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Update generated Python Op docs.

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Change: 144117353
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A. Unique TensorFlower 2017-01-10 12:59:31 -08:00 committed by TensorFlower Gardener
parent fdbd02c8d7
commit a762b0a0de
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8
tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.nn.moments.md
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@ -6,6 +6,9 @@ The mean and variance are calculated by aggregating the contents of `x`
across `axes`. If `x` is 1-D and `axes = [0]` this is just the mean
and variance of a vector.
Note: for numerical stability, when shift=None, the true mean
would be computed and used as shift.
When using these moments for batch normalization (see
`tf.nn.batch_normalization`):
@ -20,8 +23,9 @@ When using these moments for batch normalization (see
* <b>`axes`</b>: Array of ints. Axes along which to compute mean and
variance.
* <b>`shift`</b>: A `Tensor` containing the value by which to shift the data for
numerical stability, or `None` if no shift is to be performed. A shift
close to the true mean provides the most numerically stable results.
numerical stability, or `None` in which case the true mean of the data is
used as shift. A shift close to the true mean provides the most
numerically stable results.
* <b>`name`</b>: Name used to scope the operations that compute the moments.
* <b>`keep_dims`</b>: produce moments with the same dimensionality as the input.

8
tensorflow/g3doc/api_docs/python/nn.md
View File

@ -1932,6 +1932,9 @@ The mean and variance are calculated by aggregating the contents of `x`
across `axes`. If `x` is 1-D and `axes = [0]` this is just the mean
and variance of a vector.
Note: for numerical stability, when shift=None, the true mean
would be computed and used as shift.
When using these moments for batch normalization (see
`tf.nn.batch_normalization`):
@ -1946,8 +1949,9 @@ When using these moments for batch normalization (see
* <b>`axes`</b>: Array of ints. Axes along which to compute mean and
variance.
* <b>`shift`</b>: A `Tensor` containing the value by which to shift the data for
numerical stability, or `None` if no shift is to be performed. A shift
close to the true mean provides the most numerically stable results.
numerical stability, or `None` in which case the true mean of the data is
used as shift. A shift close to the true mean provides the most
numerically stable results.
* <b>`name`</b>: Name used to scope the operations that compute the moments.
* <b>`keep_dims`</b>: produce moments with the same dimensionality as the input.