class_docstr: Abstract base class for deep learning time series regression.
  
  The base classifier provides a deep learning default method for
  _predict, and provides a new abstract method for building a
  model.
  
  Parameters
  ----------
  batch_size : int, default = 40
      training batch size for the model
  
  Attributes
  ----------
  self.model_ - the fitted DL model
class_docstr_tok: ["Abstract","base","class","for","deep","learning","time","series","regression",".","The","base","classifier","provides","a","deep","learning","default","method","for","_predict",",","and","provides","a","new","abstract","method","for","building","a","model",".","Parameters","--","--","--","--","--","batch_size",":","int",",","default","=","40","training","batch","size","for","the","model","Attributes","--","--","--","--","--","self.model_","-","the","fitted","DL","model"]
code: def __init__(self, batch_size=40):
      super().__init__()
  
      self.batch_size = batch_size
      self.model_ = None
  
file_path: sktime/sktime/regression/deep_learning/base.py
imports: from abc import ABC, abstractmethod
  import numpy
  from sktime.regression.base import BaseRegressor
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 1 to create a new BaseDeepRegressor object from inherited base classes: BaseRegressor, ABC with example: obj = BaseDeepRegressor(batch_size)