提交 320c4b61 编写于 作者: M mindspore-ci-bot 提交者: Gitee

!66 Fix a docs bug.

Merge pull request !66 from jxlang910/master
......@@ -343,9 +343,9 @@ class _MechanismsParamsUpdater(Cell):
class AdaClippingWithGaussianRandom(Cell):
"""
Adaptive clipping. If `decay_policy` is 'Linear', the update formula is
$ norm_bound = norm_bound - learning_rate*(beta-target_unclipped_quantile)$.
`decay_policy` is 'Geometric', the update formula is
$ norm_bound = norm_bound*exp(-learning_rate*(empirical_fraction-target_unclipped_quantile))$.
norm_bound = norm_bound - learning_rate*(beta - target_unclipped_quantile).
If `decay_policy` is 'Geometric', the update formula is norm_bound =
norm_bound*exp(-learning_rate*(empirical_fraction - target_unclipped_quantile)).
where beta is the empirical fraction of samples with the value at most
`target_unclipped_quantile`.
......@@ -355,7 +355,7 @@ class AdaClippingWithGaussianRandom(Cell):
learning_rate(float): Learning rate of update norm clip. Default: 0.001.
target_unclipped_quantile(float): Target quantile of norm clip. Default: 0.9.
fraction_stddev(float): The stddev of Gaussian normal which used in
empirical_fraction, the formula is $empirical_fraction + N(0, fraction_stddev)$.
empirical_fraction, the formula is empirical_fraction + N(0, fraction_stddev).
Default: 0.01.
seed(int): Original random seed, if seed=0 random normal will use secure
random number. IF seed!=0 random normal will generate values using
......
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