code: def __init__(
      self, dim, n_heads, n_kv_heads, max_context, linear=nn.Linear
  ):
      self.n_heads = n_heads
      self.n_kv_heads = (
          n_kv_heads if n_kv_heads is not None else n_heads
      )  # n_kv_heads != n_heads implies MQA [arxiv/2307.09288, A.2.1]
      self.head_dim = dim // n_heads
      self.n_rep = self.n_heads // self.n_kv_heads
      self.max_context = max_context
  
      self.wq = linear(dim, self.n_heads * self.head_dim, bias=False)
      self.wk = linear(dim, self.n_kv_heads * self.head_dim, bias=False)
      self.wv = linear(dim, self.n_kv_heads * self.head_dim, bias=False)
      self.wo = linear(self.n_heads * self.head_dim, dim, bias=False)
  
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 1 to create a new Attention object  with example: obj = Attention(dim, n_heads, n_kv_heads, max_context, linear)