class_docstr: Learning Rate configuration
  
  Args:
      base_lr (float): base learning rate
      schedulers (list): learning rate schedulers
class_docstr_tok: ["Learning","Rate","configuration","Args",":","base_lr","(","float",")",":","base","learning","rate","schedulers","(","list",")",":","learning","rate","schedulers"]
code: def __init__(
      self, base_lr=0.01, schedulers=[PiecewiseDecay(), LinearWarmup()]
  ):
      super(LearningRate, self).__init__()
      self.base_lr = base_lr
      self.schedulers = []
  
      schedulers = copy.deepcopy(schedulers)
      for sched in schedulers:
          if isinstance(sched, dict):
              # support dict sched instantiate
              module = sys.modules[__name__]
              type = sched.pop("name")
              scheduler = getattr(module, type)(**sched)
              self.schedulers.append(scheduler)
          else:
              self.schedulers.append(sched)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import sys
  import math
  import paddle
  import paddle.nn
  import paddle.optimizer
  import paddle.regularizer
  from ppdet.core.workspace import register, serializable
  import copy
  from .adamw import AdamWDL, build_adamwdl
  from ppdet.utils.logger import setup_logger
label_desc: Use image node_id 1 to create a new LearningRate object from inherited base classes: object with example: obj = LearningRate(base_lr, schedulers)