code: def _convert_lightgbm(
      model, backend, test_input, device, extra_config={}
  ):
      """
      This function is used to generate a *backend* model from a given input [LightGBM] model.
      [LightGBM]: https://lightgbm.readthedocs.io/
      """
      assert_lightgbm_installed()
  
      return _convert_sklearn(
          model, backend, test_input, device, extra_config
      )
  
imports: from copy import deepcopy
  import psutil
  import numpy
  from .operator_converters import constants
  from ._parse import parse_sklearn_api_model, parse_onnx_api_model, parse_sparkml_api_model
  from ._topology import convert
  from ._utils import assert_torch_installed, assert_lightgbm_installed, assert_xgboost_installed, pandas_installed, sparkml_installed, is_pandas_dataframe, is_spark_dataframe, tvm_installed
  from .exceptions import MissingConverter, MissingBackend
  from .supported import backends
  from sklearn.utils import all_estimators
  from sklearn.utils.validation import check_is_fitted
  from .None import operator_converters
  from .supported import xgb_operator_list
  from .supported import lgbm_operator_list
label_desc: Use image node_id 6 for calling a global function with example usage: _convert_lightgbm(model, backend, test_input, device, extra_config) and returns: _convert_sklearn