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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def convert_flatten(builder, layer, input_names, output_names, keras_layer):
 """Convert a flatten layer from keras to coreml. Parameters keras_layer: layer A keras layer object. builder: NeuralNetworkBuilder A neural network builder object. """

    input_name, output_name = (input_names[0], output_names[0])

    # blob_order == 0 if the input blob needs not be rearranged
    # blob_order == 1 if the input blob needs to be rearranged
    blob_order = 0

    # using keras_layer.input.shape have a "?" (Dimension[None] at the front),
    # making a 3D tensor with unknown batch size 4D
    if len(keras_layer.input.shape) == 4:
        blob_order = 1

    builder.add_flatten(name=layer, mode=blob_order, input_name=input_name, output_name=output_name)