code: def _create_model_inputs(self, model):
      if isinstance(model.input, dict):
          inputs = {}
          for key, input_layer in model.input.items():
              inputs[key] = np.random.randn(
                  *self._batch(input_layer.get_shape().as_list(), 1)
              )
          return inputs
      else:
          return np.random.randn(
              *self._batch(model.input.get_shape().as_list(), 1)
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.quantization.keras import utils
  from tensorflow_model_optimization.python.core.quantization.keras.graph_transformations import model_transformer
  from tensorflow_model_optimization.python.core.quantization.keras.graph_transformations import transforms
label_desc: Use image node_id 3 for calling the ModelTransformerTest obj's underlying member method code with example usage: obj._create_model_inputs(model) and returns: inputs, np