diff options
Diffstat (limited to 'tensorflow/python/ops/nn_ops.py')
| -rw-r--r-- | tensorflow/python/ops/nn_ops.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/python/ops/nn_ops.py b/tensorflow/python/ops/nn_ops.py index 08f2a59b63..f7891bb2d0 100644 --- a/tensorflow/python/ops/nn_ops.py +++ b/tensorflow/python/ops/nn_ops.py @@ -194,7 +194,7 @@ def softmax_cross_entropy_with_logits(logits, labels, name=None): example, each CIFAR-10 image is labeled with one and only one label: an image can be a dog or a truck, but not both. - **NOTE:**: While the classes are mutually exclusive, their probabilities + **NOTE:** While the classes are mutually exclusive, their probabilities need not be. All that is required is that each row of `labels` is a valid probability distribution. If using exclusive `labels` (wherein one and only one class is true at a time), see @@ -231,7 +231,7 @@ def sparse_softmax_cross_entropy_with_logits(logits, labels, name=None): example, each CIFAR-10 image is labeled with one and only one label: an image can be a dog or a truck, but not both. - **NOTE:**: For this operation, the probability of a given label is considered + **NOTE:** For this operation, the probability of a given label is considered exclusive. That is, soft classes are not allowed, and the `labels` vector must provide a single specific index for the true class for each row of `logits` (each minibatch entry). For soft softmax classification with |