class_docstr: A Luong-style attention that also includes the inner product of targets-lookup.
code: def forward(
      self,
      *,
      memories: torch.Tensor,
      memories_length: torch.Tensor,
      lookup_vectors: torch.Tensor,
  ) -> torch.Tensor:
      # memories: [B, max-inp-len, H]
      # memories_length: [B]
      # look_up_vectors: [B, max-out-len, D]
      return self.forward_with_attention_vec(
          memories=memories,
          memories_length=memories_length,
          lookup_vectors=lookup_vectors,
      )[0]
  
file_path: ptgnn/ptgnn/neuralmodels/sequence/luongattention.py
imports: import math
  import torch
  from torch import nn
label_desc: Use image node_id 2 for calling the LuongAttentionModule obj's underlying member method code with example usage: obj.forward() and returns: self