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/*
* 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 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<int>::lowest() : std::numeric_limits<int>::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<int>::max() : std::numeric_limits<int>::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
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