class_docstr: Simple linear projection from the hidden vector to
  vocab.
class_docstr_tok: ["Simple","linear","projection","from","the","hidden","vector","to","vocab","."]
code: def forward(
      self,
      encoder_out: Dict[str, Tensor],
      decoder_out: Tuple[Tensor, Dict[str, Tensor]],
      incremental_state: Optional[Dict[str, Tensor]] = None,
  ):
      x, others = decoder_out
      logits = self.linear_projection(x)
      return logits, others
  
file_path: pytext/pytext/models/seq_models/projection_layers.py
imports: from typing import Dict, Optional, Tuple
  import torch
  import torch.nn.functional
  from pytext.models.seq_models.utils import Linear
  from torch import nn, Tensor
  from .attention import DecoupledMultiheadAttention
  from .utils import verify_encoder_out
label_desc: Use image node_id 3 for calling the DecoderWithLinearOutputProjection obj's underlying member method code with example usage: obj.forward(encoder_out, decoder_out, incremental_state) and returns: logits,  others