From 284cfe2e3a44e5b20978e561c96c94d2193e93a1 Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Tue, 13 Feb 2018 12:15:13 +0000 Subject: COMPMID-903: Implements NEPermute for NHWC conversions Change-Id: I4083e8d16bb23933634f229a1408dfd0e8f2922a Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/120069 Tested-by: Jenkins Reviewed-by: Anthony Barbier --- src/core/NEON/kernels/NEPermuteKernel.cpp | 215 ++++++++++++++++++++++++++++++ 1 file changed, 215 insertions(+) create mode 100644 src/core/NEON/kernels/NEPermuteKernel.cpp (limited to 'src/core/NEON/kernels/NEPermuteKernel.cpp') diff --git a/src/core/NEON/kernels/NEPermuteKernel.cpp b/src/core/NEON/kernels/NEPermuteKernel.cpp new file mode 100644 index 0000000000..f5f276f1cc --- /dev/null +++ b/src/core/NEON/kernels/NEPermuteKernel.cpp @@ -0,0 +1,215 @@ +/* + * Copyright (c) 2018 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/NEON/kernels/NEPermuteKernel.h" + +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/ITensor.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" + +namespace +{ +#include "arm_compute/core/NEON/kernels/convolution/common/shims.hpp" +} // namespace + +#include +#include + +using namespace arm_compute; + +namespace +{ +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const PermutationVector &perm) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S8, DataType::QS8, DataType::QASYMM8, + DataType::U16, DataType::S16, DataType::QS16, + DataType::U32, DataType::S32, + DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_dimensions() < 3, "Invalid input size!"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG( + (perm.num_dimensions() != 3 && ((perm[0] != 2 && perm[1] != 0 && perm[2] != 1) || (perm[0] != 1 && perm[1] != 2 && perm[2] != 0))), + "Only [2, 0, 1] and [1, 2, 0] permutation is supported"); + + const TensorShape output_shape = misc::shape_calculator::compute_permutation_output_shape(*input, perm); + + // Validate configured output + if(output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); + } + + return Status{}; +} +} // namespace + +template +void NEPermuteKernel::run_permute(const Window &window) +{ + // Input window + Window window_in = window; + window_in.set(Window::DimX, Window::Dimension(window.x().start(), window.x().end(), window.x().end() - window.x().start())); + window_in.set(Window::DimY, Window::Dimension(window.y().start(), window.y().end(), window.y().end() - window.y().start())); + window_in.set(Window::DimZ, Window::Dimension(window.z().start(), window.z().end(), window.z().end() - window.z().start())); + window_in.set(3, Window::Dimension(window[3].start(), window[3].end(), window[3].end() - window[3].start())); + + // Output window + Window window_out(window); + const Window::Dimension zero_window = Window::Dimension(0, 0, 0); + for(size_t d = 0; d <= _perm.num_dimensions(); ++d) + { + window_out.set(d, zero_window); + } + + // Create iterators + Iterator in(_input, window_in); + Iterator out(_output, window_out); + + // CHW -> HWC + if((_perm.num_dimensions() == 3) && (_perm[0] == 2) && (_perm[1] == 0) && (_perm[2] == 1)) + { + const int in_row_stride = _input->info()->strides_in_bytes().y() / sizeof(T); + const int in_channel_stride = _input->info()->strides_in_bytes().z() / sizeof(T); + const int in_batch_stride = _input->info()->strides_in_bytes()[3] / sizeof(T); + + const int out_channel_stride = _output->info()->strides_in_bytes().x() / sizeof(T); + const int out_col_stride = _output->info()->strides_in_bytes().y() / sizeof(T); + const int out_row_stride = _output->info()->strides_in_bytes().z() / sizeof(T); + const int out_batch_stride = _output->info()->strides_in_bytes()[3] / sizeof(T); + + const int n_cols = _input->info()->tensor_shape().x(); + const int n_rows = window_in.y().step(); + const int n_channels = _input->info()->tensor_shape().z(); + const int n_batches = _input->info()->tensor_shape()[3]; + + execute_window_loop(window_in, [&](const Coordinates & id) + { + const int idx = id[0] * out_col_stride + id[1] * out_row_stride + id[2] * out_channel_stride; + reorder::nchw_to_nhwc(reinterpret_cast(in.ptr()), reinterpret_cast(out.ptr()) + idx, + n_batches, n_channels, n_rows, n_cols, + in_batch_stride, in_channel_stride, in_row_stride, + out_batch_stride, out_row_stride, out_col_stride); + }, + in, out); + } + // HWC -> CHW + else if((_perm.num_dimensions() == 3) && (_perm[0] == 1) && (_perm[1] == 2) && (_perm[2] == 0)) + { + const int in_col_stride = _input->info()->strides_in_bytes().y() / sizeof(T); + const int in_row_stride = _input->info()->strides_in_bytes().z() / sizeof(T); + const int in_batch_stride = _input->info()->strides_in_bytes()[3] / sizeof(T); + + const int out_col_stride = _output->info()->strides_in_bytes().x() / sizeof(T); + const int out_row_stride = _output->info()->strides_in_bytes().y() / sizeof(T); + const int out_channel_stride = _output->info()->strides_in_bytes().z() / sizeof(T); + const int out_batch_stride = _output->info()->strides_in_bytes()[3] / sizeof(T); + + const int n_channels = _input->info()->tensor_shape().x(); + const int n_cols = window_in.y().step(); + const int n_rows = _input->info()->tensor_shape().z(); + const int n_batches = _input->info()->tensor_shape()[3]; + + execute_window_loop(window_in, [&](const Coordinates & id) + { + const int idx = id[0] * out_channel_stride + id[1] * out_col_stride + id[2] * out_row_stride; + reorder::nhwc_to_nchw(reinterpret_cast(in.ptr()), reinterpret_cast(out.ptr()) + idx, + n_batches, n_rows, n_cols, n_channels, + in_batch_stride, in_row_stride, in_col_stride, + out_batch_stride, out_channel_stride, out_row_stride); + }, + in, out); + } + else + { + ARM_COMPUTE_ERROR("Unsupported permutation vector"); + } +} + +NEPermuteKernel::NEPermuteKernel() + : _func(), _input(nullptr), _output(nullptr), _perm() +{ +} + +void NEPermuteKernel::configure(const ITensor *input, ITensor *output, const PermutationVector &perm) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + const TensorShape output_shape = misc::shape_calculator::compute_permutation_output_shape(*input->info(), perm); + // Output auto inizialitation if not yet initialized + auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape)); + + // Perform validation step + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), perm)); + + _input = input; + _output = output; + _perm = perm; + + switch(input->info()->element_size()) + { + case 1: + _func = &NEPermuteKernel::run_permute; + break; + case 2: + _func = &NEPermuteKernel::run_permute; + break; + case 4: + _func = &NEPermuteKernel::run_permute; + break; + default: + ARM_COMPUTE_ERROR("Element size not supported"); + break; + } + + // Configure kernel window + Window win = calculate_max_window(*input->info(), Steps()); + + // The NEPermute doesn't need padding so update_window_and_padding() can be skipped + Coordinates coord; + coord.set_num_dimensions(output->info()->num_dimensions()); + output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape())); + + ICPPKernel::configure(win); +} + +Status NEPermuteKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const PermutationVector &perm) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, perm)); + return Status{}; +} + +void NEPermuteKernel::run(const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICPPKernel::window(), window); + + if(_func != nullptr) + { + (this->*_func)(window); + } +} -- cgit v1.2.1