class_docstr: Common super class for decoder networks with output projection layers.
class_docstr_tok: ["Common","super","class","for","decoder","networks","with","output","projection","layers","."]
docstr: Forward pass through the decoder without output projection.
docstr_tok: ["Forward","pass","through","the","decoder","without","output","projection","."]
code: def forward_unprojected(
      self, input_tokens, encoder_out, incremental_state=None
  ):
      """Forward pass through the decoder without output projection."""
      raise NotImplementedError()
  
imports: from typing import Dict, List, Optional, Tuple
  import torch
  import torch.nn.functional
  from fairseq import utils
  from pytext.config import ConfigBase
  from pytext.models.seq_models.base import PyTextSeq2SeqModule
  from pytext.utils.usage import log_class_usage
  from torch import nn
  from .attention import DotAttention
  from .base import PlaceholderIdentity, PyTextIncrementalDecoderComponent
label_desc: Use image node_id 4 for calling the DecoderWithLinearOutputProjection obj's underlying member method code with example usage: obj.forward_unprojected(input_tokens, encoder_out, incremental_state) without return types