class_docstr: An implementation of Adamax http://arxiv.org/pdf/1412.6980.pdf
  :param learningrate learning rate
  :param beta1 first moment coefficient
  :param beta2 second moment coefficient
  :param epsilon for numerical stability
  >>> adagrad = Adamax()
  creating: createAdamax
class_docstr_tok: ["An","implementation","of","Adamax","http",":","\/\/arxiv.org\/pdf\/1412.6980.pdf",":","param","learningrate","learning","rate",":","param","beta1","first","moment","coefficient",":","param","beta2","second","moment","coefficient",":","param","epsilon","for","numerical","stability",">",">",">","adagrad","=","Adamax","(",")","creating",":","createAdamax"]
code: def __init__(
      self,
      learningrate: float = 0.002,
      beta1: float = 0.9,
      beta2: float = 0.999,
      epsilon: float = 1e-38,
  ) -> None:
      from bigdl.dllib.optim.optimizer import Adamax as BAdamax
  
      self.optimizer = BAdamax(
          learningrate, beta1, beta2, epsilon, bigdl_type="float"
      )
  
imports: from abc import ABC, abstractmethod
  from bigdl.dllib.utils.common import DOUBLEMAX
  from bigdl.orca.learn.optimizers.schedule import Scheduler
  from bigdl.dllib.utils.log4Error import invalidInputError
  from typing import Any, Optional, Dict, TYPE_CHECKING
label_desc: Use image node_id 1 to create a new Adamax object from inherited base classes: Optimizer with example: obj = Adamax(learningrate, beta1, beta2, epsilon)