class_docstr: Crop random sub-sequences from time series.
  
  To guarantee all output series have the same length, if the crop size is not
  deterministic, all crops must be resize to a fixed length.
  
  Parameters
  ----------
  size : int, tuple, list
      The length of random crops.
  
      - If int, all crops have the same length.
      - If list, a crop from a series has a length sampled from this list
        randomly.
      - If 2-tuple, a crop from a series has a length sampled from this
        interval randomly.
  
  resize : int, optional
      The length that all crops are resized to. Only necessary if the crop
      size is not fixed.
  
  repeats : int, optional
      The number of times a series is augmented. If greater than one, a series
      will be augmented so many times independently. This parameter can also
      be set by operator `*`. Default: 1.
  
  prob : float, optional
      The probability of a series is augmented. It must be in (0.0, 1.0]. If
      multiple output is expected, this value must be 1.0, so that all output
      have the same length. This parameter can also be set by operator `@`.
      Default: 1.0.
  
  seed : int, optional
      The random seed. Default: None.
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code: def resize(self) -> Optional[int]:
      return self._resize
  
file_path: tsaug/src/tsaug/_augmenter/crop.py
imports: from typing import List, Optional, Tuple, Union
  import numpy
  from .base import _Augmenter, _default_seed
  from .resize import Resize
label_desc: Use image node_id 5 for calling the Crop obj's underlying member method code with example usage: obj.resize() and returns: self