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Diffstat (limited to 'libs/ARMComputeEx/src/core/CL/kernels/CLPadLayerKernel.cpp')
| -rw-r--r-- | libs/ARMComputeEx/src/core/CL/kernels/CLPadLayerKernel.cpp | 149 |
1 files changed, 149 insertions, 0 deletions
diff --git a/libs/ARMComputeEx/src/core/CL/kernels/CLPadLayerKernel.cpp b/libs/ARMComputeEx/src/core/CL/kernels/CLPadLayerKernel.cpp new file mode 100644 index 000000000..99b54c822 --- /dev/null +++ b/libs/ARMComputeEx/src/core/CL/kernels/CLPadLayerKernel.cpp @@ -0,0 +1,149 @@ +/* + * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved + * Copyright (c) 2016-2018 ARM Limited. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +#include "arm_compute/core/CL/kernels/CLPadLayerKernel.h" + +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/CLKernelLibraryEx.h" +#include "arm_compute/core/CL/ICLTensor.h" + +using namespace arm_compute; + +namespace +{ +Status validate_arguments(const ITensorInfo *input_info, const ITensorInfo *output_info, + const ITensorInfo *pad_size_info) +{ + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input_info, 1, DataType::U8, DataType::QASYMM8, + DataType::S16, DataType::S32, DataType::F16, + DataType::F32); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_info, 1, DataType::U8, DataType::QASYMM8, + DataType::S16, DataType::S32, DataType::F16, + DataType::F32); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(pad_size_info, 1, DataType::S32); + + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_info->num_dimensions() > 0 && + input_info->num_dimensions() <= 4, + "Pad kernel supports upto 4-D input tensor"); + + ARM_COMPUTE_RETURN_ERROR_ON_MSG( + input_info->num_dimensions() == output_info->num_dimensions(), + "output tensor should have same number of dimensions as input tensor"); + + if (input_info->data_type() == DataType::QASYMM8) + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_info->quantization_info() != + output_info->quantization_info(), + "The input and output quantization info are different!"); + } + + return Status{}; +} + +} // namespace + +CLPadLayerKernel::CLPadLayerKernel() : _input(nullptr), _output(nullptr), _pad_size(nullptr) {} + +void CLPadLayerKernel::configure(const ICLTensor *input, ICLTensor *output, ICLTensor *pad_size) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, pad_size); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), pad_size->info())); + + _input = input; + _output = output; + _pad_size = pad_size; + + // Set kernel build options + std::set<std::string> build_opts; + build_opts.emplace("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); + build_opts.emplace("-DDEPTH_OUT=" + support::cpp11::to_string(output->info()->dimension(2))); + build_opts.emplace("-DIB=" + support::cpp11::to_string(input->info()->dimension(3))); + build_opts.emplace("-DIW=" + support::cpp11::to_string(input->info()->dimension(0))); + build_opts.emplace("-DIH=" + support::cpp11::to_string(input->info()->dimension(1))); + build_opts.emplace("-DID=" + support::cpp11::to_string(input->info()->dimension(2))); + if (input->info()->data_type() == DataType::QASYMM8) + { + build_opts.emplace("-DZERO_VALUE=" + + support::cpp11::to_string(input->info()->quantization_info().offset)); + } + else + { + build_opts.emplace("-DZERO_VALUE=" + support::cpp11::to_string(0)); + } + + // Create kernel + _kernel = static_cast<cl::Kernel>(CLKernelLibraryEx::get().create_kernel("pad", build_opts)); + + // Configure kernel window + Window win = calculate_max_window(*output->info(), Steps()); + + Coordinates coord; + coord.set_num_dimensions(output->info()->num_dimensions()); + output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape())); + + ICLKernel::configure_internal(win); +} + +void CLPadLayerKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(ICLKernel::window(), window); + + _pad_size->map(queue); + + // Padding values only for up, top, left and front are required based on the rank of tensor + int rank = _pad_size->info()->dimension(1); + + auto pad_batch_up = + (rank == 4) ? *reinterpret_cast<const int32_t *>(_pad_size->ptr_to_element({0, 0})) : 0; + auto pad_height_top = + (rank >= 2) + ? *reinterpret_cast<const int32_t *>(_pad_size->ptr_to_element({0, (rank == 2) ? 0 : 1})) + : 0; + auto pad_width_left = (rank >= 1) + ? *reinterpret_cast<const int32_t *>( + _pad_size->ptr_to_element({0, (rank == 4) ? 2 : rank - 1})) + : 0; + auto pad_depth_front = + (rank >= 3) + ? *reinterpret_cast<const int32_t *>(_pad_size->ptr_to_element({0, (rank == 3) ? 0 : 3})) + : 0; + + _pad_size->unmap(queue); + + // Pad_values which needs to be passed + const cl_int4 paddingValues = { + {static_cast<cl_int>(pad_width_left), static_cast<cl_int>(pad_height_top), + static_cast<cl_int>(pad_depth_front), static_cast<cl_int>(pad_batch_up)}}; + + Window slice_out = window.first_slice_window_4D().collapse(ICLKernel::window(), 2, 4); + + // Setup output slice + Window slice_in(slice_out); + slice_in.set(Window::DimX, Window::Dimension(0, 0, 0)); + slice_in.set(Window::DimY, Window::Dimension(0, 0, 0)); + slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0)); + slice_in.set(3, Window::Dimension(0, 0, 0)); + + do + { + unsigned int idx = 0; + add_4D_tensor_argument(idx, _input, slice_in); + add_4D_tensor_argument(idx, _output, slice_out); + _kernel.setArg<cl_int4>(idx++, paddingValues); + enqueue(queue, *this, slice_out); + } while (window.slide_window_slice_4D(slice_out) && window.slide_window_slice_4D(slice_in)); +} |