class_docstr: Test if the PeftModel behaves as expected. This includes:
  - test if the model has the expected methods
  
  We use parametrized.expand for debugging purposes to test each model individually.
class_docstr_tok: ["Test","if","the","PeftModel","behaves","as","expected",".","This","includes",":","-","test","if","the","model","has","the","expected","methods","We","use","parametrized.expand","for","debugging","purposes","to","test","each","model","individually","."]
code: def prepare_inputs_for_testing(self):
      input_ids = torch.tensor([[1, 1, 1], [1, 2, 1]]).to(
          self.torch_device
      )
      attention_mask = torch.tensor([[1, 1, 1], [1, 0, 1]]).to(
          self.torch_device
      )
  
      input_dict = {
          "input_ids": input_ids,
          "attention_mask": attention_mask,
      }
  
      return input_dict
  
imports: import unittest
  import torch
  from parameterized import parameterized
  from transformers import AutoModel
  from peft import PrefixTuningConfig, PromptLearningConfig
  from .testing_common import PeftCommonTester, PeftTestConfigManager
label_desc: Use image node_id 1 for calling the PeftFeatureExtractionModelTester obj's underlying member method code with example usage: obj.prepare_inputs_for_testing() and returns: input_dict