| /* |
| * Copyright (c) 2016-2021 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 "arm_compute/core/Error.h" |
| |
| #include <cmath> |
| #include <numeric> |
| |
| namespace arm_compute |
| { |
| template <size_t dimension> |
| struct IncrementIterators |
| { |
| template <typename T, typename... Ts> |
| static void unroll(T &&it, Ts &&... iterators) |
| { |
| auto increment = [](T && it) |
| { |
| it.increment(dimension); |
| }; |
| utility::for_each(increment, std::forward<T>(it), std::forward<Ts>(iterators)...); |
| } |
| static void unroll() |
| { |
| // End of recursion |
| } |
| }; |
| |
| template <size_t dim> |
| struct ForEachDimension |
| { |
| template <typename L, typename... Ts> |
| static void unroll(const Window &w, Coordinates &id, L &&lambda_function, Ts &&... iterators) |
| { |
| const auto &d = w[dim - 1]; |
| |
| for(auto v = d.start(); v < d.end(); v += d.step(), IncrementIterators < dim - 1 >::unroll(iterators...)) |
| { |
| id.set(dim - 1, v); |
| ForEachDimension < dim - 1 >::unroll(w, id, lambda_function, iterators...); |
| } |
| } |
| }; |
| |
| template <> |
| struct ForEachDimension<0> |
| { |
| template <typename L, typename... Ts> |
| static void unroll(const Window &w, Coordinates &id, L &&lambda_function, Ts &&... iterators) |
| { |
| ARM_COMPUTE_UNUSED(w, iterators...); |
| lambda_function(id); |
| } |
| }; |
| |
| template <typename L, typename... Ts> |
| inline void execute_window_loop(const Window &w, L &&lambda_function, Ts &&... iterators) |
| { |
| w.validate(); |
| |
| for(unsigned int i = 0; i < Coordinates::num_max_dimensions; ++i) |
| { |
| ARM_COMPUTE_ERROR_ON(w[i].step() == 0); |
| } |
| |
| Coordinates id; |
| ForEachDimension<Coordinates::num_max_dimensions>::unroll(w, id, std::forward<L>(lambda_function), std::forward<Ts>(iterators)...); |
| } |
| |
| inline constexpr Iterator::Iterator() |
| : _ptr(nullptr), _dims() |
| { |
| } |
| |
| inline Iterator::Iterator(const ITensor *tensor, const Window &win) |
| : Iterator() |
| { |
| ARM_COMPUTE_ERROR_ON(tensor == nullptr); |
| ARM_COMPUTE_ERROR_ON(tensor->info() == nullptr); |
| |
| const ITensorInfo *info = tensor->info(); |
| const Strides &strides = info->strides_in_bytes(); |
| |
| _ptr = tensor->buffer() + info->offset_first_element_in_bytes(); |
| |
| //Initialize the stride for each dimension and calculate the position of the first element of the iteration: |
| for(unsigned int n = 0; n < info->num_dimensions(); ++n) |
| { |
| _dims[n]._stride = win[n].step() * strides[n]; |
| std::get<0>(_dims)._dim_start += static_cast<size_t>(strides[n]) * win[n].start(); |
| } |
| |
| //Copy the starting point to all the dimensions: |
| for(unsigned int n = 1; n < Coordinates::num_max_dimensions; ++n) |
| { |
| _dims[n]._dim_start = std::get<0>(_dims)._dim_start; |
| } |
| |
| ARM_COMPUTE_ERROR_ON_WINDOW_DIMENSIONS_GTE(win, info->num_dimensions()); |
| } |
| |
| inline void Iterator::increment(const size_t dimension) |
| { |
| ARM_COMPUTE_ERROR_ON(dimension >= Coordinates::num_max_dimensions); |
| |
| _dims[dimension]._dim_start += _dims[dimension]._stride; |
| |
| for(unsigned int n = 0; n < dimension; ++n) |
| { |
| _dims[n]._dim_start = _dims[dimension]._dim_start; |
| } |
| } |
| |
| inline constexpr size_t Iterator::offset() const |
| { |
| return _dims.at(0)._dim_start; |
| } |
| |
| inline constexpr uint8_t *Iterator::ptr() const |
| { |
| return _ptr + _dims.at(0)._dim_start; |
| } |
| |
| inline void Iterator::reset(const size_t dimension) |
| { |
| ARM_COMPUTE_ERROR_ON(dimension >= Coordinates::num_max_dimensions - 1); |
| |
| _dims[dimension]._dim_start = _dims[dimension + 1]._dim_start; |
| |
| for(unsigned int n = 0; n < dimension; ++n) |
| { |
| _dims[n]._dim_start = _dims[dimension]._dim_start; |
| } |
| } |
| |
| inline Coordinates index2coords(const TensorShape &shape, int index) |
| { |
| int num_elements = shape.total_size(); |
| |
| ARM_COMPUTE_ERROR_ON_MSG(index < 0 || index >= num_elements, "Index has to be in [0, num_elements]!"); |
| ARM_COMPUTE_ERROR_ON_MSG(num_elements == 0, "Cannot create coordinate from empty shape!"); |
| |
| Coordinates coord{ 0 }; |
| |
| for(int d = shape.num_dimensions() - 1; d >= 0; --d) |
| { |
| num_elements /= shape[d]; |
| coord.set(d, index / num_elements); |
| index %= num_elements; |
| } |
| |
| return coord; |
| } |
| |
| inline int coords2index(const TensorShape &shape, const Coordinates &coord) |
| { |
| int num_elements = shape.total_size(); |
| ARM_COMPUTE_UNUSED(num_elements); |
| ARM_COMPUTE_ERROR_ON_MSG(num_elements == 0, "Cannot create linear index from empty shape!"); |
| |
| int index = 0; |
| int stride = 1; |
| |
| for(unsigned int d = 0; d < coord.num_dimensions(); ++d) |
| { |
| index += coord[d] * stride; |
| stride *= shape[d]; |
| } |
| |
| return index; |
| } |
| |
| inline size_t get_data_layout_dimension_index(const DataLayout &data_layout, const DataLayoutDimension &data_layout_dimension) |
| { |
| ARM_COMPUTE_ERROR_ON_MSG(data_layout == DataLayout::UNKNOWN, "Cannot retrieve the dimension index for an unknown layout!"); |
| const auto &dims = get_layout_map().at(data_layout); |
| const auto &it = std::find(dims.cbegin(), dims.cend(), data_layout_dimension); |
| ARM_COMPUTE_ERROR_ON_MSG(it == dims.cend(), "Invalid dimension for the given layout."); |
| return it - dims.cbegin(); |
| } |
| |
| inline DataLayoutDimension get_index_data_layout_dimension(const DataLayout &data_layout, const size_t index) |
| { |
| ARM_COMPUTE_ERROR_ON_MSG(data_layout == DataLayout::UNKNOWN, "Cannot retrieve the layout dimension for an unknown layout!"); |
| const auto &dims = get_layout_map().at(data_layout); |
| ARM_COMPUTE_ERROR_ON_MSG(index >= dims.size(), "Invalid index for the given layout."); |
| return dims[index]; |
| } |
| } // namespace arm_compute |