code: def get_model_from_generator(
      model_generator: type_aliases.ModelGenerator,
      layer_generator: type_aliases.LayerGenerator,
      input_dims: Sequence[int],
      output_dims: Sequence[int],
      is_eager: bool,
  ) -> tf.keras.Model:
      """Creates a simple model from input specifications."""
      model = model_generator(layer_generator, input_dims, output_dims)
      model.compile(
          optimizer=tf.keras.optimizers.SGD(learning_rate=1.0),
          loss=tf.keras.losses.MeanSquaredError(
              reduction=tf.keras.losses.Reduction.SUM_OVER_BATCH_SIZE
          ),
          run_eagerly=is_eager,
      )
      return model
  
imports: from collections.abc import Callable, MutableSequence, Sequence
  from typing import Optional
  import numpy
  import tensorflow
  import tensorflow.compat.v2
  from tensorflow_privacy.privacy.fast_gradient_clipping import clip_grads
  from tensorflow_privacy.privacy.fast_gradient_clipping import layer_registry
  from tensorflow_privacy.privacy.fast_gradient_clipping import type_aliases
label_desc: Use image node_id 6 for calling a global function with example usage: get_model_from_generator(model_generator, layer_generator, input_dims, output_dims, is_eager) and returns: model