code: def forward(self, x, mask=None):
      x = x + self.attn(self.ln_1(x), mask=mask)
      x = x + self.mlp(self.ln_2(x))
      return x
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  from .nn import timestep_embedding
label_desc: Use image node_id 2 for calling the ResidualAttentionBlock obj's underlying member method code with example usage: obj.forward(x, mask) and returns: x