docstr: Fit the transformer to the (sequence of) series and return the transformed input.
  
  Parameters
  ----------
  series
      the (sequence of) series to transform.
  args
      Additional positional arguments passed to the :func:`ts_transform` and :func:`ts_fit` methods.
  component_mask : Optional[np.ndarray] = None
      Optionally, a 1-D boolean np.ndarray of length ``series.n_components`` that specifies which
      components of the underlying `series` the transform should be fitted and applied to.
  kwargs
      Additional keyword arguments passed to the :func:`ts_transform` and :func:`ts_fit` methods.
  
  Returns
  -------
  Union[TimeSeries, Sequence[TimeSeries]]
      Transformed data.
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code: def fit_transform(
      self,
      series: Union[TimeSeries, Sequence[TimeSeries]],
      *args,
      component_mask: Optional[np.array] = None,
      **kwargs,
  ) -> Union[TimeSeries, List[TimeSeries]]:
      """Fit the transformer to the (sequence of) series and return the transformed input.
  
      Parameters
      ----------
      series
          the (sequence of) series to transform.
      args
          Additional positional arguments passed to the :func:`ts_transform` and :func:`ts_fit` methods.
      component_mask : Optional[np.ndarray] = None
          Optionally, a 1-D boolean np.ndarray of length ``series.n_components`` that specifies which
          components of the underlying `series` the transform should be fitted and applied to.
      kwargs
          Additional keyword arguments passed to the :func:`ts_transform` and :func:`ts_fit` methods.
  
      Returns
      -------
      Union[TimeSeries, Sequence[TimeSeries]]
          Transformed data.
      """
      return self.fit(
          series, *args, component_mask=component_mask, **kwargs
      ).transform(
          series, *args, component_mask=component_mask, **kwargs
      )
  
file_path: darts/darts/dataprocessing/transformers/fittable_data_transformer.py
imports: from abc import abstractmethod
  from typing import Any, Generator, List, Mapping, Optional, Sequence, Union
  import numpy
  from darts import TimeSeries
  from darts.logging import get_logger, raise_if, raise_if_not
  from darts.utils import _build_tqdm_iterator, _parallel_apply
  from .base_data_transformer import BaseDataTransformer
label_desc: Use image node_id 4 for calling the FittableDataTransformer obj's underlying member method code with example usage: obj.fit_transform(series) and returns: self