code: def get_nd_test_batches(n: int):
      """Returns a list of input batches of dimension n."""
      # The first two batches have a single element, the last batch has 2 elements.
      x0 = tf.zeros([1, n], dtype=tf.float64)
      x1 = tf.constant([range(n)], dtype=tf.float64)
      x2 = tf.concat([x0, x1], axis=0)
      w0 = tf.constant([1], dtype=tf.float64)
      w1 = tf.constant([2], dtype=tf.float64)
      w2 = tf.constant([0.5, 0.5], dtype=tf.float64)
      return [x0, x1, x2], [w0, w1, w2]
  
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 3 for calling a global function with example usage: get_nd_test_batches(n) and returns: list,  list