class_docstr: Base class for LIT models.
docstr: Return the full vocabulary and embedding table.
  
  Implementing this is optional, but needed for some techniques such as
  HotFlip which use the embedding table to search over candidate words.
  
  Returns:
    (<string>[vocab_size], <float32>[vocab_size, emb_dim])
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code: def get_embedding_table(self) -> tuple[list[str], np.ndarray]:
      """Return the full vocabulary and embedding table.
  
      Implementing this is optional, but needed for some techniques such as
      HotFlip which use the embedding table to search over candidate words.
  
      Returns:
        (<string>[vocab_size], <float32>[vocab_size, emb_dim])
      """
      raise NotImplementedError(
          "get_embedding_table() not implemented for "
          + self.__class__.__name__
      )
  
imports: import abc
  from collections.abc import Iterable, Iterator
  import inspect
  import itertools
  import multiprocessing
  from typing import Optional, Union
  from absl import logging
  from lit_nlp.api import dataset
  from lit_nlp.api import types
  from lit_nlp.lib import utils
  import numpy
label_desc: Use image node_id 8 for calling the Model obj's underlying member method code with example usage: obj.get_embedding_table() without return types