tf.assert_rank_at_least()

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

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)

Example of adding dependency to the tensor being checked:

x = tf.with_dependencies([tf.assert_rank_at_least(x, 2)], 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.
doc_TensorFlow
2016-10-14 12:42:47
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