code: def forward(
      self,
      net: Tensor,
      *,
      no_head: bool = False,
      apply_tanh: Optional[bool] = None,
  ) -> Tensor:
      net = self.decoder(net)
      if no_head:
          return net
      net = self.head(net)
      net = self.postprocess(net, apply_tanh)
      return net
  
file_path: carefree-learn/cflearn/models/cv/decoder/attn.py
imports: import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from typing import Tuple
  from typing import Optional
  from .schema import DecoderMixin
  from ....modules.blocks import make_attention
  from ....modules.blocks import HijackConv2d
  from ....modules.blocks import ApplyTanhMixin
  from ....modules.blocks import ResidualBlockWithTimeEmbedding
label_desc: Use image node_id 2 for calling the AttentionDecoder obj's underlying member method code with example usage: obj.forward(net) and returns: net, net