TensorFlow 2 version | View source on GitHub |
Assert the condition x < 0
holds element-wise.
tf.debugging.assert_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_negative(x, y)]):
output = tf.reduce_sum(x)
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_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.
|
Eager Compatibility
returns None