code: def _save_model_with_obscurely_shaped_list_output(export_dir):
      """Writes SavedModel with hard-to-predict output shapes."""
  
      def broadcast_obscurely_to(input_tensor, shape):
          """Like tf.broadcast_to(), but hostile to static shape propagation."""
          obscured_shape = tf.cast(
              tf.cast(shape, tf.float32)
              # Add small random noise that gets rounded away.
              + 0.1 * tf.sin(tf.random.uniform((), -3, +3)) + 0.3,
              tf.int32,
          )
          return tf.broadcast_to(input_tensor, obscured_shape)
  
      @tf.function(
          input_signature=[
              tf.TensorSpec(shape=(None, 1), dtype=tf.float32)
          ]
      )
      def call_fn(x):
          # For each batch element x, the three outputs are
          #   value x with shape (1)
          #   value 2*x broadcast to shape (2,2)
          #   value 3*x broadcast to shape (3,3,3)
          batch_size = tf.shape(x)[0]
          return [
              broadcast_obscurely_to(
                  tf.reshape(i * x, [batch_size] + [1] * i),
                  tf.concat([[batch_size], [i] * i], axis=0),
              )
              for i in range(1, 4)
          ]
  
      obj = tf.train.Checkpoint()
      obj.__call__ = call_fn
      tf.saved_model.save(obj, export_dir)
  
imports: import json
  import os
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_hub
label_desc: Use image node_id 11 for calling a global function with example usage: _save_model_with_obscurely_shaped_list_output(export_dir) and returns: tf, unknown