code: def convert_upsample(
      builder, layer, input_names, output_names, keras_layer
  ):
      """Convert convolution layer from keras to coreml.
  
      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.UpSampling1D
      ):
          fh, fw = 1, keras_layer.length
      else:  # 2D
          fh, fw = keras_layer.size
  
      builder.add_upsample(
          name=layer,
          scaling_factor_h=fh,
          scaling_factor_w=fw,
          input_name=input_name,
          output_name=output_name,
      )
  
imports: from .None import _utils
  import keras
  import numpy
label_desc: Use image node_id 12 for calling a global function with example usage: convert_upsample(builder, layer, input_names, output_names, keras_layer) without return types