blob: a399229013ef2156edae715b0dcf46bfa6a0fca7 [file] [log] [blame]
/*
* Copyright (c) 2018-2019 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/graph/nodes/ResizeLayerNode.h"
#include "arm_compute/graph/Graph.h"
#include "arm_compute/graph/INodeVisitor.h"
#include "arm_compute/graph/Utils.h"
namespace arm_compute
{
namespace graph
{
ResizeLayerNode::ResizeLayerNode(InterpolationPolicy policy, float scale_width, float scale_height)
: _policy(policy), _scale_width(scale_width), _scale_height(scale_height)
{
_input_edges.resize(1, EmptyEdgeID);
_outputs.resize(1, NullTensorID);
}
InterpolationPolicy ResizeLayerNode::policy() const
{
return _policy;
}
std::pair<float, float> ResizeLayerNode::scaling_factor() const
{
return std::make_pair(_scale_width, _scale_height);
}
bool ResizeLayerNode::forward_descriptors()
{
if((input_id(0) != NullTensorID) && (output_id(0) != NullTensorID))
{
Tensor *dst = output(0);
ARM_COMPUTE_ERROR_ON(dst == nullptr);
dst->desc() = configure_output(0);
return true;
}
return false;
}
TensorDescriptor ResizeLayerNode::configure_output(size_t idx) const
{
ARM_COMPUTE_UNUSED(idx);
ARM_COMPUTE_ERROR_ON(idx >= _outputs.size());
const Tensor *src = input(0);
ARM_COMPUTE_ERROR_ON(src == nullptr);
const DataLayout data_layout = src->desc().layout;
TensorDescriptor output_desc = src->desc();
size_t width_idx = get_dimension_idx(data_layout, DataLayoutDimension::WIDTH);
size_t height_idx = get_dimension_idx(data_layout, DataLayoutDimension::HEIGHT);
output_desc.shape.set(width_idx, static_cast<int>(output_desc.shape[width_idx] * _scale_width));
output_desc.shape.set(height_idx, static_cast<int>(output_desc.shape[height_idx] * _scale_height));
return output_desc;
}
NodeType ResizeLayerNode::type() const
{
return NodeType::ResizeLayer;
}
void ResizeLayerNode::accept(INodeVisitor &v)
{
v.visit(*this);
}
} // namespace graph
} // namespace arm_compute