{

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");

}

{

std::ostringstream method;

method << node.convolution_method();

layer_data["convolution_method"] = method.str();

{

// 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) + "]";

}

{

_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);

{

_layer_data.clear();

add_generic_layer_data<DepthwiseConvolutionLayerNode>(_layer_data, n);

add_convolution_layer_data<DepthwiseConvolutionLayerNode>(_layer_data, 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);

{

_layer_data.clear();

add_generic_layer_data<FusedDepthwiseConvolutionBatchNormalizationNode>(_layer_data, n);

add_convolution_layer_data<FusedDepthwiseConvolutionBatchNormalizationNode>(_layer_data, n);

{

_layer_data.clear();

ARM_COMPUTE_UNUSED(n);

{

_layer_data.clear();

add_generic_layer_data<INode>(_layer_data, n);