original_docstring: 
          concat before passing to the rest
          
docstring: concat before passing to the rest
docstring_tokens: concat before passing to the rest
code: def forward_embedding(self, src_tokens, src_factor_tokens):
          """
          concat before passing to the rest
          """
          x = self.embed_tokens(src_tokens)
          x = torch.cat([self.src_factor_tokens(src_factor_tokens),x],-1)
  
          x = embed = self.embed_scale * x
          if self.embed_positions is not None:
              x = embed + self.embed_positions(src_tokens)
          if self.layernorm_embedding is not None:
              x = self.layernorm_embedding(x)
          x = self.dropout_module(x)
          if self.quant_noise is not None:
              x = self.quant_noise(x)
          return x, embed
code_tokens: def forward_embedding ( self , src_tokens , src_factor_tokens ) : x = self . embed_tokens ( src_tokens ) x = torch . cat ( [ self . src_factor_tokens ( src_factor_tokens ) , x ] , - 1 ) x = embed = self . embed_scale * x if self . embed_positions is not None : x = embed + self . embed_positions ( src_tokens ) if self . layernorm_embedding is not None : x = self . layernorm_embedding ( x ) x = self . dropout_module ( x ) if self . quant_noise is not None : x = self . quant_noise ( x ) return x , embed
short_docstring: concat before passing to the rest
short_docstring_tokens: concat before passing to the rest
comment: """
          concat before passing to the rest
          """