tf.assert_rank_at_least(x, rank, data=None, summarize=None, message=None, name=None)

tf.assert_rank_at_least(x, rank, data=None, summarize=None, message=None, name=None)

See the guide: Asserts and boolean checks

Assert x has rank equal to rank or higher.

Example of adding a dependency to an operation:

with tf.control_dependencies([tf.assert_rank_at_least(x, 2)]):
  output = tf.reduce_sum(x)

Args:

• x: Numeric Tensor.
• rank: Scalar Tensor.
• data: The tensors to print out if the condition is False. Defaults to error message and first few entries of x.
• 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_least".

Returns:

Op raising InvalidArgumentError unless x has specified rank or higher. If static checks determine x has correct rank, a no_op is returned.

Raises:

• ValueError: If static checks determine x has wrong rank.

Defined in tensorflow/python/ops/check_ops.py.