|TensorFlow 2 version||View source on GitHub|
Assert the condition
x != y holds element-wise.
tf.debugging.assert_none_equal( x, y, data=None, summarize=None, message=None, name=None )
This condition holds if for every pair of (possibly broadcast) elements
y[i], we have
x[i] != y[i].
y are empty, this is trivially satisfied.
When running in graph mode, you should add a dependency on this operation to ensure that it runs. Example of adding a dependency to an operation:
with tf.control_dependencies([tf.compat.v1.assert_none_equal(x, y)]): output = tf.reduce_sum(x)
Tensor, same dtype as and broadcastable to
data: The tensors to print out if the condition is False. Defaults to error message and first few entries of
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_none_equal".
Op that raises
x != y is False.
InvalidArgumentError: if the check can be performed immediately and
x != yis False. The check can be performed immediately during eager execution or if
yare statically known.