension(0); - const float beta = info.beta; - const auto is_signed_qasymm8 = is_data_type_quantized_asymmetric_signed(info.input_data_type); - const int min_value = is_signed_qasymm8 ? CL_SCHAR_MIN : 0; - - ParallelReductionInfo parallel_reduction_info = is_parallel_reduction(reduction_dim_size); - const unsigned int vector_size = adjust_vec_size(std::get<1>(parallel_reduction_info), reduction_dim_size); - - // Set build options - CLBuildOptions build_opts; - build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(dt)); - build_opts.add_option("-DMIN_VALUE=" + support::cpp11::to_string(min_value)); - build_opts.add_option("-DVECTOR_SIZE=" + support::cpp11::to_string(vector_size)); - build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(reduction_dim_size)); - build_opts.add_option("-DVECTOR_SIZE_LEFTOVER=" + support::cpp11::to_string(reduction_dim_size % vector_size)); - build_opts.add_option("-DLOG_VECTOR_SIZE=" + support::cpp11::to_string(lround(log2(vector_size)))); - build_opts.add_option_if((reduction_dim_size % vector_size) != 0, "-DNON_MULTIPLE_OF_VECTOR_SIZE"); - build_opts.add_option_if(is_signed_qasymm8, "-DQASYMM8_SIGNED"); - build_opts.add_option_if(is_data_type_float(dt) && (beta != 1.0f), "-DBETA=" + float_to_string_with_full_precision(beta)); - build_opts.add_option_if(is_data_type_float(dt) && info.is_log, "-DLOG_SOFTMAX"); - build_opts.add_option_if(is_data_type_float(dt), "-DMINVAL=" + ((dt == DataType::F16) ? std::string("-HALF_MAX") : std::string("-FLT_MAX"))); - build_opts.add_options_if(is_data_type_quantized_asymmetric(dt), prepare_quantized_softmax_build_options(qinfo.scale, beta).options()); - - cl::NDRange lws_hint(cl::NullRange); - std::string kernel_name = std::string("softmax_layer_max_shift_exp_sum_") + (is_data_type_quantized_asymmetric(dt) ? "quantized_" : ""); - - // Configure parallel kernel if needed - if(std::get<0>(parallel_reduction_info)) - { - kernel_name += "parallel"; - bool is_grid_size_pow2 = (_grid_size != 0) && ((_grid_size & (_grid_size - 1)) == 0); - build_opts.add_option_if(is_grid_size_pow2 && _grid_size <= 256, "-DGRID_SIZE=" + support::cpp11::to_string(_grid_size)); - - // Handle boundary conditions. - const unsigned int multiple_grid_size = (reduction_dim_size / vector_size) % _grid_size; - build_opts.add_option_if((multiple_grid_size != 0) || ((reduction_dim_size % vector_size) != 0), "-DNON_MULTIPLE_OF_GRID_SIZE"); - // Setting _lws_hint in this way can also communicate grid_size to ClLogits1DMaxShiftExpSumKernel::run(). - // A single workgroup performs reduction in dimension 0 in the parallel case, hence lws[0]==gws[0]. - lws_hint = cl::NDRange(_grid_size); - } - else - { - kernel_name += "serial"; - } - - // Create kernel. - _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); - - // Configure window - Window win = calculate_max_window(src, Steps(reduction_dim_size)); - IClKernel::configure_internal(win, lws_hint); - - ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); -} - -Status ClLogits1DMaxShiftExpSumKernel::validate(const ITensorInfo &src, const ITensorInfo &max, const ITensorInfo &dst, const ITensorInfo &sum) -{ - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_1DMaxShiftExpSum(src, max, dst, sum)); - return Status{}; -} - -ClLogits1DMaxShiftExpSumKernel::ParallelReductionInfo ClLogits1DMaxShiftExpSumKernel::is_parallel_reduction(size_t size) -{ - bool is_parallel_reduction = (size >= (_grid_size * _serial_vector_size)) && (_grid_size > 1); - unsigned int vector_size = is_parallel_reduction ? _parallel_vector_size : _serial_vector_size; - return std::make_tuple(is_parallel_reduction, vector_size); -} - -void ClLogits1DMaxShiftExpSumKernel::run_op(ITensorPack &tensors, const Window &window, ::cl::CommandQueue &queue) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); - - 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)); - auto max = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_INT_0)); - auto sum = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_INT_1)); - - ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst, max, sum); - - // Collapse window in Z dimension - Window window_collapsed = window.collapse_if_possible(IClKernel::window(), Window::DimZ); - - // Reconfigure window in case of parallel reduction - ParallelReductionInfo parallel_reduction_info = is_parallel_reduction(src->info()->dimension(0)); - if(std::get<0>(parallel_reduction_info)) - { - // Launch grid_size parallel work items - window_collapsed.set(Window::DimX, Window::Dimension(0, _grid_size, 1)); - } - - // Get slices - Window slice = window_collapsed.first_slice_window_3D(); - do - { - unsigned int idx = 0; - // Set inputs - add_3D_tensor_argument(idx, src, slice); - add_3D_tensor_argument(idx, max, slice); - add_3D_tensor_argument(idx, dst, slice); - add_3D_tensor_argument(idx, sum, slice); - enqueue(queue, *this, slice, lws_hint()); - } - while(window_collapsed.slide_window_slice_3D(slice)); -} - -void ClLogits1DNormKernel::configure(const CLCompileContext &compile_context, const ITensorInfo &src, const ITensorInfo &sum, ITensorInfo &dst, const SoftmaxKernelInfo &info) -{ - auto padding_info = get_padding_info({ &src, &dst, &sum }); - - // Note: output should always have a scale of 1/256 and offset 0 - const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(info.input_data_type); - const DataType output_data_type = info.input_data_type; - const QuantizationInfo allowed_quantization_info = get_softmax_output_quantization_info(info.input_data_type, info.is_log); - const UniformQuantizationInfo qinfo = src.quantization_info().uniform(); - - // Output auto initialization if not yet initialized - auto_init_if_empty(dst, src.clone()->set_data_type(output_data_type).set_quantization_info(allowed_quantization_info)); - - // Perform validation step - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_1DNorm(src, sum, dst, info)); - - const auto is_signed_qasymm8 = is_data_type_quantized_asymmetric_signed(info.input_data_type); - const int min_value = is_signed_qasymm8 ? CL_SCHAR_MIN : 0; - const unsigned int vector_size = adjust_vec_size(16, src.dimension(0)); - - // Set build options - CLBuildOptions build_opts; - build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(info.input_data_type)); - build_opts.add_option("-DMIN_VALUE=" + support::cpp11::to_string(min_value)); - build_opts.add_option("-DVECTOR_SIZE=" + support::cpp11::to_string(vector_size)); - build_opts.add_option("-DVECTOR_SIZE_LEFTOVER=" + support::cpp11::to_string(src.dimension(0) % vector_size)); - build_opts.add_option_if(is_data_type_quantized_asymmetric_signed(info.input_data_type), "-DQASYMM8_SIGNED"); - build_opts.add_options_if(is_quantized_asymmetric, - prepare_quantized_softmax_build_options(qinfo.scale, info.beta).options()); - build_opts.add_option_if(info.is_log, "-DLOG_SOFTMAX"); - - // Create kernel - std::string kernel_name = std::string("softmax_layer_norm") + (is_quantized_asymmetric ? "_quantized" : ""); - _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); - - // Configure window - auto win = calculate_max_window(src, Steps(vector_size)); - ICLKernel::configure_internal(win); - - ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); -} - -Status ClLogits1DNormKernel::validate(const ITensorInfo &src, const ITensorInfo &sum, const ITensorInfo &dst, const SoftmaxKernelInfo &info) -{ - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_1DNorm(src, sum, dst, info)); - - return Status{}; -} - -void ClLogits1DNormKernel::run_op(ITensorPack &tensors, const Window &window, ::cl::CommandQueue &queue) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); - - 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)); - auto sum = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_INT_0)); - - ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst, sum); - - Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); - Window slice = window_collapsed.first_slice_window_3D(); - - do - { - Window sum_slice = slice; - sum_slice.set(Window::DimX, Window::Dimension(0, 1, 1)); - - unsigned int idx = 0; - // Set inputs - add_3D_tensor_argument(idx, src, slice); - add_3D_tensor_argument(idx, sum, sum_slice); - add_3D_tensor_argument(idx, dst, slice); - enqueue(queue, *this, slice, lws_hint()); - } - while(window_collapsed.slide_window_slice_3D(slice)); -} -} // namespace kernels -} // namespace opencl -} // namespace arm_compute
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