class_docstr: an unassuming Transformer block
class_docstr_tok: ["an","unassuming","Transformer","block"]
code: def forward(self, x, attention_masks=None):
      # Multi-head attention sub-layer.
      x_att, att = self.attn(
          self.ln_1(x), attention_masks=attention_masks
      )
      # Residual of multi-head attention sub-layer.
      x = x + x_att
  
      # Position-wise FFN sub-layer: fc + activation + fc + dropout
      x_ffn = self.mlp.dropout(
          self.mlp.c_proj(self.mlp.act(self.mlp.c_fc(x)))
      )
      # Residual of position-wise FFN sub-layer.
      x = x + x_ffn
      return x, att
  
imports: import math
  from dataclasses import dataclass
  from typing import Tuple
  import torch
  import torch.nn
  from torch.nn import functional
  from ray.rllib.utils.annotations import DeveloperAPI
  from ray.rllib.utils.deprecation import Deprecated
label_desc: Use image node_id 2 for calling the Block obj's underlying member method code with example usage: obj.forward(x, attention_masks) and returns: x,  att