tf.debugging.assert_none_equal

Assert the condition x != y holds element-wise.

tf.debugging.assert_none_equal(
    x, y, summarize=None, message=None, name=None
)

This Op checks that x[i] != y[i] holds for every pair of (possibly broadcast) elements of x and y. If both x and y are empty, this is trivially satisfied.

If x != y does not hold, message, as well as the first summarize entries of x and y are printed, and InvalidArgumentError is raised.

When using inside tf.function, this API takes effects during execution. It's recommended to use this API with tf.control_dependencies to ensure the correct execution order.

In the following example, without tf.control_dependencies, errors may not be raised at all. Check tf.control_dependencies for more details.

def check_size(x):
  with tf.control_dependencies([
      tf.debugging.assert_none_equal(tf.size(x), 6,
                      message='Bad tensor size')]):
    return x
 
check_size(tf.ones([2, 3], tf.float32))
Traceback (most recent call last):

InvalidArgumentError: ...

x Numeric Tensor.
y Numeric Tensor, same dtype as and broadcastable to x.
message A string to prefix to the default message. (optional)
summarize Print this many entries of each tensor. (optional)
name A name for this operation (optional). Defaults to "assert_none_equal".

Op that raises InvalidArgumentError if x != y is False. This can be used with tf.control_dependencies inside of tf.functions to block followup computation until the check has executed.

InvalidArgumentError if the check can be performed immediately and x == y is False. The check can be performed immediately during eager execution or if x and y are statically known.

eager compatibility

returns None