code: def __call__(
      self, x: Tensor, start_pos: Variable, mask: Optional[Tensor]
  ) -> Tensor:
      if mask is not None or start_pos.val == 0:
          # no symbolic shape qkv when consuming prompts
          start_pos = start_pos.val
  
      if HALF:
          x = x.half()
      xqkv = self.c_attn(x)
      xq, xk, xv = [
          xqkv.shrink(
              (None, None, (i * self.dim, (i + 1) * self.dim))
          ).reshape(None, None, self.n_heads, self.head_dim)
          for i in range(3)
      ]
      bsz, seqlen, _, _ = xq.shape
  
      # create kv cache
      if not hasattr(self, "cache_kv"):
          self.cache_kv = Tensor.zeros(
              2,
              bsz,
              MAX_CONTEXT,
              self.n_heads,
              self.head_dim,
              dtype=x.dtype,
          )
  
      if start_pos > 0:
          keys = (
              self.cache_kv[0]
              .shrink((None, (0, start_pos), None, None))
              .cat(xk, dim=1)
          )
          values = (
              self.cache_kv[1]
              .shrink((None, (0, start_pos), None, None))
              .cat(xv, dim=1)
          )
      else:
          keys = xk
          values = xv
  
      # update the cache
      new_cache = (
          Tensor.stack([keys, values])
          .pad(
              (
                  None,
                  None,
                  (0, MAX_CONTEXT - start_pos - seqlen),
                  None,
                  None,
              )
          )
          .contiguous()
      )
      self.cache_kv.assign(new_cache).realize()
  
      xq, keys, values = (
          xq.transpose(1, 2),
          keys.transpose(1, 2),
          values.transpose(1, 2),
      )
      return self.c_proj(
          xq.scaled_dot_product_attention(keys, values, mask)
          .transpose(1, 2)
          .reshape(bsz, seqlen, self.dim)
      )
  
imports: from typing import Optional, Union
  import argparse
  from tqdm import trange
  import numpy
  import tiktoken
  from tinygrad import Tensor, TinyJit, Device, GlobalCounters
  from tinygrad.helpers import Timing, DEBUG, getenv, fetch, colored
  from tinygrad.nn import Embedding, Linear, LayerNorm
  from tinygrad.nn.state import torch_load, load_state_dict, get_state_dict
  from tinygrad.shape.symbolic import Variable
label_desc: Use image node_id 2 for calling the Attention obj's underlying member method code with example usage: obj.__call__(x, start_pos, mask) and returns: self