class_docstr: This is an example input baseline generator for DocNN model which uses
  word and dict features.
class_docstr_tok: ["This","is","an","example","input","baseline","generator","for","DocNN","model","which","uses","word","and","dict","features","."]
code: def _generate_baseline_single_word_feature(self, device):
      return (
          torch.tensor(
              [
                  self.vocab_word.stoi[self.PAD]
                  if hasattr(self, "vocab_word")
                  else 0
              ]
          )
          .unsqueeze(0)
          .to(device)
      )
  
imports: from collections import defaultdict
  import torch
  from pytext.models.embeddings.dict_embedding import DictEmbedding
  from pytext.models.embeddings.word_embedding import WordEmbedding
  from pytext.models.model import EmbeddingBase, EmbeddingList
label_desc: Use image node_id 3 for calling the BaselineGenerator obj's underlying member method code with example usage: obj._generate_baseline_single_word_feature(device) and returns: torch