code: def test_small_model_pt(self):
      tokenizer = AutoTokenizer.from_pretrained(
          "microsoft/DialoGPT-small"
      )
      model = AutoModelForCausalLM.from_pretrained(
          "microsoft/DialoGPT-small"
      )
      conversation_agent = ConversationalPipeline(
          model=model, tokenizer=tokenizer
      )
      conversation = Conversation("hello")
      output = conversation_agent(conversation)
      self.assertEqual(
          output,
          Conversation(
              past_user_inputs=["hello"], generated_responses=["Hi"]
          ),
      )
  
file_path: transformers/tests/pipelines/test_pipelines_conversational.py
imports: import gc
  import unittest
  from transformers import MODEL_FOR_CAUSAL_LM_MAPPING, MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, AutoModelForCausalLM, AutoModelForSeq2SeqLM, AutoTokenizer, BlenderbotSmallForConditionalGeneration, BlenderbotSmallTokenizer, Conversation, ConversationalPipeline, TFAutoModelForCausalLM, pipeline
  from transformers.testing_utils import backend_empty_cache, is_pipeline_test, is_torch_available, require_tf, require_torch, slow, torch_device
  from .test_pipelines_common import ANY
label_desc: Use image node_id 6 for calling the ConversationalPipelineTests obj's underlying member method code with example usage: obj.test_small_model_pt() without return types