|TensorFlow 2 version||View source on GitHub|
Assert the condition
x <= 0 holds element-wise.
tf.debugging.assert_non_positive( x, data=None, summarize=None, message=None, name=None )
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.debugging.assert_non_positive(x, y)]): output = tf.reduce_sum(x)
Non-positive means, for every element
x, we have
x[i] <= 0.
x is empty this is trivially satisfied.
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_non_positive".
Op that raises
x <= 0 is False.
InvalidArgumentError: if the check can be performed immediately and
x <= 0is False. The check can be performed immediately during eager execution or if
xis statically known.