docstr: Update the state of the sequence before a forward pass.
  
  Arguments:
      num_tokens (int): The number of tokens in the sequence that will be executed during the
          next forward pass of the model.
docstr_tok: ["Update","the","state","of","the","sequence","before","a","forward","pass",".","Arguments",":","num_tokens","(","int",")",":","The","number","of","tokens","in","the","sequence","that","will","be","executed","during","the","next","forward","pass","of","the","model","."]
code: def pre_forward(self, num_tokens: int) -> None:
      """
      Update the state of the sequence before a forward pass.
  
      Arguments:
          num_tokens (int): The number of tokens in the sequence that will be executed during the
              next forward pass of the model.
      """
      self._in_flight_tokens = num_tokens
  
imports: from typing import List, Tuple, Union
  import torch
label_desc: Use image node_id 10 for calling the DSSequenceDescriptor obj's underlying member method code with example usage: obj.pre_forward(num_tokens) without return types