class_docstr: This processor can be used to suppress a list of tokens. The processor will set their log probs to `-inf` so that they
  are not sampled.
class_docstr_tok: ["This","processor","can","be","used","to","suppress","a","list","of","tokens",".","The","processor","will","set","their","log","probs","to","`","-inf","`","so","that","they","are","not","sampled","."]
code: def __call__(
      self, input_ids: tf.Tensor, scores: tf.Tensor, cur_len: int
  ) -> tf.Tensor:
      scores = tf.tensor_scatter_nd_update(
          scores,
          indices=[
              [i, token]
              for i in range(scores.shape[0])
              for token in self.suppress_tokens
          ],
          updates=[
              -float("inf")
              for _ in range(
                  scores.shape[0] * len(self.suppress_tokens)
              )
          ],
      )
      return scores
  
imports: import inspect
  from typing import List, Tuple
  import numpy
  import tensorflow
  from ..tf_utils import stable_softmax
  from ..utils import add_start_docstrings
  from ..utils.logging import get_logger
label_desc: Use image node_id 2 for calling the TFSuppressTokensLogitsProcessor obj's underlying member method code with example usage: obj.__call__(input_ids, scores, cur_len) and returns: scores