class_docstr: Inference model implementation for ragged batching for OPT models.
class_docstr_tok: ["Inference","model","implementation","for","ragged","batching","for","OPT","models","."]
code: def vocab_size(self) -> int:
      return self._config.vocab_size
  
imports: from typing import Iterable, Optional, Tuple
  import torch
  import deepspeed.comm
  from ...allocator import empty_from
  from ...inference_utils import ActivationType, DtypeEnum
  from ...model_implementations import *
  from ...modules.configs import *
  from ...ragged import RaggedBatchWrapper
  from .container import OPTNonTransformerContainer, OPTTransformerContainer
  from ...modules.heuristics import instantiate_embed
label_desc: Use image node_id 4 for calling the OPTInferenceModel obj's underlying member method code with example usage: obj.vocab_size() and returns: self