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/*
* Copyright (c) 2021, 2023 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/DataLayerVisitor.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/graph/Graph.h"
#include "arm_compute/graph/nodes/Nodes.h"
#include "arm_compute/graph/TypePrinter.h"
namespace arm_compute
{
namespace graph
{
namespace
{
template <typename T>
void add_convolution_layer_data(DataLayerVisitor::LayerData &layer_data, T &node)
{
PadStrideInfo ps_info = node.convolution_info();
DataLayout layout = node.output(0)->desc().layout;
// Add data layout
layer_data["data_layout"] = to_string(layout);
// Add padding info
std::ostringstream padding;
padding << "[" << to_string(ps_info.pad_left()) << "," << to_string(ps_info.pad_top()) << ","
<< to_string(ps_info.pad_bottom()) << "," << to_string(ps_info.pad_right()) << "]";
layer_data["pad"] = padding.str();
// Add stride info
std::ostringstream stride;
stride << "[" << to_string(ps_info.stride().first) << "," << to_string(ps_info.stride().second) << "]";
layer_data["stride"] = stride.str();
// Add dilation info
// graph api does not support dilation > 1
layer_data["dilation"] = "[1,1]";
// Add bias enabled?
// Assumes three inputs (input, weights, bias)
std::string bias_enabled = node.input(2) == nullptr ? "0" : "1";
layer_data["bias_enabled"] = bias_enabled;
// Change input names for weights / bias (if applicable)
// Assumes input(1) is weights and input(2) is bias
if (layer_data.count("input_shape1"))
{
layer_data["weights_shape"] = layer_data["input_shape1"];
layer_data.erase("input_shape1");
}
if (layer_data.count("input_shape2"))
{
layer_data["bias_shape"] = layer_data["input_shape2"];
layer_data.erase("input_shape2");
}
}
template <typename T>
void add_convolution_layer_method(DataLayerVisitor::LayerData &layer_data, T &node)
{
std::ostringstream method;
method << node.convolution_method();
layer_data["convolution_method"] = method.str();
}
template <typename T>
void add_generic_layer_data(DataLayerVisitor::LayerData &layer_data, T &node)
{
// Loop over each input tensor
for (size_t tensor_no = 0; tensor_no < node.num_inputs(); ++tensor_no)
{
// Add input tensor shapes
if (node.input(tensor_no) != nullptr)
{
layer_data["input_shape" + to_string(tensor_no)] =
"[" + to_string(node.input(tensor_no)->desc().shape) + "]";
}
}
// Add output tensor shape
if (node.output(0) != nullptr)
{
layer_data["output_shape0"] = "[" + to_string(node.output(0)->desc().shape) + "]";
}
}
} // namespace
void DataLayerVisitor::visit(ConvolutionLayerNode &n)
{
_layer_data.clear();
add_generic_layer_data<ConvolutionLayerNode>(_layer_data, n);
add_convolution_layer_data<ConvolutionLayerNode>(_layer_data, n);
add_convolution_layer_method<ConvolutionLayerNode>(_layer_data, n);
}
void DataLayerVisitor::visit(DepthwiseConvolutionLayerNode &n)
{
_layer_data.clear();
add_generic_layer_data<DepthwiseConvolutionLayerNode>(_layer_data, n);
add_convolution_layer_data<DepthwiseConvolutionLayerNode>(_layer_data, n);
}
void DataLayerVisitor::visit(FusedConvolutionBatchNormalizationNode &n)
{
_layer_data.clear();
add_generic_layer_data<FusedConvolutionBatchNormalizationNode>(_layer_data, n);
add_convolution_layer_data<FusedConvolutionBatchNormalizationNode>(_layer_data, n);
add_convolution_layer_method<FusedConvolutionBatchNormalizationNode>(_layer_data, n);
}
void DataLayerVisitor::visit(FusedDepthwiseConvolutionBatchNormalizationNode &n)
{
_layer_data.clear();
add_generic_layer_data<FusedDepthwiseConvolutionBatchNormalizationNode>(_layer_data, n);
add_convolution_layer_data<FusedDepthwiseConvolutionBatchNormalizationNode>(_layer_data, n);
}
void DataLayerVisitor::visit(OutputNode &n)
{
_layer_data.clear();
ARM_COMPUTE_UNUSED(n);
}
void DataLayerVisitor::default_visit(INode &n)
{
_layer_data.clear();
add_generic_layer_data<INode>(_layer_data, n);
}
const DataLayerVisitor::LayerData &DataLayerVisitor::layer_data() const
{
return _layer_data;
}
} // namespace graph
} // namespace arm_compute
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