| /* |
| * 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 "src/core/CL/kernels/CLComparisonKernel.h" |
| |
| #include "arm_compute/core/CL/CLHelpers.h" |
| #include "arm_compute/core/CL/ICLTensor.h" |
| #include "src/core/CL/CLValidate.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| #include "support/StringSupport.h" |
| |
| #include <map> |
| |
| namespace arm_compute |
| { |
| namespace |
| { |
| // Create supported comparisons map |
| const std::map<ComparisonOperation, std::string> supported_comparison_ops = |
| { |
| { ComparisonOperation::Equal, "EQUAL" }, |
| { ComparisonOperation::NotEqual, "NOTEQUAL" }, |
| { ComparisonOperation::Greater, "GREATER" }, |
| { ComparisonOperation::GreaterEqual, "GREATEREQUAL" }, |
| { ComparisonOperation::Less, "LESS" }, |
| { ComparisonOperation::LessEqual, "LESSEQUAL" }, |
| }; |
| |
| int calculate_num_elems_processed_per_iteration(const ITensorInfo &input) |
| { |
| return 16 / input.element_size(); |
| } |
| |
| Status validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output, ComparisonOperation operation) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&input1); |
| ARM_COMPUTE_RETURN_ERROR_ON(input1.data_type() == DataType::UNKNOWN); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &input2); |
| ARM_COMPUTE_RETURN_ERROR_ON(supported_comparison_ops.count(operation) == 0); |
| |
| 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::U8); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output.tensor_shape(), 0), |
| "Wrong shape for output"); |
| } |
| |
| return Status{}; |
| } |
| |
| std::pair<Status, Window> validate_and_configure_window(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; |
| |
| const unsigned int num_elems_processed_per_iteration = calculate_num_elems_processed_per_iteration(input1); |
| |
| // Auto initialize output if not initialized |
| auto_init_if_empty(output, out_shape, 1, DataType::U8, QuantizationInfo()); |
| |
| 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); |
| } |
| } // namespace |
| |
| CLComparisonKernel::CLComparisonKernel() |
| : _input1(nullptr), _input2(nullptr), _output(nullptr) |
| { |
| } |
| |
| void CLComparisonKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ComparisonOperation operation) |
| { |
| configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, operation); |
| } |
| |
| void CLComparisonKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ComparisonOperation operation) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input1->info(), *input2->info(), *output->info(), operation)); |
| |
| // 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; |
| |
| const std::string &operation_name = supported_comparison_ops.at(operation); |
| std::string kernel_name = "compare_" + lower_string(operation_name); |
| |
| // Set kernel build options |
| std::set<std::string> build_opts; |
| build_opts.emplace("-DDATA_TYPE=" + get_cl_type_from_data_type(input1->info()->data_type())); |
| build_opts.emplace("-DVEC_SIZE=" + support::cpp11::to_string(calculate_num_elems_processed_per_iteration(*input1->info()))); |
| build_opts.emplace("-DOP=" + operation_name); |
| build_opts.emplace("-DOP_NAME=" + lower_string(operation_name)); |
| if(is_data_type_quantized(input1->info()->data_type())) |
| { |
| const UniformQuantizationInfo iq1_info = input1->info()->quantization_info().uniform(); |
| const UniformQuantizationInfo iq2_info = input2->info()->quantization_info().uniform(); |
| |
| build_opts.emplace("-DOFFSET_IN1=" + support::cpp11::to_string(iq1_info.offset)); |
| build_opts.emplace("-DOFFSET_IN2=" + support::cpp11::to_string(iq2_info.offset)); |
| build_opts.emplace("-DSCALE_IN1=" + float_to_string_with_full_precision(iq1_info.scale)); |
| build_opts.emplace("-DSCALE_IN2=" + float_to_string_with_full_precision(iq2_info.scale)); |
| kernel_name += "_quantized"; |
| } |
| |
| // Create kernel |
| _kernel = create_kernel(compile_context, kernel_name, build_opts); |
| |
| ICLKernel::configure_internal(win_config.second); |
| |
| // Set config_id for enabling LWS tuning |
| _config_id = kernel_name; |
| _config_id += "_"; |
| _config_id += lower_string(string_from_data_type(input1->info()->data_type())); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(output->info()->dimension(0)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(output->info()->dimension(1)); |
| _config_id += lower_string(string_from_data_layout(input1->info()->data_layout())); |
| } |
| |
| Status CLComparisonKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ComparisonOperation operation) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output); |
| |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*input1, *input2, *output, operation)); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(*input1->clone(), *input2->clone(), *output->clone()).first); |
| |
| return Status{}; |
| } |
| |
| void CLComparisonKernel::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 CLComparisonKernel::border_size() const |
| { |
| const int num_elems_processed_per_iteration = calculate_num_elems_processed_per_iteration(*_input1->info()); |
| |
| 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 }; |
| } |
| } // namespace arm_compute |