code: def forward(self, x, context=None, mask=None):
      h = self.heads
  
      q = self.to_q(x)
      context = default(context, x)
      k = self.to_k(context)
      v = self.to_v(context)
  
      out = self._attention(q, k, v, mask)
  
      return self.to_out(out)
  
imports: import math
  from inspect import isfunction
  import torch
  import torch.nn.functional
  from apex.contrib.group_norm import GroupNorm
  from einops import rearrange
  from torch import einsum, nn
  from torch._dynamo import disable
  from nemo.collections.multimodal.modules.stable_diffusion.diffusionmodules.util import checkpoint
label_desc: Use image node_id 2 for calling the CrossAttention obj's underlying member method code with example usage: obj.forward(x, context, mask) and returns: self