tf.assert_non_negative( x, data=None, summarize=None, message=None, name=None )
See the guide: Asserts and boolean checks
Assert the condition
x >= 0 holds element-wise.
Example of adding a dependency to an operation:
with tf.control_dependencies([tf.assert_non_negative(x)]): output = tf.reduce_sum(x)
Non-negative means, for every element
x, we have
x[i] >= 0. If
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_negative".
x is all non-negative.
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.