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体验新版 GitCode,发现更多精彩内容 >>
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156617d3
编写于
6月 17, 2018
作者:
Q
qiaolongfei
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差异文件
polish doc of RMSPropOptimizer
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python/paddle/fluid/optimizer.py
python/paddle/fluid/optimizer.py
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python/paddle/fluid/optimizer.py
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...
@@ -774,26 +774,26 @@ class RMSPropOptimizer(Optimizer):
...
@@ -774,26 +774,26 @@ class RMSPropOptimizer(Optimizer):
.. math::
.. math::
r(w, t) & =
\\
rho r(w, t-1) + (1 -
\\
rho)(
\\
nabla Q_{i}(w))^2
\\
r(w, t) & =
\\
rho r(w, t-1) + (1 -
\\
rho)(
\\
nabla Q_{i}(w))^2
w & = w -
\\
frac{
\\
eta} {
\\
sqrt{r(w,t) +
\\
epsilon}}
\\
nabla Q_{i}(w)
w & = w -
\\
frac{
\\
eta} {
\\
sqrt{r(w,t) +
\\
epsilon}}
\\
nabla Q_{i}(w)
The first equation calculates moving average of the squared gradient for
The first equation calculates moving average of the squared gradient for
each weight. Then dividing the gradient by :math:
`sqrt{v(w,t)}`.
each weight. Then dividing the gradient by :math:`sqrt{v(w,t)}`.
In some cases, adding a momentum term :math: `
\\
beta` is beneficial.
In some cases, adding a momentum term :math: `
\\
beta` is beneficial.
In our implementation, Nesterov momentum is used:
In our implementation, Nesterov momentum is used:
.. math::
.. math::
r(w, t) & =
\\
rho r(w, t-1) + (1 -
\\
rho)(
\\
nabla Q_{i}(w))^2
\\\\
r(w, t) & =
\\
rho r(w, t-1) + (1 -
\\
rho)(
\\
nabla Q_{i}(w))^2
v(w, t) & =
\\
beta v(w, t-1) +
\\
frac{
\\
eta} {
\\
sqrt{v(w,t) +
v(w, t) & =
\\
beta v(w, t-1) +
\\
frac{
\\
eta} {
\\
sqrt{v(w,t) +
\\
epsilon}}
\\
nabla Q_{i}(w)
\\
epsilon}}
\\
nabla Q_{i}(w)
w & = w - v(w, t)
w & = w - v(w, t)
where, :math:
`
\\
rho` is a hyperparameter and typical values are 0.9, 0.95
where, :math:`
\\
rho` is a hyperparameter and typical values are 0.9, 0.95
and so on. :math: `beta` is the momentum term. :math: `
\\
epsilon` is a
and so on. :math: `beta` is the momentum term. :math: `
\\
epsilon` is a
smoothing term to avoid division by zero, usually set somewhere in range
smoothing term to avoid division by zero, usually set somewhere in range
from 1e-4 to 1e-8.
from 1e-4 to 1e-8.
...
@@ -801,10 +801,10 @@ class RMSPropOptimizer(Optimizer):
...
@@ -801,10 +801,10 @@ class RMSPropOptimizer(Optimizer):
Args:
Args:
learning_rate(float): global leraning rate.
learning_rate(float): global leraning rate.
rho(float): rho is :math:
`
\\
rho` in equation, set 0.95 by default.
rho(float): rho is :math:`
\\
rho` in equation, set 0.95 by default.
epsilon(float): :math:
`
\\
epsilon` in equation is smoothing term to
epsilon(float): :math:`
\\
epsilon` in equation is smoothing term to
avoid division by zero, set 1e-6 by default.
avoid division by zero, set 1e-6 by default.
momentum(float): :math:
`
\\
beta` in equation is the momentum term,
momentum(float): :math:`
\\
beta` in equation is the momentum term,
set 0.0 by default.
set 0.0 by default.
Raises:
Raises:
...
...
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