code: def convert_cropping(
      builder, layer, input_names, output_names, keras_layer
  ):
      """Convert padding layer from keras to coreml.
      Keras only supports zero padding at this time.
      Parameters
      ----------
      keras_layer: layer
          A keras layer object.
  
      builder: NeuralNetworkBuilder
          A neural network builder object.
      """
      # Get input and output names
      input_name, output_name = (input_names[0], output_names[0])
  
      if isinstance(keras_layer, keras.layers.convolutional.Cropping1D):
          left, right = keras_layer.cropping
          top, bottom = (0, 0)
      else:  # 2D
          left, right = keras_layer.cropping[0]
          top, bottom = keras_layer.cropping[1]
  
      # Now add the layer
      builder.add_crop(
          name=layer,
          left=left,
          right=right,
          top=top,
          bottom=bottom,
          offset=[0, 0],
          input_names=[input_name],
          output_name=output_name,
      )
  
imports: from .None import _utils
  import keras
  import numpy
label_desc: Use image node_id 10 for calling a global function with example usage: convert_cropping(builder, layer, input_names, output_names, keras_layer) without return types