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Diffstat (limited to 'src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp')
| -rw-r--r-- | src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp | 283 |
1 files changed, 283 insertions, 0 deletions
diff --git a/src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp b/src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp new file mode 100644 index 0000000000..c8e87ba5ce --- /dev/null +++ b/src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp @@ -0,0 +1,283 @@ +/* + * Copyright (c) 2019 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/CLArgMinMaxLayerKernel.h" + +#include "arm_compute/core/AccessWindowStatic.h" +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/CL/CLValidate.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/Window.h" + +#include "support/ToolchainSupport.h" + +namespace arm_compute +{ +namespace +{ +constexpr unsigned int vector_size = 16; + +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *prev_output, const ITensorInfo *output, unsigned int axis, ReductionOperation op) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::S32, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(op != ReductionOperation::ARG_IDX_MAX && op != ReductionOperation::ARG_IDX_MIN, "Only ARG_IDX_MAX and ARG_IDX_MIN are supported"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Reduction axis greater than max number of dimensions"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis > 3, "Unsupported reduction axis"); + + if(output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U32, DataType::S32); + } + if(prev_output != nullptr && prev_output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(prev_output, 1, DataType::U32, DataType::S32); + if(output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(prev_output, output); + } + } + + return Status{}; +} + +std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *prev_output, ITensorInfo *output, unsigned int axis, ReductionOperation op) +{ + ARM_COMPUTE_UNUSED(op); + // Output tensor auto initialization if not yet initialized + TensorShape output_shape{ input->tensor_shape() }; + output_shape.set(axis, 1); + DataType output_data_type = DataType::S32; + auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape).set_data_type(output_data_type).reset_padding().set_is_resizable(true)); + + Window win = calculate_max_window((prev_output != nullptr) ? (*prev_output) : (*input), Steps(vector_size)); + bool window_changed = false; + + switch(axis) + { + case 0: + { + ITensorInfo *input_tensor_access = prev_output != nullptr ? prev_output : input; + AccessWindowStatic input_access(input_tensor_access, 0, 0, static_cast<int>(input_tensor_access->dimension(0)), 1); + AccessWindowHorizontal output_access(output, 0, 1); + window_changed = update_window_and_padding(win, input_access, output_access); + output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); + } + break; + case 1: + case 2: + case 3: + { + AccessWindowHorizontal input_access(input, 0, vector_size); + AccessWindowHorizontal output_access(output, 0, vector_size); + window_changed = update_window_and_padding(win, input_access, output_access); + output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); + } + break; + default: + ARM_COMPUTE_ERROR("Not supported"); + } + + Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; + return std::make_tuple(err, win); +} +} // namespace + +CLArgMinMaxLayerKernel::CLArgMinMaxLayerKernel() + : _input(nullptr), _prev_output(nullptr), _output(nullptr), _reduction_axis(0), _op(ReductionOperation::ARG_IDX_MAX) +{ +} + +void CLArgMinMaxLayerKernel::configure(const ICLTensor *input, const ICLTensor *prev_output, ICLTensor *output, unsigned int axis, ReductionOperation op) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (prev_output != nullptr) ? prev_output->info() : nullptr, output->info(), axis, op)); + auto win_config = validate_and_configure_window(input->info(), (prev_output != nullptr) ? prev_output->info() : nullptr, output->info(), axis, op); + ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config)); + + _input = input; + _prev_output = prev_output; + _output = output; + _reduction_axis = axis; + _op = op; + + // Set build options + CLBuildOptions build_opts; + const std::string data_type_promoted = get_cl_type_from_data_type(input->info()->data_type()); + + build_opts.add_option_if(_prev_output != nullptr, "-DPREV_OUTPUT"); + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); + build_opts.add_option("-DDATA_TYPE_PROMOTED=" + data_type_promoted); + build_opts.add_option_if(is_data_type_float(input->info()->data_type()), "-DFLOAT_DATA_TYPE"); + build_opts.add_option_if(op == ReductionOperation::ARG_IDX_MAX, "-DARG_MAX"); + build_opts.add_option_if(op == ReductionOperation::ARG_IDX_MIN, "-DARG_MIN"); + build_opts.add_option("-DCOND_DATA_TYPE=" + get_cl_select_type_from_data_type(input->info()->data_type())); + build_opts.add_option("-DDATA_TYPE_OUTPUT=" + get_cl_type_from_data_type(output->info()->data_type())); + + // Create kernel + cl::NDRange lws_hint = CLKernelLibrary::get().default_ndrange(); + std::string kernel_axis_name; + switch(axis) + { + case 0: + { + const ICLTensor *input_for_width = prev_output != nullptr ? _prev_output : _input; + build_opts.add_option("-DWIDTH=" + support::cpp11::to_string(input_for_width->info()->dimension(0))); + + kernel_axis_name = "x"; + lws_hint = create_lws_hint_parallel_implementations(input_for_width->info()->dimension(0), vector_size); + } + break; + case 1: + build_opts.add_option("-DHEIGHT=" + support::cpp11::to_string(input->info()->dimension(1))); + kernel_axis_name = "y"; + break; + case 2: + build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(input->info()->dimension(2))); + kernel_axis_name = "z"; + break; + case 3: + build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(input->info()->dimension(2))); + build_opts.add_option("-DBATCH=" + support::cpp11::to_string(input->info()->dimension(3))); + kernel_axis_name = "w"; + break; + default: + ARM_COMPUTE_ERROR("Not supported"); + } + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("arg_min_max_" + kernel_axis_name, build_opts.options())); + + // Configure kernel window + ICLKernel::configure_internal(std::get<1>(win_config), lws_hint); +} + +Status CLArgMinMaxLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *prev_output, const ITensorInfo *output, unsigned int axis, ReductionOperation op) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, prev_output, output, axis, op)); + ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), (prev_output != nullptr) ? prev_output->clone().get() : nullptr, output->clone().get(), axis, op))); + return Status{}; +} + +void CLArgMinMaxLayerKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); + + switch(_reduction_axis) + { + case 0: + { + // Set out window + Window out_window(window); + out_window.set(Window::DimX, Window::Dimension(0, 0, 0)); + + // Get first input and output slices + Window in_slice = window.first_slice_window_2D(); + Window out_slice = out_window.first_slice_window_2D(); + + // Reshape window + const unsigned int border_width = ((in_slice.x().end() % vector_size) != 0) ? vector_size - in_slice.x().end() % vector_size : 0; + in_slice.set(Window::DimX, Window::Dimension(in_slice.x().start(), in_slice.x().end() + border_width, in_slice.x().step())); + const unsigned int num_tensors = _prev_output != nullptr ? 3 : 2; + + // Set local sums buffer + unsigned int local_res_size = lws_hint()[0] * _output->info()->element_size(); + _kernel.setArg(num_arguments_per_2D_tensor() * num_tensors, local_res_size, nullptr); + do + { + unsigned int idx = 0; + add_2D_tensor_argument(idx, _input, in_slice); + if(_prev_output != nullptr) + { + add_2D_tensor_argument(idx, _prev_output, in_slice); + } + add_2D_tensor_argument(idx, _output, out_slice); + enqueue(queue, *this, in_slice, lws_hint()); + } + while(window.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(out_slice)); + } + break; + case 1: + { + // Get first input and output slices + Window window_in{ window }; + window_in.set(Window::DimY, Window::Dimension(0, _input->info()->dimension(1), _input->info()->dimension(1))); + Window in_slice = window_in.first_slice_window_2D(); + Window out_slice = window.first_slice_window_2D(); + + do + { + unsigned int idx = 0; + add_2D_tensor_argument(idx, _input, in_slice); + add_2D_tensor_argument(idx, _output, out_slice); + enqueue(queue, *this, in_slice, lws_hint()); + } + while(window_in.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(out_slice)); + } + break; + case 2: + { + // Get first input and output slices + Window window_in{ window }; + window_in.set(Window::DimZ, Window::Dimension(0, _input->info()->dimension(2), _input->info()->dimension(2))); + Window in_slice = window_in.first_slice_window_3D(); + Window out_slice = window.first_slice_window_3D(); + + do + { + unsigned int idx = 0; + add_3D_tensor_argument(idx, _input, in_slice); + add_3D_tensor_argument(idx, _output, out_slice); + enqueue(queue, *this, in_slice, lws_hint()); + } + while(window_in.slide_window_slice_3D(in_slice) && window.slide_window_slice_3D(out_slice)); + } + break; + case 3: + { + // Get first input and output slices + Window window_in{ window }; + window_in.set(3, Window::Dimension(0, 1, 1)); + Window in_slice = window_in.first_slice_window_4D(); + Window out_slice = window.first_slice_window_4D(); + + do + { + unsigned int idx = 0; + add_4D_tensor_argument(idx, _input, in_slice); + add_4D_tensor_argument(idx, _output, out_slice); + enqueue(queue, *this, in_slice, lws_hint()); + } + while(window_in.slide_window_slice_4D(in_slice) && window.slide_window_slice_4D(out_slice)); + } + break; + default: + ARM_COMPUTE_ERROR("Not supported"); + } +} +} // namespace arm_compute |