code: def __init__(self, vocab, max_tokens=7, num_labels=2):
      super().__init__(vocab)
      self._max_tokens = max_tokens
      self.embedder = torch.nn.Embedding(vocab.get_vocab_size(), 16)
      self.linear = torch.nn.Linear(max_tokens * 16, num_labels)
      self._loss = torch.nn.CrossEntropyLoss()
  
file_path: allennlp/allennlp/common/testing/interpret_test.py
imports: from allennlp.predictors import TextClassifierPredictor
  from allennlp.models.model import Model
  import torch
label_desc: Use image node_id 1 to create a new FakeModelForTestingInterpret object from inherited base classes: Model with example: obj = FakeModelForTestingInterpret(vocab, max_tokens, num_labels)