Support imperative learning rate scheduler #15584
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velconia
commented
Jan 29, 2019
•
velconia
commented
- move imperative mnist ut to test_imperative_mnist
- add optimizer lr scheduler ut into test_imperative_optimizer.py
- implement lr scheduler in imperative mode
… imperative_lr_scheduler
… imperative_lr_scheduler
test=develop
test=develop
panyx0718
reviewed
Mar 12, 2019
| __all__ = ['PiecewiseDecay'] | ||
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| class LearningRateDecay(object): |
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does this support static graph? why not use existing lr_scheduler?
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static lr and dynamic lr is used via interface in learning_rate_scheduler.py under the fluid dir
… imperative_lr_scheduler
…/Paddle into imperative_lr_scheduler test=develop
test=develop
test=develop
panyx0718
reviewed
Mar 27, 2019
python/paddle/fluid/optimizer.py
Outdated
| # create learning rate Variable | ||
| if isinstance(self._learning_rate, float): | ||
| self._learning_rate_map[framework.default_main_program( | ||
| )] = layers.create_global_var( |
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can this be created many times?
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no, this should only be called once Optimizer.init
| persistable=True) | ||
| # get learning rate Variable from LearningRateDecay | ||
| elif isinstance(self._learning_rate, LearningRateDecay): | ||
| self._learning_rate_map[framework.default_main_program( |
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to keep the same with static mode code
… imperative_lr_scheduler test=develop
test=develop
test=develop
… imperative_lr_scheduler test=develop
test=develop
test=develop
test=develop
panyx0718
approved these changes
Mar 31, 2019
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