[Slice of Caffe parser support] Error when converting DPN68 from caffe to IR about mmdnn

[gafr]

any update on this one?

[Alan-Turing-Ko]

Any update?

[l8rpeace]

Any update on this?

[ljie-PI]

any update on this :)

[kitstar]

Slice layer of Caffe parser is not implemented. We will inform you asap. Thanks.

[AllenMao]

any update on this :)

[BasicCoder]

I have an immature solution in caffe to tensorflow:
in mmdnn/conversion/caffe/shape.py add code:

def shape_slice(node):    
    print(node.parameters)    
    axis = node.parameters.axis    
    slices = len(node.parameters.slice_point) if len(node.parameters.slice_point) > 2 else 2    
    input_shape = node.get_only_parent()[0].output_shape    
    if axis == 1:    
        return TensorShape(input_shape.batch_size, input_shape.channels // slices, input_shape.height, input_shape.width)    
    elif axis == 2:    
        return TensorShape(input_shape.batch_size, input_shape.channels, input_shape.height // slices, input_shape.width)    
    elif axis == 3:    
        return TensorShape(input_shape.batch_size, input_shape.channels, input_shape.height, input_shape.width // slices)    
    return TensorShape(input_shape.batch_size, input_shape.channels // slices, input_shape.height, input_shape.width)    

in mmdnn/conversion/caffe/graph.py modify code:

...    
'Split': shape_split,    
'Slice': shape_slice,    
'TanH': shape_identity,    
...    

in mmdnn/conversion/caffe/mapper.py add code in class NodeMapper:

@classmethod    
 def map_slice(cls, node):    
       slices = len(node.parameters.slice_point) if len(node.parameters.slice_point) > 2 else 2    
       kwargs = {'axis': (2, 3, 1, 0)[node.parameters.axis], 'num_or_size_splits': slices}    
       cls._convert_output_shape(kwargs, node)    
       return Node.create('Split', **kwargs)    

so you can run command:

mmtoir -f caffe -n ./models/model.prototxt -w ./models/model.caffemodel -o caffe_model_IR    

mmtocode -f tensorflow --IRModelPath caffe_model_IR.pb --IRWeightPath caffe_model_IR.npy --dstModelPath tf_model_IR.py

It generates tensorflow model code: tf_model_IR.py
Now you can modify tf_model_IR.py source file to correspond to caffe model

Note:
This can only divide input tensor evenly.