code: def test_inference_casual(self):
      texts = "今天天气真好！"
      model_path = "openbmb/cpm-ant-10b"
      model = CpmAntForCausalLM.from_pretrained(model_path)
      tokenizer = CpmAntTokenizer.from_pretrained(model_path)
      inputs = tokenizer(texts, return_tensors="pt")
      hidden_states = model(**inputs).logits
  
      expected_slice = torch.tensor(
          [
              [
                  [-6.4267, -6.4083, -6.3958],
                  [-5.8802, -5.9447, -5.7811],
                  [-5.3896, -5.4820, -5.4295],
              ]
          ],
      )
      self.assertTrue(
          torch.allclose(
              hidden_states[:, :3, :3], expected_slice, atol=1e-2
          )
      )
  
imports: import unittest
  from transformers.testing_utils import is_torch_available, require_torch, tooslow
  from ...generation.test_utils import torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 for calling the CpmAntForCausalLMlIntegrationTest obj's underlying member method code with example usage: obj.test_inference_casual() without return types