/* * 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/utils/helpers/tensor_transform.h" namespace arm_compute { namespace helpers { namespace tensor_transform { Coordinates slice_absolute_end_coords(TensorShape input_shape, Coordinates ends) { // Create end mask int32_t end_mask = 0; for(unsigned int i = 0; i < ends.num_dimensions(); ++i) { if(ends[i] < 0) { end_mask |= 1 << i; } } // Get unit strides const BiStrides unit_strides = strided_slice_strides(input_shape, BiStrides()); return strided_slice_absolute_end_coords(input_shape, Coordinates(), ends, unit_strides, end_mask); } TensorShape compute_slice_output_shape(TensorShape input_shape, Coordinates starts, Coordinates ends_abs) { // Get unit strides const BiStrides unit_strides = strided_slice_strides(input_shape, BiStrides()); return compute_strided_slice_output_shape(input_shape, starts, ends_abs, unit_strides); } Coordinates strided_slice_absolute_start_coords(TensorShape input_shape, Coordinates starts, Coordinates strides, int32_t begin_mask) { Coordinates starts_abs; for(unsigned int i = 0; i < starts.num_dimensions(); ++i) { // Get start index int start_i = starts[i]; // Reset in case of begin mask present if((begin_mask & 1 << i) != 0) { start_i = strides[i] > 0 ? std::numeric_limits::lowest() : std::numeric_limits::max(); } // Account negative start points const int dim_size = input_shape[i]; if(start_i < 0) { start_i += dim_size; } // Final clamp start_i = utility::clamp(start_i, 0, dim_size - 1); starts_abs.set(i, start_i); } // Fill remaining for(unsigned int i = starts_abs.num_dimensions(); i < input_shape.num_dimensions(); ++i) { starts_abs.set(i, 0); } return starts_abs; } Coordinates strided_slice_absolute_end_coords(TensorShape input_shape, Coordinates starts_abs, Coordinates ends, Coordinates strides, int32_t end_mask, int32_t shrink_axis_mask) { Coordinates ends_abs; for(unsigned int i = 0; i < ends.num_dimensions(); ++i) { // Get end index int stop_i = ends[i]; // Shrink dimension if((shrink_axis_mask & (1 << i)) != 0) { stop_i = starts_abs[i] + 1; } // Reset in case of begin mask present if((end_mask & 1 << i) != 0) { stop_i = (strides[i] > 0) ? std::numeric_limits::max() : std::numeric_limits::lowest(); } // Account negative end points const int dim_size = input_shape[i]; if(stop_i < 0) { stop_i += dim_size; } // Final clamp stop_i = (strides[i] > 0) ? utility::clamp(stop_i, 0, dim_size) : utility::clamp(stop_i, -1, dim_size - 1); ends_abs.set(i, stop_i); } // Fill remaining ends for(unsigned int i = ends_abs.num_dimensions(); i < input_shape.num_dimensions(); ++i) { ends_abs.set(i, input_shape[i]); } return ends_abs; } Coordinates strided_slice_strides(TensorShape input_shape, Coordinates strides) { for(unsigned int i = strides.num_dimensions(); i < input_shape.num_dimensions(); ++i) { strides.set(i, 1); } return strides; } TensorShape compute_strided_slice_output_shape(TensorShape input_shape, Coordinates starts_abs, Coordinates ends_abs, Coordinates final_strides) { TensorShape output_shape = input_shape; for(unsigned int i = 0; i < input_shape.num_dimensions(); ++i) { const int stride_i = final_strides[i]; const int range = ends_abs[i] - starts_abs[i]; if((range == 0) || // Zero range (range < 0 && stride_i >= 0) || // Negative range with positive stride (range > 0 && stride_i <= 0)) // Positive range with negative stride { output_shape.set(i, 0); return output_shape; } else { int dim = range / stride_i + (range % stride_i != 0 ? 1 : 0); output_shape.set(i, dim); } } return output_shape; } } // namespace tensor_transform } // namespace helpers } // namespace arm_compute