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Assert x has rank equal to rank or higher.
tf.compat.v1.assert_rank_at_least(
x, rank, data=None, summarize=None, message=None, name=None
)
Example of adding a dependency to an operation:
with tf.control_dependencies([tf.compat.v1.assert_rank_at_least(x, 2)]):
output = tf.reduce_sum(x)
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".Op raising InvalidArgumentError unless x has specified rank or higher.
If static checks determine x has correct rank, a no_op is returned.
ValueError: If static checks determine x has wrong rank.