zhreshold commented on a change in pull request #8005: add warmup lr_scheduler
URL: https://github.com/apache/incubator-mxnet/pull/8005#discussion_r141416042
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File path: python/mxnet/lr_scheduler.py
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@@ -136,3 +136,80 @@ def __call__(self, num_update):
else:
return self.base_lr
return self.base_lr
+
+class GradualWarmupWithMultiFactorScheduler(LRScheduler):
+ def __init__(self, warmup_step = 100, begin_lr=0.01, stop_lr=0.1,
multifactor_step = 100, factor = 1):
+ """Warmup the learning rate by a const value for first 'warmup_step'
steps.
+
+ It returns a new learning rate by::
+
+ begin_lr + num_update * const_update
+
+ Then reduce the learning rate by given a list of steps as
MultiFactorScheduler.
+
+ Parameters
+ ----------
+ warmup_step : int
+ Changes the learning rate for first 'warmup_step' updates.
+ begin_lr : float, optional
+ The learning rate at begin.
+ stop_lr : float, optional
+ Stop updating the learning rate if it is less than this value.
+ multifactor_step: list of int
+ The list of steps to schedule a change
+ factor: float
+ The factor to change the learning rate.
+ """
+ super(GradualWarmupWithMultiFactorScheduler, self).__init__()
+ if stop_lr <= begin_lr:
+ raise ValueError("stop_lr must larger than begin_lr")
+ assert isinstance(multifactor_step, list) and len(multifactor_step) >=
1
Review comment:
default multifactor_step == int will break, add cast to list first
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