code: def assert_rank_at_most(
      x, rank, summarize=None, message=None, name=None
  ):
      """Assert `x` has rank equal to `rank` or smaller.
  
      Example of adding a dependency to an operation:
  
      ```python
      with tf.control_dependencies([tf.assert_rank_at_most(x, 2)]):
        output = tf.reduce_sum(x)
      ```
  
      Args:
        x:  Numeric `Tensor`.
        rank:  Scalar `Tensor`.
        summarize: Print this many entries of each tensor.
        message: A string to prefix to the default message.
        name: A name for this operation (optional).
          Defaults to "assert_rank_at_most".
  
      Returns:
        Op raising `InvalidArgumentError` unless `x` has specified rank or lower.
        If static checks determine `x` has correct rank, a `no_op` is returned.
  
      Raises:
        ValueError:  If static checks determine `x` has wrong rank.
      """
      with tf.name_scope(name or "assert_rank_at_most"):
          return tf.debugging.assert_less_equal(
              tf.rank(x), rank, summarize=summarize, message=message
          )
  
imports: import numpy
  import tensorflow.compat.v2
label_desc: Use image node_id 3 for calling a global function with example usage: assert_rank_at_most(x, rank, summarize, message, name) and returns: tf