class_docstr: A simple Dataset object to wrap a List of Datapoints, for example Sentences.
class_docstr_tok: ["A","simple","Dataset","object","to","wrap","a","List","of","Datapoints",",","for","example","Sentences","."]
docstr: Instantiate FlairDatapointDataset.
  
  Args:
      datapoints: DT or List of DT that make up FlairDatapointDataset
docstr_tok: ["Instantiate","FlairDatapointDataset",".","Args",":","datapoints",":","DT","or","List","of","DT","that","make","up","FlairDatapointDataset"]
code: def __init__(self, datapoints: Union[DT, List[DT]]) -> None:
      """Instantiate FlairDatapointDataset.
  
      Args:
          datapoints: DT or List of DT that make up FlairDatapointDataset
      """
      # cast to list if necessary
      if not isinstance(datapoints, list):
          datapoints = [datapoints]
      self.datapoints = datapoints
  
imports: import logging
  from abc import abstractmethod
  from pathlib import Path
  from typing import Generic, List, Optional, Union
  import torch.utils.data.dataloader
  from deprecated.sphinx import deprecated
  from flair.data import DT, FlairDataset, Sentence, Tokenizer
  from flair.tokenization import SegtokTokenizer, SpaceTokenizer
label_desc: Use image node_id 1 to create a new FlairDatapointDataset object from inherited base classes: FlairDataset, Generic with example: obj = FlairDatapointDataset(datapoints)