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| author |  A. Unique TensorFlower <gardener@tensorflow.org> | 2018-10-08 09:49:59 -0700 |
|---|---|---|
| committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-10-08 09:59:07 -0700 |
| commit | 87315f41ced19136819cef56ef37636c52c474de (patch) | |
| tree | ec59603b89328a439146cdf4c3144fee5bbbf060 | |
| parent | f435e776216c7a86f619a17064fd6e1deee638b3 (diff) | |
Remove Raises documentation on imperative_grads for ValueErrror not raised.
PiperOrigin-RevId: 216201714
| -rw-r--r-- | tensorflow/python/eager/imperative_grad.py | 5 |
1 files changed, 0 insertions, 5 deletions
diff --git a/tensorflow/python/eager/imperative_grad.py b/tensorflow/python/eager/imperative_grad.py index 5f5af4ab6c..5c35860e9d 100644 --- a/tensorflow/python/eager/imperative_grad.py +++ b/tensorflow/python/eager/imperative_grad.py @@ -51,11 +51,6 @@ def imperative_grad( Raises: RuntimeError: if something goes wrong. - ValueError: if there is no sequence of differentiable operations connecting - a source and any target Tensor. This can happen either if the target is - not computed based on the source, if the tracing was set up incorrectly, - or if only non-differentiable functions of the source were used in the - computation of target. """ return pywrap_tensorflow.TFE_Py_TapeGradient( tape._tape, # pylint: disable=protected-access |