tf.debugging.check_numerics | TensorFlow v2.16.1 (original) (raw)
Checks a tensor for NaN and Inf values.
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Compat aliases for migration
SeeMigration guide for more details.
tf.debugging.check_numerics(
tensor: Annotated[Any, TV_CheckNumerics_T], message: str, name=None
) -> Annotated[Any, TV_CheckNumerics_T]
Used in the notebooks
| Used in the guide |
|---|
| TensorFlow graph optimization with Grappler |
When run, reports an InvalidArgument error if tensor has any values that are not a number (NaN) or infinity (Inf). Otherwise, returns the input tensor.
Example usage:
a = tf.Variable(1.0)
tf.debugging.check_numerics(a, message='')
b = tf.Variable(np.nan)
try:
tf.debugging.check_numerics(b, message='Checking b')
except Exception as e:
assert "Checking b : Tensor had NaN values" in e.message
c = tf.Variable(np.inf)
try:
tf.debugging.check_numerics(c, message='Checking c')
except Exception as e:
assert "Checking c : Tensor had Inf values" in e.message
| Args | |
|---|---|
| tensor | A Tensor. Must be one of the following types: bfloat16, half, float32, float64. |
| message | A string. Prefix of the error message. |
| name | A name for the operation (optional). |
| Returns |
|---|
| A Tensor. Has the same type as tensor. |