| /* |
| * Copyright (c) 2018-2021 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/cpu/kernels/CpuPermuteKernel.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/utils/misc/ShapeCalculator.h" |
| #include "arm_compute/core/Validate.h" |
| |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| |
| namespace |
| { |
| #include "src/core/NEON/kernels/convolution/common/shims.hpp" |
| } // namespace |
| |
| namespace arm_compute |
| { |
| namespace cpu |
| { |
| namespace kernels |
| { |
| namespace |
| { |
| inline bool is_permutation_supported(const PermutationVector &v) |
| { |
| static const std::array<PermutationVector, 2> permutations2 = {{ |
| PermutationVector(0U, 1U), |
| PermutationVector(1U, 0U), |
| }}; |
| static const std::array<PermutationVector, 6> permutations3 = {{ |
| PermutationVector(2U, 0U, 1U), |
| PermutationVector(1U, 2U, 0U), |
| PermutationVector(0U, 1U, 2U), |
| PermutationVector(0U, 2U, 1U), |
| PermutationVector(1U, 0U, 2U), |
| PermutationVector(2U, 1U, 0U), |
| }}; |
| static const std::array<PermutationVector, 24> permutations4 = { |
| {PermutationVector(0U, 1U, 2U, 3U), PermutationVector(1U, 0U, 2U, 3U), PermutationVector(2U, 0U, 1U, 3U), |
| PermutationVector(0U, 2U, 1U, 3U), PermutationVector(1U, 2U, 0U, 3U), PermutationVector(2U, 1U, 0U, 3U), |
| PermutationVector(2U, 1U, 3U, 0U), PermutationVector(1U, 2U, 3U, 0U), PermutationVector(3U, 2U, 1U, 0U), |
| PermutationVector(2U, 3U, 1U, 0U), PermutationVector(1U, 3U, 2U, 0U), PermutationVector(3U, 1U, 2U, 0U), |
| PermutationVector(3U, 0U, 2U, 1U), PermutationVector(0U, 3U, 2U, 1U), PermutationVector(2U, 3U, 0U, 1U), |
| PermutationVector(3U, 2U, 0U, 1U), PermutationVector(0U, 2U, 3U, 1U), PermutationVector(2U, 0U, 3U, 1U), |
| PermutationVector(1U, 0U, 3U, 2U), PermutationVector(0U, 1U, 3U, 2U), PermutationVector(3U, 1U, 0U, 2U), |
| PermutationVector(1U, 3U, 0U, 2U), PermutationVector(0U, 3U, 1U, 2U), PermutationVector(3U, 0U, 1U, 2U)}}; |
| |
| return (permutations2.end() != std::find(permutations2.begin(), permutations2.end(), v)) || |
| (permutations3.end() != std::find(permutations3.begin(), permutations3.end(), v)) || |
| (permutations4.end() != std::find(permutations4.begin(), permutations4.end(), v)); |
| } |
| |
| Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst, const PermutationVector &perm) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON(src->data_type() == DataType::UNKNOWN); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(!is_permutation_supported(perm), "PermutationVector not supported."); |
| |
| const TensorShape dst_shape = misc::shape_calculator::compute_permutation_output_shape(*src, perm); |
| |
| // Validate configured destination |
| if (dst->total_size() != 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(dst->tensor_shape(), dst_shape); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(src, dst); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst); |
| } |
| |
| return Status{}; |
| } |
| |
| template <typename T> |
| void run_permute(const Window &window, const ITensor *src, const ITensor *dst, const PermutationVector &perm) |
| { |
| const DataLayout src_layout = src->info()->data_layout(); |
| |
| // Source window |
| Window window_src = window; |
| |
| // we only support these two configs in src/core/NEON/kernels/convolution/common/shims.hpp, for all others |
| // we have to fall back to C++ |
| if ((src_layout == DataLayout::NCHW && perm == PermutationVector{2U, 0U, 1U}) || |
| (src_layout == DataLayout::NHWC && perm == PermutationVector{1U, 2U, 0U})) |
| { |
| window_src.set(Window::DimX, |
| Window::Dimension(window.x().start(), window.x().end(), window.x().end() - window.x().start())); |
| window_src.set(Window::DimY, |
| Window::Dimension(window.y().start(), window.y().end(), window.y().end() - window.y().start())); |
| window_src.set(Window::DimZ, |
| Window::Dimension(window.z().start(), window.z().end(), window.z().end() - window.z().start())); |
| window_src.set(3, Window::Dimension(window[3].start(), window[3].end(), window[3].end() - window[3].start())); |
| } |
| |
| // Destination window |
| Window window_dst(window); |
| const Window::Dimension zero_window = Window::Dimension(0, 0, 0); |
| for (size_t d = 0; d <= dst->info()->num_dimensions(); ++d) |
| { |
| window_dst.set(d, zero_window); |
| } |
| |
| // Create iterators |
| Iterator src_it(src, window_src); |
| Iterator dst_it(dst, window_dst); |
| |
| int in_row_stride = 0; |
| int in_col_stride = 0; |
| int in_channel_stride = 0; |
| int in_batch_stride = 0; |
| int n_cols = 0; |
| int n_rows = 0; |
| int n_channels = 0; |
| int n_batches = 0; |
| |
| switch (src_layout) |
| { |
| case DataLayout::NCHW: |
| { |
| in_row_stride = src->info()->strides_in_bytes().y() / sizeof(T); |
| in_channel_stride = src->info()->strides_in_bytes().z() / sizeof(T); |
| in_batch_stride = src->info()->strides_in_bytes()[3] / sizeof(T); |
| n_cols = src->info()->tensor_shape().x(); |
| n_rows = window_src.y().step(); |
| n_channels = src->info()->tensor_shape().z(); |
| n_batches = src->info()->tensor_shape()[3]; |
| break; |
| } |
| case DataLayout::NHWC: |
| { |
| in_col_stride = src->info()->strides_in_bytes().y() / sizeof(T); |
| in_row_stride = src->info()->strides_in_bytes().z() / sizeof(T); |
| in_batch_stride = src->info()->strides_in_bytes()[3] / sizeof(T); |
| n_channels = src->info()->tensor_shape().x(); |
| n_cols = window_src.y().step(); |
| n_rows = src->info()->tensor_shape().z(); |
| n_batches = src->info()->tensor_shape()[3]; |
| break; |
| } |
| default: |
| { |
| ARM_COMPUTE_ERROR("Invalid source data layout."); |
| break; |
| } |
| } |
| |
| // CHW -> HWC |
| if (src_layout == DataLayout::NCHW && perm == PermutationVector{2U, 0U, 1U}) |
| { |
| const int out_channel_stride = dst->info()->strides_in_bytes().x() / sizeof(T); |
| const int out_col_stride = dst->info()->strides_in_bytes().y() / sizeof(T); |
| const int out_row_stride = dst->info()->strides_in_bytes().z() / sizeof(T); |
| const int out_batch_stride = dst->info()->strides_in_bytes()[3] / sizeof(T); |
| execute_window_loop( |
| window_src, |
| [&](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<const T *>(src_it.ptr()), |
| reinterpret_cast<T *>(dst_it.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); |
| }, |
| src_it, dst_it); |
| } |
| // HWC -> CHW |
| else if (src_layout == DataLayout::NHWC && perm == PermutationVector{1U, 2U, 0U}) |
| { |
| const int out_col_stride = dst->info()->strides_in_bytes().x() / sizeof(T); |
| const int out_row_stride = dst->info()->strides_in_bytes().y() / sizeof(T); |
| const int out_channel_stride = dst->info()->strides_in_bytes().z() / sizeof(T); |
| const int out_batch_stride = dst->info()->strides_in_bytes()[3] / sizeof(T); |
| execute_window_loop( |
| window_src, |
| [&](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<const T *>(src_it.ptr()), |
| reinterpret_cast<T *>(dst_it.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); |
| }, |
| src_it, dst_it); |
| } |
| else |
| { |
| // All other cases fall back to C++ |
| // Permute strides |
| Strides strides = dst->info()->strides_in_bytes(); |
| Strides perm_strides = strides; |
| permute_strides(perm_strides, perm); |
| const int perm_stride_3 = src->info()->num_dimensions() >= 4 ? perm_strides[3] : 0; |
| execute_window_loop( |
| window, |
| [&](const Coordinates &id) |
| { |
| const int idx = |
| id[0] * perm_strides[0] + id[1] * perm_strides[1] + id[2] * perm_strides[2] + id[3] * perm_stride_3; |
| *(reinterpret_cast<T *>(dst_it.ptr() + idx)) = *(reinterpret_cast<const T *>(src_it.ptr())); |
| }, |
| src_it, dst_it); |
| } |
| } |
| } // namespace |
| |
| void CpuPermuteKernel::configure(const ITensorInfo *src, ITensorInfo *dst, const PermutationVector &perm) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); |
| const TensorShape dst_shape = misc::shape_calculator::compute_permutation_output_shape(*src, perm); |
| // Destination auto inizialitation if not yet initialized |
| auto_init_if_empty(*dst, src->clone()->set_tensor_shape(dst_shape)); |
| |
| // Perform validation step |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, perm)); |
| |
| _perm = perm; |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*src, Steps()); |
| |
| // This kernel doesn't need padding so update_window_and_padding() can be skipped |
| |
| ICpuKernel::configure(win); |
| } |
| |
| Status CpuPermuteKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const PermutationVector &perm) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, dst, perm)); |
| return Status{}; |
| } |
| |
| void CpuPermuteKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) |
| { |
| ARM_COMPUTE_UNUSED(info); |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window); |
| |
| const auto src = tensors.get_const_tensor(TensorType::ACL_SRC); |
| auto dst = tensors.get_tensor(TensorType::ACL_DST); |
| |
| switch (src->info()->element_size()) |
| { |
| case 1: |
| run_permute<uint8_t>(window, src, dst, _perm); |
| break; |
| case 2: |
| run_permute<uint16_t>(window, src, dst, _perm); |
| break; |
| case 4: |
| run_permute<uint32_t>(window, src, dst, _perm); |
| break; |
| default: |
| ARM_COMPUTE_ERROR("Element size not supported"); |
| break; |
| } |
| } |
| |
| const char *CpuPermuteKernel::name() const |
| { |
| return "CpuPermuteKernel"; |
| } |
| } // namespace kernels |
| } // namespace cpu |
| } // namespace arm_compute |