class_docstr: Abstract base class for deep learning time series classifiers.
  
  The base classifier provides a deep learning default method for
  _predict and _predict_proba, 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, random_state=None):
      super().__init__()
  
      self.batch_size = batch_size
      self.random_state = random_state
      self.model_ = None
  
imports: from abc import ABC, abstractmethod
  import numpy
  from sklearn.preprocessing import LabelEncoder, OneHotEncoder
  from sklearn.utils import check_random_state
  from sktime.base._base import SERIALIZATION_FORMATS
  from sktime.classification.base import BaseClassifier
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 1 to create a new BaseDeepClassifier object from inherited base classes: BaseClassifier, ABC with example: obj = BaseDeepClassifier(batch_size, random_state)