code: def convert_padding(builder, layer, input_names, output_names, keras_layer):
      
      _check_data_format(keras_layer)
      # Get input and output names
      input_name, output_name = (input_names[0], output_names[0])
  
      is_1d = isinstance(keras_layer, _keras.layers.ZeroPadding1D)
  
      padding = keras_layer.padding
      top = left = bottom = right = 0
      if is_1d:
          if type(padding) is int:
              left = right = padding
          elif type(padding) is tuple:
              if type(padding[0]) is int:
                  left, right = padding
              elif type(padding[0]) is tuple and len(padding[0]) == 2:
                  left, right = padding[0]
              else:
                  raise ValueError("Unrecognized padding option: %s" % (str(padding)))
          else:
              raise ValueError("Unrecognized padding option: %s" % (str(padding)))
      else:
          if type(padding) is int:
              top = left = bottom = right = padding
          elif type(padding) is tuple:
              if type(padding[0]) is int:
                  top, left = padding
                  bottom, right = padding
              elif type(padding[0]) is tuple:
                  top, bottom = padding[0]
                  left, right = padding[1]
              else:
                  raise ValueError("Unrecognized padding option: %s" % (str(padding)))
          else:
              raise ValueError("Unrecognized padding option: %s" % (str(padding)))
  
      # Now add the layer
      builder.add_padding(name = layer,
          left = left, right=right, top=top, bottom=bottom, value = 0,
          input_name = input_name, output_name=output_name
          )
docs: 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.