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eb5d427d
编写于
12月 14, 2018
作者:
Q
Qiao Longfei
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add comment for lazy_mode adam optimizer
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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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@@ -641,9 +641,14 @@ class AdamOptimizer(Optimizer):
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.
regularization: A Regularizer, such as
fluid.regularizer.L2DecayRegularizer.
regularization: A Regularizer, such as fluid.regularizer.L2DecayRegularizer.
name: A optional name prefix.
lazy_mode(bool: false): The official Adam algorithm has two moving-average accumulators
the accumulators are updated at every step. Every element of the two moving-average is updated
in both dense mode and sparse mode. If the size of parameter is very large, then the update
may be very slow. The lazy mode only update the element that has gradient is the current
mini-batch, so it will be much more faster. But this mode has different semantics with the
original Adam algorithm and may lead to different result.
Examples:
.. code-block:: python
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