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Moses Marin 2019-04-15 20:30:50 -07:00 committed by GitHub
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tensorflow/python/keras/optimizer_v2/adam.py
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@ -34,12 +34,14 @@ class Adam(optimizer_v2.OptimizerV2):
Adam optimization is a stochastic gradient descent method that is based on Adam optimization is a stochastic gradient descent method that is based on
adaptive estimation of first-order and second-order moments. adaptive estimation of first-order and second-order moments.
According to the paper According to the paper
[Adam: A Method for Stochastic Optimization. Kingma et al., 2014](http://arxiv.org/abs/1412.6980), [Adam: A Method for Stochastic Optimization. Kingma et al.,
2014](http://arxiv.org/abs/1412.6980),
the method is "*computationally efficient, has little memory the method is "*computationally efficient, has little memory
requirement, invariant to diagonal rescaling of gradients, and is well suited requirement, invariant to diagonal rescaling of gradients, and is well suited
for problems that are large in terms of data/parameters*". for problems that are large in terms of data/parameters*".
For AMSGrad see [On The Convergence Of Adam And Beyond. Reddi et al., 5-8](https://openreview.net/pdf?id=ryQu7f-RZ). For AMSGrad see [On The Convergence Of Adam And Beyond.
Reddi et al., 5-8](https://openreview.net/pdf?id=ryQu7f-RZ).
""" """
def __init__(self, def __init__(self,