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| author |  A. Unique TensorFlower <nobody@tensorflow.org> | 2016-05-24 08:20:34 -0800 |
|---|---|---|
| committer |  TensorFlower Gardener <gardener@tensorflow.org> | 2016-05-24 09:36:27 -0700 |
| commit | 0fc350ec8af982b3081c3df41147126af7d867bb (patch) | |
| tree | 20d8d3d6bf322e0f9e33c78b795e9c6ad5261bf4 | |
| parent | 95da19d8cebc095c381ef1377e4e2aa088c06d64 (diff) | |
Update generated Python Op docs.
Change: 123112607
| -rw-r--r-- | tensorflow/g3doc/api_docs/python/functions_and_classes/tf.nn.sufficient_statistics.md | 8 | ||||
| -rw-r--r-- | tensorflow/g3doc/api_docs/python/nn.md | 8 |
2 files changed, 4 insertions, 12 deletions
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/tf.nn.sufficient_statistics.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/tf.nn.sufficient_statistics.md index 81ae4a89f8..92cb5596e6 100644 --- a/tensorflow/g3doc/api_docs/python/functions_and_classes/tf.nn.sufficient_statistics.md +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/tf.nn.sufficient_statistics.md @@ -3,12 +3,8 @@ Calculate the sufficient statistics for the mean and variance of `x`. These sufficient statistics are computed using the one pass algorithm on -an input that's optionally shifted using the value of the 1st element in `x`. -See: +an input that's optionally shifted. See: https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Computing_shifted_data -Unfortunately, in some cases using a random individual sample as the shift -value leads experimentally to very poor numerical stability, so it is disabled -by default. The one-pass approach might have to be revised accordingly. ##### Args: @@ -27,5 +23,5 @@ by default. The one-pass approach might have to be revised accordingly. * the count (number of elements to average over). * the (possibly shifted) sum of the elements in the array. * the (possibly shifted) sum of squares of the elements in the array. - * the shift by which the mean must be corrected or None if `shift` is False. + * the shift by which the mean must be corrected or None if `shift` is None. diff --git a/tensorflow/g3doc/api_docs/python/nn.md b/tensorflow/g3doc/api_docs/python/nn.md index c70beb9fbc..8254810db8 100644 --- a/tensorflow/g3doc/api_docs/python/nn.md +++ b/tensorflow/g3doc/api_docs/python/nn.md @@ -829,12 +829,8 @@ convolutional neural networks (NIPS 2012)] Calculate the sufficient statistics for the mean and variance of `x`. These sufficient statistics are computed using the one pass algorithm on -an input that's optionally shifted using the value of the 1st element in `x`. -See: +an input that's optionally shifted. See: https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Computing_shifted_data -Unfortunately, in some cases using a random individual sample as the shift -value leads experimentally to very poor numerical stability, so it is disabled -by default. The one-pass approach might have to be revised accordingly. ##### Args: @@ -853,7 +849,7 @@ by default. The one-pass approach might have to be revised accordingly. * the count (number of elements to average over). * the (possibly shifted) sum of the elements in the array. * the (possibly shifted) sum of squares of the elements in the array. - * the shift by which the mean must be corrected or None if `shift` is False. + * the shift by which the mean must be corrected or None if `shift` is None. - - - |