code: def __call__(
      self, x: Tensor, pos: int, encoded_audio: Tensor, streaming=False
  ):
      seqlen = x.shape[-1]
      x = (
          self.token_embedding(x)
          + self.positional_embedding[pos : pos + seqlen]
      )
      if pos == 0:
          for block in (
              self.blocks if streaming else self.blocks_start_tok
          ):
              x = block(
                  x, xa=encoded_audio, mask=self.mask, len=0
              )  # pass xa for cross attn kv caching
          return (
              self.output_tok(x)
              if streaming
              else self.start_output_tok(x)
          )
      else:
          for block in self.blocks_after_start_tok:
              len_v = Variable(
                  "self_attn_cache_len", 1, self.max_self_attn_cache_len
              ).bind(pos)
              x = block(x, mask=self.mask, len=len_v)
          return self.after_start_output_tok(x)
  
imports: import sys
  import pathlib
  import base64
  import multiprocessing
  import numpy
  from typing import Optional, Union, Literal, List
  from tinygrad.jit import TinyJit
  from tinygrad.nn.state import torch_load, load_state_dict
  from tinygrad.helpers import getenv, DEBUG, CI, fetch
  import tinygrad.nn
  from tinygrad.shape.symbolic import Variable
  from tinygrad.tensor import Tensor
  import itertools
  import librosa
label_desc: Use image node_id 2 for calling the TextDecoder obj's underlying member method code with example usage: obj.__call__(x, pos, encoded_audio, streaming) and returns: unknown, self