diff options
Diffstat (limited to 'src/core/CL/kernels/CLElementwiseOperationKernel.cpp')
| -rw-r--r-- | src/core/CL/kernels/CLElementwiseOperationKernel.cpp | 463 |
1 files changed, 0 insertions, 463 deletions
diff --git a/src/core/CL/kernels/CLElementwiseOperationKernel.cpp b/src/core/CL/kernels/CLElementwiseOperationKernel.cpp deleted file mode 100644 index 00a97d50e9..0000000000 --- a/src/core/CL/kernels/CLElementwiseOperationKernel.cpp +++ /dev/null @@ -1,463 +0,0 @@ -/* - * Copyright (c) 2018-2020 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 "arm_compute/core/CL/kernels/CLElementwiseOperationKernel.h" - -#include "arm_compute/core/CL/CLHelpers.h" -#include "arm_compute/core/CL/CLValidate.h" -#include "arm_compute/core/CL/ICLTensor.h" -#include "support/StringSupport.h" -#include <map> - -namespace arm_compute -{ -namespace -{ -constexpr unsigned int num_elems_processed_per_iteration = 16; - -std::map<ArithmeticOperation, std::string> supported_arithmetic_ops = -{ - { ArithmeticOperation::ADD, "ADD" }, - { ArithmeticOperation::SUB, "SUB" }, - { ArithmeticOperation::DIV, "DIV" }, - { ArithmeticOperation::SQUARED_DIFF, "SQUARED_DIFF" }, - { ArithmeticOperation::MIN, "MIN" }, - { ArithmeticOperation::MAX, "MAX" }, - { ArithmeticOperation::POWER, "POWER" }, - { ArithmeticOperation::PRELU, "PRELU" }, -}; - -std::map<ArithmeticOperation, std::string> supported_sat_arithmetic_ops = -{ - { ArithmeticOperation::ADD, "ADD" }, - { ArithmeticOperation::SUB, "SUB" }, -}; - -std::string generate_id_for_tuning_common(const std::string &kernel_name, const ITensorInfo &input1, const ITensorInfo &output) -{ - std::string config_id; - // Set config_id for enabling LWS tuning - config_id = kernel_name; - config_id += "_"; - config_id += lower_string(string_from_data_type(input1.data_type())); - config_id += "_"; - config_id += support::cpp11::to_string(output.dimension(0)); - config_id += "_"; - config_id += support::cpp11::to_string(output.dimension(1)); - return config_id; -} - -Status validate_arguments_with_float_only_supported_rules(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output) -{ - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(&input1, &input2, &output); - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&input1); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input1, 1, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &input2); - - const TensorShape out_shape = TensorShape::broadcast_shape(input1.tensor_shape(), input2.tensor_shape()); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); - - // Validate in case of configured output - if(output.total_size() > 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&output, 1, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &output); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output.tensor_shape(), 0), - "Wrong shape for output"); - } - - return Status{}; -} - -Status validate_arguments_with_arithmetic_rules(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output) -{ - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&input1); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input1, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S16, DataType::QSYMM16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&input2); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input2, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S16, DataType::QSYMM16, DataType::F16, DataType::F32); - - const bool is_quantized = is_data_type_quantized(input1.data_type()) || is_data_type_quantized(input2.data_type()); - if(is_quantized) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &input2); - - if(is_data_type_quantized_symmetric(input1.data_type())) - { - const int32_t in1_offset = input1.quantization_info().uniform().offset; - const int32_t in2_offset = input2.quantization_info().uniform().offset; - ARM_COMPUTE_RETURN_ERROR_ON_MSG(in1_offset != 0, "For quantized symmetric, offset must be zero"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(in2_offset != 0, "For quantized symmetric, offset must be zero"); - } - } - - const TensorShape out_shape = TensorShape::broadcast_shape(input1.tensor_shape(), input2.tensor_shape()); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); - - // Validate in case of configured output - if(output.total_size() > 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&output); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&output, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S16, DataType::QSYMM16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((output.data_type() == DataType::U8) && ((input1.data_type() != DataType::U8) || (input2.data_type() != DataType::U8)), - "Output can only be U8 if both inputs are U8"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output.tensor_shape(), 0), - "Wrong shape for output"); - - if(is_quantized) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &output); - - if(is_data_type_quantized_symmetric(output.data_type())) - { - const int32_t offset = output.quantization_info().uniform().offset; - ARM_COMPUTE_RETURN_ERROR_ON_MSG(offset != 0, "For quantized symmetric, offset must be zero"); - } - } - } - return Status{}; -} - -CLBuildOptions generate_build_options_with_arithmetic_rules(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output, const std::string &operation_string) -{ - CLBuildOptions build_opts; - - build_opts.add_option("-DDATA_TYPE_IN1=" + get_cl_type_from_data_type(input1.data_type())); - build_opts.add_option("-DDATA_TYPE_IN2=" + get_cl_type_from_data_type(input2.data_type())); - build_opts.add_option("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output.data_type())); - build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)); - build_opts.add_option("-DOP=" + operation_string); - if(is_data_type_quantized(input1.data_type())) - { - const UniformQuantizationInfo iq1info = input1.quantization_info().uniform(); - const UniformQuantizationInfo iq2info = input2.quantization_info().uniform(); - const UniformQuantizationInfo oqinfo = output.quantization_info().uniform(); - - build_opts.add_option("-DOFFSET_IN1=" + support::cpp11::to_string(iq1info.offset)); - build_opts.add_option("-DOFFSET_IN2=" + support::cpp11::to_string(iq2info.offset)); - build_opts.add_option("-DOFFSET_OUT=" + support::cpp11::to_string(oqinfo.offset)); - build_opts.add_option("-DSCALE_IN1=" + float_to_string_with_full_precision(iq1info.scale)); - build_opts.add_option("-DSCALE_IN2=" + float_to_string_with_full_precision(iq2info.scale)); - build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oqinfo.scale)); - } - return build_opts; -} - -std::pair<Status, Window> configure_window_arithmetic_common(const ValidRegion &valid_region, ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output) -{ - Window win = calculate_max_window(valid_region, Steps(num_elems_processed_per_iteration)); - Window win_input1 = win.broadcast_if_dimension_le_one(input1); - Window win_input2 = win.broadcast_if_dimension_le_one(input2); - - AccessWindowHorizontal input1_access(&input1, 0, num_elems_processed_per_iteration); - AccessWindowHorizontal input2_access(&input2, 0, num_elems_processed_per_iteration); - AccessWindowHorizontal output_access(&output, 0, num_elems_processed_per_iteration); - - bool window_changed = update_window_and_padding(win_input1, input1_access) - || update_window_and_padding(win_input2, input2_access) - || update_window_and_padding(win, output_access); - - output_access.set_valid_region(win, valid_region); - - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_pair(err, win); -} - -std::pair<Status, Window> validate_and_configure_window_for_arithmetic_operators(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output) -{ - const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(input1, input2); - const TensorShape &out_shape = broadcast_pair.first; - const ValidRegion &valid_region = broadcast_pair.second; - - set_shape_if_empty(output, out_shape); - - if(input1.data_type() == DataType::S16 || input2.data_type() == DataType::S16) - { - set_format_if_unknown(output, Format::S16); - } - else if(input1.data_type() == DataType::F16 || input2.data_type() == DataType::F16) - { - set_format_if_unknown(output, Format::F16); - } - else if(input1.data_type() == DataType::F32 || input2.data_type() == DataType::F32) - { - set_format_if_unknown(output, Format::F32); - } - else if(input1.data_type() == DataType::QASYMM8 || input2.data_type() == DataType::QASYMM8) - { - set_data_type_if_unknown(output, DataType::QASYMM8); - } - else if(input1.data_type() == DataType::QASYMM8_SIGNED || input2.data_type() == DataType::QASYMM8_SIGNED) - { - set_data_type_if_unknown(output, DataType::QASYMM8_SIGNED); - } - else if(input1.data_type() == DataType::QSYMM16 || input2.data_type() == DataType::QSYMM16) - { - set_data_type_if_unknown(output, DataType::QSYMM16); - } - - return configure_window_arithmetic_common(valid_region, input1, input2, output); -} - -std::pair<Status, Window> validate_and_configure_window_for_division(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output) -{ - const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(input1, input2); - const TensorShape &out_shape = broadcast_pair.first; - const ValidRegion &valid_region = broadcast_pair.second; - auto_init_if_empty(output, out_shape, 1, input1.data_type()); - return configure_window_arithmetic_common(valid_region, input1, input2, output); -} -} // namespace - -CLElementwiseOperationKernel::CLElementwiseOperationKernel() - : _act_info(), _input1(nullptr), _input2(nullptr), _output(nullptr) -{ -} - -void CLElementwiseOperationKernel::configure_common(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output) -{ - configure_common(CLKernelLibrary::get().get_compile_context(), input1, input2, output); -} - -void CLElementwiseOperationKernel::configure_common(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input1->info(), *input2->info(), *output->info())); - - // Configure kernel window - auto win_config = validate_and_configure_window(*input1->info(), *input2->info(), *output->info()); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - - _input1 = input1; - _input2 = input2; - _output = output; - - std::string kernel_name = "elementwise_operation_" + name(); - if(is_data_type_quantized(input1->info()->data_type())) - { - kernel_name += "_quantized"; - } - - // Set kernel build options - CLBuildOptions build_opts = generate_build_options(*input1->info(), *input2->info(), *output->info()); - if(_act_info.enabled()) - { - build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(_act_info.activation()))); - build_opts.add_option("-DA_VAL=" + float_to_string_with_full_precision(_act_info.a())); - build_opts.add_option("-DB_VAL=" + float_to_string_with_full_precision(_act_info.b())); - } - - // Create kernel - _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); - - ICLKernel::configure_internal(win_config.second); - - _config_id = generate_id_for_tuning(kernel_name, *input1->info(), *output->info()); -} - -void CLElementwiseOperationKernel::run(const Window &window, cl::CommandQueue &queue) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); - - const TensorShape &in_shape1 = _input1->info()->tensor_shape(); - const TensorShape &in_shape2 = _input2->info()->tensor_shape(); - const TensorShape &out_shape = _output->info()->tensor_shape(); - - bool can_collapse = true; - const bool is_vector = in_shape1.num_dimensions() == 1 || in_shape2.num_dimensions() == 1; - if(std::min(in_shape1.total_size(), in_shape2.total_size()) > 1 && !is_vector) - { - can_collapse = (std::min(in_shape1.num_dimensions(), in_shape2.num_dimensions()) > Window::DimZ); - for(size_t d = Window::DimZ; can_collapse && (d < out_shape.num_dimensions()); d++) - { - can_collapse = (in_shape1[d] == in_shape2[d]); - } - } - - bool has_collapsed = false; - Window collapsed = can_collapse ? window.collapse_if_possible(ICLKernel::window(), Window::DimZ, &has_collapsed) : window; - - const TensorShape &in_shape1_collapsed = has_collapsed ? in_shape1.collapsed_from(Window::DimZ) : in_shape1; - const TensorShape &in_shape2_collapsed = has_collapsed ? in_shape2.collapsed_from(Window::DimZ) : in_shape2; - - Window slice = collapsed.first_slice_window_3D(); - Window slice_input1 = slice.broadcast_if_dimension_le_one(in_shape1_collapsed); - Window slice_input2 = slice.broadcast_if_dimension_le_one(in_shape2_collapsed); - - do - { - unsigned int idx = 0; - - add_3D_tensor_argument(idx, _input1, slice_input1); - add_3D_tensor_argument(idx, _input2, slice_input2); - add_3D_tensor_argument(idx, _output, slice); - - enqueue(queue, *this, slice, lws_hint()); - - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input1)); - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input2)); - } - while(collapsed.slide_window_slice_3D(slice)); -} - -BorderSize CLElementwiseOperationKernel::border_size() const -{ - const unsigned int replicateSize = _output->info()->dimension(0) - std::min(_input1->info()->dimension(0), _input2->info()->dimension(0)); - const unsigned int border = std::min<unsigned int>(num_elems_processed_per_iteration - 1U, replicateSize); - return BorderSize{ 0, border, 0, 0 }; -} - -/** Arithmetic operations with saturation*/ - -void CLSaturatedArithmeticOperationKernel::configure(ArithmeticOperation op, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const ConvertPolicy &policy, - const ActivationLayerInfo &act_info) -{ - configure(CLKernelLibrary::get().get_compile_context(), op, input1, input2, output, policy, act_info); -} - -void CLSaturatedArithmeticOperationKernel::configure(const CLCompileContext &compile_context, ArithmeticOperation op, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, - const ConvertPolicy &policy, - const ActivationLayerInfo &act_info) -{ - _policy = policy; - _op = op; - _act_info = act_info; - configure_common(compile_context, input1, input2, output); -} - -Status CLSaturatedArithmeticOperationKernel::validate(ArithmeticOperation op, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ConvertPolicy &policy, - const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_UNUSED(op, policy); - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output); - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_with_arithmetic_rules(*input1, *input2, *output)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_for_arithmetic_operators(*input1->clone(), *input2->clone(), *output->clone()).first); - ARM_COMPUTE_RETURN_ERROR_ON(act_info.enabled() && !is_data_type_float(output->data_type())); - - return Status{}; -} - -std::pair<Status, Window> CLSaturatedArithmeticOperationKernel::validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output) -{ - return validate_and_configure_window_for_arithmetic_operators(input1, input2, output); -} - -Status CLSaturatedArithmeticOperationKernel::validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output) -{ - return validate_arguments_with_arithmetic_rules(input1, input2, output); -} - -CLBuildOptions CLSaturatedArithmeticOperationKernel::generate_build_options(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output) -{ - const bool has_float_out = is_data_type_float(output.data_type()); - auto build_options = generate_build_options_with_arithmetic_rules(input1, input2, output, name()); - build_options.add_option((_policy == ConvertPolicy::WRAP || has_float_out) ? "-DWRAP" : "-DSATURATE"); - return build_options; -} -std::string CLSaturatedArithmeticOperationKernel::generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &input1, const ITensorInfo &output) -{ - auto config_id = generate_id_for_tuning_common(kernel_name, input1, output); - config_id += (_policy == ConvertPolicy::WRAP) ? "_wrap_" : "_saturate_"; - config_id += lower_string(string_from_data_layout(input1.data_layout())); - return config_id; -} - -std::string CLSaturatedArithmeticOperationKernel::name() -{ - return supported_sat_arithmetic_ops[_op]; -} - -/** Arithmetic operations*/ - -void CLArithmeticOperationKernel::configure(ArithmeticOperation op, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info) -{ - configure(CLKernelLibrary::get().get_compile_context(), op, input1, input2, output, act_info); -} - -void CLArithmeticOperationKernel::configure(const CLCompileContext &compile_context, ArithmeticOperation op, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, - const ActivationLayerInfo &act_info) -{ - _op = op; - _act_info = act_info; - configure_common(compile_context, input1, input2, output); -} - -Status CLArithmeticOperationKernel::validate(ArithmeticOperation op, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output); - if(op == ArithmeticOperation::DIV || op == ArithmeticOperation::POWER) - { - // Division and Power operators don't support integer arithmetic - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_with_float_only_supported_rules(*input1, *input2, *output)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_for_division(*input1->clone(), *input2->clone(), *output->clone()).first); - } - else - { - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_with_arithmetic_rules(*input1, *input2, *output)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_for_arithmetic_operators(*input1->clone(), *input2->clone(), *output->clone()).first); - } - ARM_COMPUTE_RETURN_ERROR_ON(act_info.enabled() && !is_data_type_float(output->data_type())); - - return Status{}; -} -std::pair<Status, Window> CLArithmeticOperationKernel::validate_and_configure_window(ITensorInfo &input1, ITensorInfo &input2, ITensorInfo &output) -{ - if(_op == ArithmeticOperation::DIV || _op == ArithmeticOperation::POWER) - { - // Division and Power operators don't support integer arithmetic - return validate_and_configure_window_for_division(input1, input2, output); - } - else - { - return validate_and_configure_window_for_arithmetic_operators(input1, input2, output); - } -} -Status CLArithmeticOperationKernel::validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output) -{ - if(_op == ArithmeticOperation::DIV || _op == ArithmeticOperation::POWER) - { - // Division and Power operators don't support integer arithmetic - return validate_arguments_with_float_only_supported_rules(input1, input2, output); - } - else - { - return validate_arguments_with_arithmetic_rules(input1, input2, output); - } -} - -CLBuildOptions CLArithmeticOperationKernel::generate_build_options(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output) -{ - return generate_build_options_with_arithmetic_rules(input1, input2, output, name()); -} -std::string CLArithmeticOperationKernel::generate_id_for_tuning(const std::string &kernel_name, const ITensorInfo &input1, const ITensorInfo &output) -{ - return generate_id_for_tuning_common(kernel_name, input1, output); -} - -std::string CLArithmeticOperationKernel::name() -{ - return supported_arithmetic_ops[_op]; -} -} // namespace arm_compute |