code: 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,
      )
  
imports: from .None import _utils
  import keras
  import numpy
label_desc: Use image node_id 20 for calling a global function with example usage: convert_flatten(builder, layer, input_names, output_names, keras_layer) without return types