code: def convert_clip(params, w_name, scope_name, inputs, layers, weights, names):
      
      print('Converting clip ...')
  
      if params['min'] == 0:
          print("using ReLU({0})".format(params['max']))
          layer = keras.layers.ReLU(max_value=params['max'])
      else:
          def target_layer(x, vmin=params['min'], vmax=params['max']):
              import tensorflow as tf
              return tf.clip_by_value(x, vmin, vmax)
          layer = keras.layers.Lambda(target_layer)
  
      layers[scope_name] = layer(layers[inputs[0]])
docs: Convert clip operation.
  
      Args:
          params: dictionary with layer parameters
          w_name: name prefix in state_dict
          scope_name: pytorch scope name
          inputs: pytorch node inputs
          layers: dictionary with keras tensors
          weights: pytorch state_dict
          names: use short names for keras layers