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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/graph2/nodes/DepthwiseConvolutionLayerNode.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/graph2/Graph.h"
#include "arm_compute/graph2/INodeVisitor.h"
namespace arm_compute
{
namespace graph2
{
DepthwiseConvolutionLayerNode::DepthwiseConvolutionLayerNode(PadStrideInfo info, DepthwiseConvolutionMethod method)
: _info(std::move(info)), _method(method)
{
_input_edges.resize(3, EmptyEdgeID);
_outputs.resize(1, NullTensorID);
}
void DepthwiseConvolutionLayerNode::set_depthwise_convolution_method(DepthwiseConvolutionMethod method)
{
_method = method;
}
DepthwiseConvolutionMethod DepthwiseConvolutionLayerNode::depthwise_convolution_method() const
{
return _method;
}
PadStrideInfo DepthwiseConvolutionLayerNode::convolution_info() const
{
return _info;
}
TensorShape DepthwiseConvolutionLayerNode::compute_output_shape(TensorShape input_shape, TensorShape weights_shape, PadStrideInfo info)
{
unsigned int output_width = 0;
unsigned int output_height = 0;
std::tie(output_width, output_height) = scaled_dimensions(input_shape.x(), input_shape.y(), weights_shape.x(), weights_shape.y(), info);
TensorShape output_shape{ input_shape };
output_shape.set(0, output_width);
output_shape.set(1, output_height);
return output_shape;
}
bool DepthwiseConvolutionLayerNode::forward_descriptors()
{
if((input_id(0) != NullTensorID) && (input_id(1) != 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 DepthwiseConvolutionLayerNode::configure_output(size_t idx) const
{
ARM_COMPUTE_UNUSED(idx);
const Tensor *src = input(0);
const Tensor *weights = input(1);
ARM_COMPUTE_ERROR_ON(src == nullptr || weights == nullptr);
TensorDescriptor output_info = src->desc();
TensorShape output_shape = compute_output_shape(src->desc().shape, weights->desc().shape, _info);
output_info.shape = output_shape;
return output_info;
}
Status DepthwiseConvolutionLayerNode::validate()
{
return Status{};
}
NodeType DepthwiseConvolutionLayerNode::type() const
{
return NodeType::DepthwiseConvolutionLayer;
}
void DepthwiseConvolutionLayerNode::accept(INodeVisitor &v)
{
v.visit(*this);
}
} // namespace graph2
} // namespace arm_compute
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