docstr: Simple test that checks if the quantized model is working properly with multiple GPUs
docstr_tok: ["Simple","test","that","checks","if","the","quantized","model","is","working","properly","with","multiple","GPUs"]
code: def test_quantized_model_no_k_proj_quantized(self):
      """
      Simple test that checks if the quantized model is working properly with multiple GPUs
      """
      dummy_input = torch.LongTensor([[0, 1, 0]]).to(torch_device)
  
      quantized_model = AutoModelForCausalLM.from_pretrained(
          self.model_with_no_k_proj_quantized
      ).to(torch_device)
  
      self.assertTrue(
          isinstance(
              quantized_model.model.decoder.layers[0].self_attn.k_proj,
              torch.nn.Linear,
          )
      )
      self.assertFalse(
          isinstance(
              quantized_model.model.decoder.layers[0].self_attn.v_proj,
              torch.nn.Linear,
          )
      )
  
      EXPECTED_OUTPUT = torch.LongTensor(
          [
              [
                  0,
                  1,
                  0,
                  50118,
                  50118,
                  133,
                  248,
                  12,
                  134,
                  16,
                  10,
                  372,
                  2031,
              ]
          ]
      ).to(torch_device)
  
      output = quantized_model.generate(dummy_input, max_new_tokens=10)
      self.assertTrue((EXPECTED_OUTPUT == output).all())
  
imports: import gc
  import tempfile
  import unittest
  from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, AwqConfig, OPTForCausalLM
  from transformers.testing_utils import require_accelerate, require_auto_awq, require_torch_gpu, require_torch_multi_gpu, slow, torch_device
  from transformers.utils import is_accelerate_available, is_torch_available
label_desc: Use image node_id 10 for calling the AwqTest obj's underlying member method code with example usage: obj.test_quantized_model_no_k_proj_quantized() without return types