code: def test_generic_arguments(
      framework: types.ModuleType, test_model: FrameworkTestModel
  ):
      # test that the generic save API works
      from sklearn.preprocessing import StandardScaler  # type: ignore (bad sklearn types)
  
      scaler: StandardScaler = StandardScaler().fit(  # type: ignore (bad sklearn types)
          [[4], [3], [7], [8], [4], [3], [9], [6]]
      )
      assert scaler.mean_[0] == 5.5  # type: ignore (bad sklearn types)
      assert scaler.var_[0] == 4.75  # type: ignore (bad sklearn types)
  
      kwargs = test_model.save_kwargs.copy()
      if test_model.model_signatures:
          kwargs["signatures"] = test_model.model_signatures
          meths = list(test_model.model_signatures.keys())
      else:
          default_meth = "pytest-signature-rjM5"
          kwargs["signatures"] = {
              default_meth: {"batchable": True, "batch_dim": (1, 0)}
          }
          meths = [default_meth]
      kwargs["labels"] = {
          "pytest-label-N4nr": "pytest-label-value-4mH7",
          "pytest-label-7q72": "pytest-label-value-3mDd",
      }
      kwargs["custom_objects"] = {"pytest-custom-object-r7BU": scaler}
      kwargs["metadata"] = {
          "pytest-metadata-vSW4": [0, 9, 2],
          "pytest-metadata-qJJ3": "Wy5M",
      }
      bento_model = framework.save_model(
          test_model.name,
          test_model.model,
          **kwargs,
      )
  
      for meth in meths:
          assert bento_model.info.signatures[meth] == ModelSignature.from_dict(kwargs["signatures"][meth])  # type: ignore
  
      assert bento_model.info.labels == kwargs["labels"]
      assert (
          bento_model.custom_objects["pytest-custom-object-r7BU"].mean_[
              0
          ]
          == 5.5
      )
      assert (
          bento_model.custom_objects["pytest-custom-object-r7BU"].var_[
              0
          ]
          == 4.75
      )
      assert bento_model.info.metadata == kwargs["metadata"]
  
imports: from __future__ import annotations
  import logging
  import os
  import types
  import typing
  from typing import TYPE_CHECKING
  import pytest
  import bentoml
  from bentoml._internal.models.model import ModelContext
  from bentoml._internal.models.model import ModelSignature
  from bentoml._internal.runner.runner import Runner
  from bentoml._internal.runner.runner_handle.local import LocalRunnerRef
  from bentoml._internal.runner.strategy import DefaultStrategy
  from bentoml.exceptions import NotFound
  from .models import FrameworkTestModel
label_desc: Use image node_id 5 for calling a global function with example usage: test_generic_arguments(framework, test_model) without return types