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tf.debugging.assert_none_equal

TensorFlow 2 version View source on GitHub

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

Aliases:

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 x[i], y[i], we have x[i] != y[i]. If both x and 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)

Args:

  • x: Numeric Tensor.
  • y: Numeric Tensor, same dtype as and broadcastable to x.
  • data: The tensors to print out if the condition is False. Defaults to error message and first few entries of x, y.
  • 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".

Returns:

Op that raises InvalidArgumentError if x != y is False.

Raises:

  • 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