class_docstr: [`TFLogitsProcessor`] enforcing a min-length by setting EOS probability to 0.
  
  Args:
      min_length (`int`):
          The minimum length below which the score of `eos_token_id` is set to `-float("Inf")`.
      eos_token_id (`int`):
          The id of the *end-of-sequence* token.
class_docstr_tok: ["[","`","TFLogitsProcessor","`","]","enforcing","a","min-length","by","setting","EOS","probability","to","0",".","Args",":","min_length","(","`","int","`",")",":","The","minimum","length","below","which","the","score","of","`","eos_token_id","`","is","set","to","`","-float","(","``","Inf","''",")","`",".","eos_token_id","(","`","int","`",")",":","The","id","of","the","*","end-of-sequence","*","token","."]
code: def __call__(
      self, input_ids: tf.Tensor, scores: tf.Tensor, cur_len: int
  ) -> tf.Tensor:
      # applies eos token masking if the first argument is true
      scores = tf.cond(
          tf.less(cur_len, self.min_length),
          lambda: self._apply_eos_token_mask(scores),
          lambda: tf.identity(scores),
      )
      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 3 for calling the TFMinLengthLogitsProcessor obj's underlying member method code with example usage: obj.__call__(input_ids, scores, cur_len) and returns: scores