code: def get_model(self, mname):
      if mname not in self.models_cache:
          self.models_cache[
              mname
          ] = FSMTForConditionalGeneration.from_pretrained(mname).to(
              torch_device
          )
          if torch_device == "cuda":
              self.models_cache[mname].half()
      return self.models_cache[mname]
  
imports: import tempfile
  import unittest
  import timeout_decorator
  from parameterized import parameterized
  from transformers import FSMTConfig, is_torch_available
  from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, require_torch_fp16, slow, torch_device
  from transformers.utils import cached_property
  from ...generation.test_utils import GenerationTesterMixin
  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 4 for calling the FSMTModelIntegrationTests obj's underlying member method code with example usage: obj.get_model(mname) and returns: self