code: def _build_tf_keras_model(self, input_shape, flat_call_inputs=True):
      inputs = []
      if not isinstance(input_shape[0], (tuple, list)):
          input_shape = [input_shape]
  
      for shape in input_shape:
          inputs.append(tf.keras.Input(shape=shape))
  
      if flat_call_inputs:
          outputs = self._tf_keras_layer(*inputs)
      else:
          outputs = self._tf_keras_layer(inputs)
      return tf.keras.Model(inputs=inputs, outputs=outputs)
  
imports: import time
  import numpy
  import tensorflow
  from absl import flags
  import keras
label_desc: Use image node_id 3 for calling the LayerBenchmark obj's underlying member method code with example usage: obj._build_tf_keras_model(input_shape, flat_call_inputs) and returns: tf