class_docstr: This class is primarily meant to be instantiated from ``train_test_split()`` function.
class_docstr_tok: ["This","class","is","primarily","meant","to","be","instantiated","from","``","train_test_split","(",")","``","function","."]
code: def __init__(
      self,
      type: str,
      data: Sequence[TimeSeries],
      test_size: Optional[Union[float, int]] = 0.25,
      axis: Optional[int] = 0,
      input_size: Optional[int] = None,
      horizon: Optional[int] = None,
      vertical_split_type: Optional[str] = SIMPLE,
  ):
      if type not in ["train", "test"]:
          raise AttributeError(
              "Value for type parameter should be either `train` or `test`"
          )
  
      if not data:
          raise AttributeError("The `data` parameter cannot be empty.")
  
      if axis not in [0, 1]:
          raise AttributeError(
              "The `axis` parameter should be either 0 or 1."
          )
  
      if vertical_split_type not in [SIMPLE, MODEL_AWARE]:
          raise AttributeError(
              "`vertical_split_type` can be either `simple` or `model-aware`."
          )
  
      if (
          axis == 1
          and vertical_split_type == MODEL_AWARE
          and (horizon == 0 or input_size == 0)
      ):
          raise AttributeError(
              "You need to provide non-zero `horizon` and `input_size` parameters when axis=1"
          )
  
      self.type = type
      self.data = data
      self.test_size = test_size
      self.axis = axis
      self.input_size = input_size
      self.horizon = horizon
      self.vertical_split_type = vertical_split_type
      self._horizontal_split_index = None
  
file_path: darts/darts/utils/model_selection.py
imports: from typing import Optional, Sequence, Tuple, Union
  from darts import TimeSeries
label_desc: Use image node_id 1 to create a new SplitTimeSeriesSequence object from inherited base classes: Sequence with example: obj = SplitTimeSeriesSequence(type, data, test_size, axis, input_size, horizon, vertical_split_type)