docstr: Augment time series.
  
  Parameters
  ----------
  X : numpy array
      Time series to be augmented. It must be a numpy array with shape
      (T,), (N, T), or (N, T, C), where T is the length of a series, N is
      the number of series, and C is the number of a channels in a series.
  
  Y: numpy array, optional
      Segmentation mask of the original time series. It must be a binary
      numpy array with shape (T,), (N, T), or (N, T, L), where T is the
      length of a series, N is the number of series, and L is the number
      of a segmentation classes. Default: None.
  
  Returns
  -------
  2-tuple (numpy array, numpy array), or numpy array
      The augmented time series, and (optionally) the augmented
      segmentation mask.
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code: def augment(
      self, X: np.ndarray, Y: Optional[np.ndarray] = None
  ) -> Union[np.ndarray, Tuple[np.ndarray, np.ndarray]]:
      """
      Augment time series.
  
      Parameters
      ----------
      X : numpy array
          Time series to be augmented. It must be a numpy array with shape
          (T,), (N, T), or (N, T, C), where T is the length of a series, N is
          the number of series, and C is the number of a channels in a series.
  
      Y: numpy array, optional
          Segmentation mask of the original time series. It must be a binary
          numpy array with shape (T,), (N, T), or (N, T, L), where T is the
          length of a series, N is the number of series, and L is the number
          of a segmentation classes. Default: None.
  
      Returns
      -------
      2-tuple (numpy array, numpy array), or numpy array
          The augmented time series, and (optionally) the augmented
          segmentation mask.
  
      """
      X_aug = X
      Y_aug = Y
      for augmenter in self._pipe:
          if Y_aug is None:
              X_aug = augmenter.augment(X_aug)
          else:
              X_aug, Y_aug = augmenter.augment(X_aug, Y_aug)
      if Y_aug is None:
          return X_aug
      else:
          return X_aug, Y_aug
  
imports: from abc import ABC, abstractmethod
  from copy import deepcopy
  from typing import Any, Dict, Iterator, List, Optional, Tuple, Union, overload
  import numpy
  from .None import _default_seed
label_desc: Use image node_id 10 for calling the _AugmenterPipe obj's underlying member method code with example usage: obj.augment(X, Y) and returns: X_aug, X_aug,  Y_aug