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Diffstat (limited to 'tensorflow/python/eager/backprop.py')
| -rw-r--r-- | tensorflow/python/eager/backprop.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/python/eager/backprop.py b/tensorflow/python/eager/backprop.py index b2e6c60021..bd97b181ff 100644 --- a/tensorflow/python/eager/backprop.py +++ b/tensorflow/python/eager/backprop.py @@ -196,11 +196,11 @@ def implicit_val_and_grad(f): # TODO(cais): Remove calls to tf.constant() once the gradients functions # accept lists and np.ndarrays. - def grad_fn(*args): + def grad_fn(*args, **kwds): """Computes the gradient of the wrapped function.""" this_tape = tape.push_new_tape() try: - end_node = f(*args) + end_node = f(*args, **kwds) if end_node is None: raise ValueError("Cannot differentiate a function that returns None; " "did you forget to return a value from {}?".format( |