code: def __init__(
      self,
      dim: int,
      hidden_dim: int,
      n_heads: int,
      n_kv_heads: int,
      norm_eps: float,
      max_context: int,
      linear=nn.Linear,
      feed_forward=FeedForward,
  ):
      self.attention = Attention(
          dim, n_heads, n_kv_heads, max_context, linear
      )
      self.feed_forward = feed_forward(dim, hidden_dim, linear)
      self.attention_norm = RMSNorm(dim, norm_eps)
      self.ffn_norm = RMSNorm(dim, norm_eps)
  
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 TransformerBlock object  with example: obj = TransformerBlock(dim, hidden_dim, n_heads, n_kv_heads, norm_eps, max_context, linear, feed_forward)