(builder, node, graph, err)
convert to CoreML Random Normal Like Layer:
    https://github.com/apple/coremltools/blob/655b3be5cc0d42c3c4fa49f0f0e4a93a26b3e492/mlmodel/format/NeuralNetwork.proto#L4434
convert to CoreML Random Normal Like Layer:
    https://github.com/apple/coremltools/blob/655b3be5cc0d42c3c4fa49f0f0e4a93a26b3e492/mlmodel/format/NeuralNetwork.proto#L4434
convert to CoreML Random Normal Like Layer : https : // github . com / apple / coremltools / blob / 655b3be5cc0d42c3c4fa49f0f0e4a93a26b3e492 / mlmodel / format / NeuralNetwork . proto#L4434
def _convert_randomnormallike(builder, node, graph, err):
    '''
    convert to CoreML Random Normal Like Layer:
    https://github.com/apple/coremltools/blob/655b3be5cc0d42c3c4fa49f0f0e4a93a26b3e492/mlmodel/format/NeuralNetwork.proto#L4434
    '''
     # Ignoring attribute `dtype` as CoreML internally represents tensors into 'Float'
    mean  = node.attributes.get('mean', 0.0)
    scale = node.attributes.get('scale', 1.0)
    seed  = node.attributes.get('seed', -1)

    builder.add_random_normal_like(
        name=node.name,
        input_name=node.inputs[0],
        output_name=node.outputs[0],
        mean=mean,
        stddev=scale,
        seed=seed
    )
def _convert_randomnormallike ( builder , node , graph , err ) : # Ignoring attribute `dtype` as CoreML internally represents tensors into 'Float' mean = node . attributes . get ( 'mean' , 0.0 ) scale = node . attributes . get ( 'scale' , 1.0 ) seed = node . attributes . get ( 'seed' , - 1 ) builder . add_random_normal_like ( name = node . name , input_name = node . inputs [ 0 ] , output_name = node . outputs [ 0 ] , mean = mean , stddev = scale , seed = seed )