docstr: Return the maximum sequence length of the model.
  NOTE: Different model configurations have different max sequence length
  attribute names.
      - n_positions: (CTRLConfig)
      - max_position_embeddings: (BartConfig, RoFormerConfig)
      - n_ctx: (GPT2Config)
  NOTE: For relative position encoded models you should specify the max
  sequence length of the model in the constructor via `max_length`.
docstr_tok: ["Return","the","maximum","sequence","length","of","the","model",".","NOTE",":","Different","model","configurations","have","different","max","sequence","length","attribute","names",".","-","n_positions",":","(","CTRLConfig",")","-","max_position_embeddings",":","(","BartConfig",",","RoFormerConfig",")","-","n_ctx",":","(","GPT2Config",")","NOTE",":","For","relative","position","encoded","models","you","should","specify","the","max","sequence","length","of","the","model","in","the","constructor","via","`","max_length","`","."]
code: def max_length(self) -> int:
      """Return the maximum sequence length of the model.
      NOTE: Different model configurations have different max sequence length
      attribute names.
          - n_positions: (CTRLConfig)
          - max_position_embeddings: (BartConfig, RoFormerConfig)
          - n_ctx: (GPT2Config)
      NOTE: For relative position encoded models you should specify the max
      sequence length of the model in the constructor via `max_length`.
      """
      if self._max_length is not None:
          return self._max_length
      # Try to get the sequence length from the model config.
      seqlen_config_attrs = (
          "n_positions",
          "max_position_embeddings",
          "n_ctx",
      )
      for attr in seqlen_config_attrs:
          if hasattr(self._config, attr):
              return getattr(self._config, attr)
      if hasattr(self.tokenizer, "model_max_length"):
          return self.tokenizer.model_max_length
      return self._DEFAULT_MAX_LENGTH
  
imports: import math
  import torch
  import torch.nn.functional
  import transformers
  import peft
  from pathlib import Path
  from typing import List, Mapping, NewType, Optional, Tuple, Union
  from tqdm import tqdm
  from transformers import BatchEncoding
  from lm_eval import utils
  from lm_eval.base import BaseLM
label_desc: Use image node_id 9 for calling the HuggingFaceAutoLM obj's underlying member method code with example usage: obj.max_length() and returns: self, self, self, getattr