code: def forward(self, x):
      B, N, C = x.shape
  
      qkv = self.qkv(x).chunk(3, dim=-1)
      q, k, v = map(
          lambda t: rearrange(t, "b n (h d) -> b h n d", h=self.heads),
          qkv,
      )
  
      q = q * self.scale
  
      attn = einsum("b h i d, b h j d -> b h i j", q, k)
      attn = attn.softmax(dim=-1)
      attn = self.attn_drop(attn)
  
      x = einsum("b h i j, b h j d -> b h i d", attn, v)
      x = rearrange(x, "b h n d -> b n (h d)")
  
      return self.proj_drop(self.proj(x))
  
imports: import torch
  from torch import nn, einsum
  import torch.nn.functional
  from einops import rearrange, repeat
label_desc: Use image node_id 2 for calling the Attention obj's underlying member method code with example usage: obj.forward(x) and returns: self