code: def __call__(
      self,
      tokens: Tensor,
      start_pos: Variable,
      temperature: float = 0.0,
  ):
      # TODO: better way to handle the first call v.s. the rest?
      if tokens.shape[0:2] == (1, 1) and self.forward_jit is not None:
          assert start_pos > 0
          return self.forward_jit(
              tokens,
              Variable("start_pos", 1, self.max_context).bind(
                  start_pos
              ),
              temperature,
          )
      return self.forward(tokens, start_pos, temperature)
  
imports: from typing import Tuple, Union, Optional, Dict
  from tinygrad import Tensor, Variable, TinyJit, dtypes, nn, Device
  from tinygrad.helpers import getenv
label_desc: Use image node_id 3 for calling the Transformer obj's underlying member method code with example usage: obj.__call__(tokens, start_pos, temperature) and returns: self, self