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Diffstat (limited to 'src/core/AccessWindowTranspose.cpp')
| -rw-r--r-- | src/core/AccessWindowTranspose.cpp | 209 |
1 files changed, 209 insertions, 0 deletions
diff --git a/src/core/AccessWindowTranspose.cpp b/src/core/AccessWindowTranspose.cpp new file mode 100644 index 0000000000..b3605c43f7 --- /dev/null +++ b/src/core/AccessWindowTranspose.cpp @@ -0,0 +1,209 @@ +/* + * Copyright (c) 2017 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/AccessWindowTranspose.h" + +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/ITensorInfo.h" +#include "arm_compute/core/Window.h" + +using namespace arm_compute; + +ValidRegion AccessWindowTranspose::compute_valid_region(const Window &window, ValidRegion input_valid_region, bool border_undefined, BorderSize border_size) const +{ + if(_info == nullptr) + { + return input_valid_region; + } + + Coordinates &anchor = input_valid_region.anchor; + TensorShape &shape = input_valid_region.shape; + Coordinates old_anchor(anchor); + TensorShape old_shape(shape); + + if(!border_undefined) + { + border_size = BorderSize(0); + } + + // Start of the valid region is equal to the start of the window. But it + // cannot be less than the start of the input's valid region plus the border + // size required by this kernel (if undefined). + // Additionally the valid region is shifted by the offset that is used by + // the kernel to write back output values. + // As the relation between input and output is transposed window.y() is + // used for x anchor and window.x() for y anchor. + anchor.set(0, std::max<int>(window.y().start() * _scale_x, anchor[1] + border_size.top) + _x); + anchor.set(1, std::max<int>(window.x().start() * _scale_y, anchor[0] + border_size.left) + _y); + + // End of the valid region is equal to the start of the last write of the + // kernel plus the number of written elements. (This assumes that all + // written elements are valid). Nevertheless the end cannot be larger than + // the end of the input's valid region minus the border size. + // Note: not the end points of the region are stored but its size. Thus the + // old size is first converted into end points to compared against the + // execution window. Afterwards the new end points are converted back into + // a size of the region. + // As the relation between input and output is transposed window.y() is + // used for x shape and window.x() for y shape. + shape.set(0, std::min<int>(old_anchor[1] + old_shape[1] - border_size.right, (window.y().end() - window.y().step()) * _scale_x + _width) - anchor[0]); + shape.set(1, std::min<int>(old_anchor[0] + old_shape[0] - border_size.bottom, (window.x().end() - window.x().step()) * _scale_y + _height) - anchor[1]); + + // For higher dimensions use the intersection of the window size and the + // valid region of the input + for(size_t d = 2; d < _info->num_dimensions(); ++d) + { + anchor.set(d, std::max(window[d].start(), input_valid_region.anchor[d])); + shape.set(d, std::min<int>(window[d].end(), input_valid_region.shape[d]) - anchor[d]); + } + + return input_valid_region; +} + +bool AccessWindowTranspose::update_window_if_needed(Window &window) const +{ + // Only update the window size if we can't use padding + if(_info == nullptr || _info->is_resizable()) + { + return false; + } + + const TensorShape &shape = _info->tensor_shape(); + const Strides &strides = _info->strides_in_bytes(); + const size_t offset_first_element = _info->offset_first_element_in_bytes(); + + bool window_modified = false; + + int front_pad_y = 0; + + // Transpose and scale + const int min_y = window.x().start() * _scale_y + _y; + const int max_y = window.x().end() * _scale_y + _y; + + // Adjust window start for output's Y dimension (so X in (input) window) + if(min_y < 0) + { + // Calculate rows available above the tensor + const int front_pad_y_available = -offset_first_element / strides[1]; + + if(min_y < front_pad_y_available) + { + // Not enough padding available, need to shrink the window + const int start = adjust_up(min_y, front_pad_y_available, window.x().step() * _scale_y) - _y; + + window.set(0, Window::Dimension(start / _scale_y, window.x().end(), window.x().step())); + window_modified = true; + } + + // Update front padding with reconstructed value + front_pad_y = std::max(0, static_cast<int>(std::floor(-window.x().start() * _scale_y)) - _y); + } + + // Adjust window end for Y dimension + if(max_y > static_cast<int>(shape[1])) + { + const int stride_z = _info->num_dimensions() > 2 ? strides[2] : _info->total_size(); + + // Calculate rows available below the tensor + const int tail_pad_y_available = (stride_z / strides[1]) - shape[1] - front_pad_y; + + if(static_cast<int>(shape[1]) + tail_pad_y_available < max_y) + { + // Not enough padding available, need to shrink the window + const int end = adjust_down(max_y, shape[1] + tail_pad_y_available, window.x().step() * _scale_y) + window.x().step() * _scale_y - _y - _height; + window.set(0, Window::Dimension(window.x().start(), end / _scale_y, window.x().step())); + window_modified = true; + } + } + + int front_pad_x = 0; + + // Transpose and scale + const int min_x = window.y().start() * _scale_x + _x; + const int max_x = window.y().end() * _scale_x + _x; + + const int stride_y = _info->num_dimensions() > 1 ? strides[1] : _info->total_size(); + + // Adjust window start for X dimension + if(min_x < 0) + { + const int front_pad_x_available = -std::min<int>(static_cast<int>(offset_first_element) - front_pad_y * strides[1], stride_y - shape[0] * strides[0]) / static_cast<int>(strides[0]); + + if(min_x < front_pad_x_available) + { + // Not enough padding available, need to shrink the window + const int start = adjust_up(min_x, front_pad_x_available, window.y().step() * _scale_x) - _x; + window.set(1, Window::Dimension(start / _scale_x, window.y().end(), window.y().step())); + window_modified = true; + } + + // Update front padding with reconstructed value + front_pad_x = std::max(0, static_cast<int>(std::floor(-window.y().start() * _scale_x)) - _x); + } + + // Adjust window end for X dimension + if(max_x > static_cast<int>(shape[0])) + { + const int tail_pad_x_available = (stride_y / strides[0]) - shape[0] - front_pad_x; + + if(static_cast<int>(shape[0]) + tail_pad_x_available < max_x) + { + // Not enough padding available, need to shrink the window + const int end = adjust_down(max_x, shape[0] + tail_pad_x_available, window.y().step() * _scale_x) + window.y().step() * _scale_x - _x - _width; + window.set(1, Window::Dimension(window.y().start(), end / _scale_x, window.y().step())); + window_modified = true; + } + } + + window.validate(); + + return window_modified; +} + +bool AccessWindowTranspose::update_padding_if_needed(const Window &window) const +{ + // Only update the padding if the tensor allows it + if(_info == nullptr || !_info->is_resizable()) + { + return false; + } + + ARM_COMPUTE_ERROR_ON(window.y().step() == 0); + ARM_COMPUTE_ERROR_ON(window.x().step() == 0); + + const int min_x = window.y().start() * _scale_x + _x; + const int max_x = window.y().end() * _scale_x + _x; + const int min_y = window.x().start() * _scale_y + _y; + const int max_y = window.x().end() * _scale_y + _y; + + const TensorShape &shape = _info->tensor_shape(); + + PaddingSize padding; + padding.left = std::max(0, -min_x); + padding.right = std::max<int>(0, max_x - shape[0]); + padding.top = shape.num_dimensions() == 1 ? 0 : std::max(0, -min_y); + padding.bottom = shape.num_dimensions() == 1 ? 0 : std::max<int>(0, max_y - shape[1]); + + // Update strides in tensor info + return _info->extend_padding(padding); +} |