private Layer ConvertFullyConnected(tflite.Operator op)
{
var inputs = op.GetInputsArray();
var input = _graph.Tensors(inputs[0]).Value;
var options = op.BuiltinOptions <tflite.FullyConnectedOptions>().Value;
var weights = _graph.Tensors(inputs[1]).Value;
var bias = _graph.Tensors(inputs[2]).Value;
if (input.ShapeLength == 4 && (input.Shape(1) != 1 || input.Shape(2) != 1))
{
var flatten = new TensorflowFlatten(input.GetShapeArray().ToNCHW());
var layer = new FullyConnected(flatten.Output.Dimensions, _model.GetTensor <float>(weights), _model.GetTensor <float>(bias),
options.FusedActivationFunction.ToActivationFunction());
layer.Input.SetConnection(flatten.Output);
_inputs.Add(flatten.Input, inputs[0]);
_outputs.Add(op.Outputs(0), layer.Output);
return(layer);
}
else
{
var layer = new FullyConnected(input.GetShapeArray().ToNCHW(), _model.GetTensor <float>(weights), _model.GetTensor <float>(bias),
options.FusedActivationFunction.ToActivationFunction());
_inputs.Add(layer.Input, inputs[0]);
_outputs.Add(op.Outputs(0), layer.Output);
return(layer);
}
}
public void Infer(TensorflowFlatten layer, TensorflowFlattenLayerArgument argument, InferenceContext context)
{
var inputAlloc = context.MainMemoryMap[layer.Input.Connection.From];
var outputAlloc = context.MainMemoryMap[layer.Output];
argument.Flags = K210LayerFlags.MainMemoryOutput;
argument.MainMemoryInputAddress = inputAlloc.GetAddress();
argument.MainMemoryOutputAddress = outputAlloc.GetAddress();
}
public TensorflowFlattenLayerArgument Convert(TensorflowFlatten layer, ConvertContext context)
{
return(new TensorflowFlattenLayerArgument
{
Width = (uint)layer.Input.Dimensions[3],
Height = (uint)layer.Input.Dimensions[2],
Channels = (uint)layer.Input.Dimensions[1]
});
}
private Layer ConvertL2Normalization(tflite.Operator op)
{
var inputs = op.GetInputsArray();
var input = _graph.Tensors(inputs[0]).Value;
if (input.ShapeLength == 4 && (input.Shape(1) != 1 || input.Shape(2) != 1))
{
var flatten = new TensorflowFlatten(input.GetShapeArray().ToNCHW());
var layer = new L2Normalization(flatten.Output.Dimensions);
layer.Input.SetConnection(flatten.Output);
_inputs.Add(flatten.Input, inputs[0]);
_outputs.Add(op.Outputs(0), layer.Output);
return(layer);
}
else
{
var layer = new L2Normalization(input.GetShapeArray().ToNCHW());
_inputs.Add(layer.Input, inputs[0]);
_outputs.Add(op.Outputs(0), layer.Output);
return(layer);
}
}
