code: def save_state_dict(state_dict, path, **kwargs):
      """
      Save a state_dict to a path on the local file system
  
      :param state_dict: state_dict to be saved.
      :param path: Local path where the state_dict is to be saved.
      :param kwargs: kwargs to pass to ``torch.save``.
      """
      import torch
  
      # The object type check here aims to prevent a scenario where a user accidentally passees
      # a model instead of a state_dict and `torch.save` (which accepts both model and state_dict)
      # successfully completes, leaving the user unaware of the mistake.
      if not isinstance(state_dict, dict):
          raise TypeError(
              "Invalid object type for `state_dict`: {}. Must be an instance of `dict`".format(
                  type(state_dict)
              )
          )
  
      os.makedirs(path, exist_ok=True)
      state_dict_path = os.path.join(path, _TORCH_STATE_DICT_FILE_NAME)
      torch.save(state_dict, state_dict_path, **kwargs)
  
imports: import atexit
  import importlib
  import logging
  import os
  import posixpath
  import shutil
  import warnings
  from functools import partial
  from typing import Any, Dict, Optional
  import numpy
  import pandas
  import yaml
  from packaging.version import Version
  import mlflow
  from mlflow import pyfunc
  from mlflow.environment_variables import MLFLOW_DEFAULT_PREDICTION_DEVICE
  from mlflow.exceptions import MlflowException
  from mlflow.ml_package_versions import _ML_PACKAGE_VERSIONS
  from mlflow.models import Model, ModelSignature
  from mlflow.models.model import MLMODEL_FILE_NAME
  from mlflow.models.signature import _infer_signature_from_input_example
  from mlflow.models.utils import ModelInputExample, _save_example
  from mlflow.protos.databricks_pb2 import RESOURCE_DOES_NOT_EXIST
  from mlflow.pytorch import pickle_module
  from mlflow.tracking._model_registry import DEFAULT_AWAIT_MAX_SLEEP_SECONDS
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.utils.autologging_utils import autologging_integration, safe_patch
  from mlflow.utils.docstring_utils import LOG_MODEL_PARAM_DOCS, format_docstring
  from mlflow.utils.environment import _CONDA_ENV_FILE_NAME, _CONSTRAINTS_FILE_NAME, _PYTHON_ENV_FILE_NAME, _REQUIREMENTS_FILE_NAME, _mlflow_conda_env, _process_conda_env, _process_pip_requirements, _PythonEnv, _validate_env_arguments
  from mlflow.utils.file_utils import TempDir, get_total_file_size, write_to
  from mlflow.utils.model_utils import _add_code_from_conf_to_system_path, _get_flavor_configuration, _validate_and_copy_code_paths, _validate_and_prepare_target_save_path
  from mlflow.utils.requirements_utils import _get_pinned_requirement
label_desc: Use image node_id 9 for calling a global function with example usage: save_state_dict(state_dict, path) without return types