code: def test_dynamic_cache_beam_search(self):
      tokenizer = AutoTokenizer.from_pretrained(
          "meta-llama/Llama-2-7b-hf", padding_side="left"
      )
      model = AutoModelForCausalLM.from_pretrained(
          "meta-llama/Llama-2-7b-hf",
          device_map="auto",
          torch_dtype=torch.float16,
      )
  
      inputs = tokenizer(["The best color is"], return_tensors="pt").to(
          model.device
      )
      gen_out = model.generate(
          **inputs,
          do_sample=False,
          max_new_tokens=20,
          num_beams=2,
          num_return_sequences=2,
      )
      decoded = tokenizer.batch_decode(
          gen_out, skip_special_tokens=True
      )
      expected_text = [
          "The best color is the one that makes you feel good.\nThe best color is the one that makes you feel good",
          "The best color is the one that suits you.\nThe best color is the one that suits you. The",
      ]
      self.assertListEqual(decoded, expected_text)
  
file_path: transformers/tests/test_cache_utils.py
imports: import unittest
  from transformers import set_seed
  from transformers.testing_utils import is_torch_available, require_auto_gptq, require_torch, require_torch_gpu, slow
label_desc: Use image node_id 3 for calling the CacheIntegrationTest obj's underlying member method code with example usage: obj.test_dynamic_cache_beam_search() without return types