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Assert the condition x >= 0
holds element-wise.
tf.debugging.assert_non_negative( 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_negative(x, y)]): output = tf.reduce_sum(x)
Non-negative means, for every element x[i]
of x
, we have x[i] >= 0
. If x
is empty this is trivially satisfied.
Args | |
---|---|
x | Numeric Tensor . |
data | The tensors to print out if the condition is False. Defaults to error message and first few entries of x . |
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". |
Returns | |
---|---|
Op that raises InvalidArgumentError if x >= 0 is False. |
Raises | |
---|---|
InvalidArgumentError | if the check can be performed immediately and x >= 0 is False. The check can be performed immediately during eager execution or if x is statically known. |
returns None
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/debugging/assert_non_negative