class_docstr: Full Wikipedia teacher that splits the chunks into train/valid/test.
class_docstr_tok: ["Full","Wikipedia","teacher","that","splits","the","chunks","into","train\/valid\/test","."]
docstr: Return a list of chunk IDs (integer).
  
  Given the datatype (train/test/valid), return the list of chunk IDs that
  correspond to that split.
docstr_tok: ["Return","a","list","of","chunk","IDs","(","integer",")",".","Given","the","datatype","(","train\/test\/valid",")",",","return","the","list","of","chunk","IDs","that","correspond","to","that","split","."]
code: def get_fold_chunks(self, opt) -> List[int]:  # type: ignore
      """
      Return a list of chunk IDs (integer).
  
      Given the datatype (train/test/valid), return the list of chunk IDs that
      correspond to that split.
      """
      datatype = opt["datatype"]
      all_chunk_idxs = list(self.chunk_idx_to_file.keys())
      if "train" in datatype:
          return all_chunk_idxs[:-2]
      elif "valid" in datatype:
          return [all_chunk_idxs[-2]]
      else:
          return [all_chunk_idxs[-1]]
  
imports: from parlai.core.teachers import DialogTeacher, ChunkTeacher, ChunkOutput
  from parlai.utils.io import PathManager
  from parlai.core.message import Message
  from .build import build
  import json
  import os
  from typing import List, Tuple
label_desc: Use image node_id 5 for calling the FullSplitTeacher obj's underlying member method code with example usage: obj.get_fold_chunks(opt) and returns: all_chunk_idxs, list, list