提交 2053b6b7 编写于 作者: Q qiaolongfei

add doc fo AdamOptimizer

上级 156617d3
...@@ -449,7 +449,40 @@ class AdagradOptimizer(Optimizer): ...@@ -449,7 +449,40 @@ class AdagradOptimizer(Optimizer):
class AdamOptimizer(Optimizer): class AdamOptimizer(Optimizer):
"""Implements the Adam Optimizer """
This implements the Adam optimizer from Section 2 of the Adam
paper : https://arxiv.org/abs/1412.6980.
Adam is a first-order gradient-based optimization method based on
adaptive estimates of lower-order moments.
Adam updates:
.. math::
t & = t + 1
moment\_1\_out & = {\\beta}_1 * moment\_1 + (1 - {\\beta}_1) * grad
moment\_2\_out & = {\\beta}_2 * moment\_2 + (1 - {\\beta}_2) * grad * grad
learning\_rate & = learning\_rate * \\
\\frac{\sqrt{1 - {\\beta}_2^t}}{1 - {\\beta}_1^t}
param\_out & = param - learning\_rate * \\frac{moment\_1}{\sqrt{moment\_2} + \epsilon}
Args:
learning_rate (float|Variable): the learning rate used to update parameters. \
Can be a float value or a Variable with one float value as data element.
beta1 (float): The exponential decay rate for the 1st moment estimates.
beta2 (float): The exponential decay rate for the 2nd moment estimates.
epsilon (float): a small float value for numerical stability.
Examples:
.. code-block:: python
optimizer = fluid.optimizer.Adam(learning_rate=0.2)
optimizer.minimize(cost)
""" """
_moment1_acc_str = "moment1" _moment1_acc_str = "moment1"
_moment2_acc_str = "moment2" _moment2_acc_str = "moment2"
......
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