(builder, node, graph, err)
convert to CoreML Load Constant ND Layer:
    https://github.com/apple/coremltools/blob/655b3be5cc0d42c3c4fa49f0f0e4a93a26b3e492/mlmodel/format/NeuralNetwork.proto#L3596
convert to CoreML Load Constant ND Layer:
    https://github.com/apple/coremltools/blob/655b3be5cc0d42c3c4fa49f0f0e4a93a26b3e492/mlmodel/format/NeuralNetwork.proto#L3596
convert to CoreML Load Constant ND Layer : https : // github . com / apple / coremltools / blob / 655b3be5cc0d42c3c4fa49f0f0e4a93a26b3e492 / mlmodel / format / NeuralNetwork . proto#L3596
def _convert_constant(builder, node, graph, err):
    '''
    convert to CoreML Load Constant ND Layer:
    https://github.com/apple/coremltools/blob/655b3be5cc0d42c3c4fa49f0f0e4a93a26b3e492/mlmodel/format/NeuralNetwork.proto#L3596
    '''
    value = node.attrs['value']
    # HACK: If Value is 0-Rank then make it 1-Rank
    builder.add_load_constant_nd(
        name=node.name,
        output_name=node.outputs[0],
        constant_value=value,
        shape=[1] if value.shape == () else value.shape
    )
    graph.constants_loaded(node.outputs[0])
def _convert_constant ( builder , node , graph , err ) : value = node . attrs [ 'value' ] # HACK: If Value is 0-Rank then make it 1-Rank builder . add_load_constant_nd ( name = node . name , output_name = node . outputs [ 0 ] , constant_value = value , shape = [ 1 ] if value . shape == ( ) else value . shape ) graph . constants_loaded ( node . outputs [ 0 ] )