class_docstr: Performs a common operation (embedding) that won't work on an empty tensor.
  Returns an arbitrary loss.
class_docstr_tok: ["Performs","a","common","operation","(","embedding",")","that","wo","n't","work","on","an","empty","tensor",".","Returns","an","arbitrary","loss","."]
code: def forward(  # type: ignore
      self, list_tensor: Dict[str, torch.LongTensor]
  ) -> Dict[str, torch.Tensor]:
      self.embedder(list_tensor)
      return {"loss": 1.0}
  
imports: from typing import Dict
  import numpy
  import torch
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.data import Token, Vocabulary, Instance
  from allennlp.data.fields import TextField, LabelField, ListField, IndexField, SequenceLabelField
  from allennlp.data.token_indexers import SingleIdTokenIndexer, TokenCharactersIndexer
  from allennlp.data.data_loaders import SimpleDataLoader
  from allennlp.data.tokenizers import SpacyTokenizer
  from allennlp.models import Model
  from allennlp.modules import Embedding
  from allennlp.modules.text_field_embedders import BasicTextFieldEmbedder
label_desc: Use image node_id 2 for calling the DummyModel obj's underlying member method code with example usage: obj.forward(list_tensor) and returns: dict