diff options
Diffstat (limited to 'tensorflow/python/keras/_impl')
| -rw-r--r-- | tensorflow/python/keras/_impl/keras/backend.py | 4 | ||||
| -rw-r--r-- | tensorflow/python/keras/_impl/keras/layers/normalization.py | 4 |
2 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/python/keras/_impl/keras/backend.py b/tensorflow/python/keras/_impl/keras/backend.py index 81a4d2f820..449410fe08 100644 --- a/tensorflow/python/keras/_impl/keras/backend.py +++ b/tensorflow/python/keras/_impl/keras/backend.py @@ -3448,7 +3448,7 @@ def categorical_crossentropy(target, output, from_logits=False): Returns: Output tensor. """ - # Note: nn.softmax_cross_entropy_with_logits + # Note: nn.softmax_cross_entropy_with_logits_v2 # expects logits, Keras expects probabilities. if not from_logits: # scale preds so that the class probas of each sample sum to 1 @@ -3512,7 +3512,7 @@ def binary_crossentropy(target, output, from_logits=False): Returns: A tensor. """ - # Note: nn.softmax_cross_entropy_with_logits + # Note: nn.sigmoid_cross_entropy_with_logits # expects logits, Keras expects probabilities. if not from_logits: # transform back to logits diff --git a/tensorflow/python/keras/_impl/keras/layers/normalization.py b/tensorflow/python/keras/_impl/keras/layers/normalization.py index 5462a95d7d..c16fc07fb4 100644 --- a/tensorflow/python/keras/_impl/keras/layers/normalization.py +++ b/tensorflow/python/keras/_impl/keras/layers/normalization.py @@ -593,9 +593,9 @@ class BatchNormalization(Layer): # used during evaluation, it is more efficient to just update in one # step and should not make a significant difference in the result. new_mean = math_ops.reduce_mean(new_mean, - axis=1, keep_dims=True) + axis=1, keepdims=True) new_variance = math_ops.reduce_mean(new_variance, - axis=1, keep_dims=True) + axis=1, keepdims=True) def _do_update(var, value): if in_eager_mode and not self.trainable: |