class_docstr: Override basic attention to account for edge case for polyencoder.
class_docstr_tok: ["Override","basic","attention","to","account","for","edge","case","for","polyencoder","."]
docstr: Forward pass.
  
  Account for accidental dimensionality reduction when num_codes is 1 and the
  polyencoder type is 'codes'
docstr_tok: ["Forward","pass",".","Account","for","accidental","dimensionality","reduction","when","num_codes","is","1","and","the","polyencoder","type","is","'codes","'"]
code: def forward(self, *args, **kwargs):
      """
      Forward pass.
  
      Account for accidental dimensionality reduction when num_codes is 1 and the
      polyencoder type is 'codes'
      """
      lhs_emb = super().forward(*args, **kwargs)
      if (
          self.poly_type == "codes"
          and self.n_codes == 1
          and len(lhs_emb.shape) == 2
      ):
          lhs_emb = lhs_emb.unsqueeze(self.dim - 1)
      return lhs_emb
  
imports: from parlai.core.params import ParlaiParser
  from typing import Any, Dict, Optional, Tuple
  import torch
  from parlai.core.opt import Opt
  from parlai.core.torch_ranker_agent import TorchRankerAgent
  from parlai.core.torch_agent import Batch
  from parlai.utils.misc import recursive_getattr
  from parlai.utils.logging import logging
  from .biencoder import AddLabelFixedCandsTRA
  from .modules import BasicAttention, MultiHeadAttention, TransformerEncoder
  from .transformer import TransformerRankerAgent
label_desc: Use image node_id 2 for calling the PolyBasicAttention obj's underlying member method code with example usage: obj.forward() and returns: lhs_emb