class_docstr: Abstract class for all encoders
class_docstr_tok: ["Abstract","class","for","all","encoders"]
docstr: Returns whether the `Encoder` object has been fitted.
docstr_tok: ["Returns","whether","the","`","Encoder","`","object","has","been","fitted","."]
code: def fit_called(self) -> bool:
      """Returns whether the `Encoder` object has been fitted."""
      return self._fit_called
  
imports: from abc import ABC, abstractmethod
  from typing import List, Optional, Sequence, Tuple, Union
  import numpy
  import pandas
  from darts import TimeSeries
  from darts.dataprocessing.transformers import FittableDataTransformer
  from darts.logging import get_logger, raise_if, raise_log
  from darts.utils.timeseries_generation import generate_index
label_desc: Use image node_id 7 for calling the Encoder obj's underlying member method code with example usage: obj.fit_called() and returns: self