class_docstr: Assumes you want to completely ignore the output of a `TokenIndexer` for some reason, and does
  not return anything when asked to embed it.
  
  You should almost never need to use this; normally you would just not use a particular
  `TokenIndexer`. It's only in very rare cases, like simplicity in data processing for language
  modeling (where we use just one `TextField` to handle input embedding and computing target ids),
  where you might want to use this.
  
  Registered as a `TokenEmbedder` with name "empty".
class_docstr_tok: ["Assumes","you","want","to","completely","ignore","the","output","of","a","`","TokenIndexer","`","for","some","reason",",","and","does","not","return","anything","when","asked","to","embed","it",".","You","should","almost","never","need","to","use","this",";","normally","you","would","just","not","use","a","particular","`","TokenIndexer","`",".","It","'s","only","in","very","rare","cases",",","like","simplicity","in","data","processing","for","language","modeling","(","where","we","use","just","one","`","TextField","`","to","handle","input","embedding","and","computing","target","ids",")",",","where","you","might","want","to","use","this",".","Registered","as","a","`","TokenEmbedder","`","with","name","``","empty","''","."]
code: def forward(self, *inputs, **kwargs) -> torch.Tensor:
      return None
  
imports: import torch
  from allennlp.modules.token_embedders.token_embedder import TokenEmbedder
label_desc: Use image node_id 3 for calling the EmptyEmbedder obj's underlying member method code with example usage: obj.forward() and returns: None