class_docstr: A predictor for LightGBM models.
  
  Args:
      model: The LightGBM booster to use for predictions.
      preprocessor: A preprocessor used to transform data batches prior
          to prediction.
class_docstr_tok: ["A","predictor","for","LightGBM","models",".","Args",":","model",":","The","LightGBM","booster","to","use","for","predictions",".","preprocessor",":","A","preprocessor","used","to","transform","data","batches","prior","to","prediction","."]
code: def __repr__(self):
      return (
          f"{self.__class__.__name__}(model={self.model!r}, "
          f"preprocessor={self._preprocessor!r})"
      )
  
file_path: ray/python/ray/train/lightgbm/lightgbm_predictor.py
imports: from typing import TYPE_CHECKING, List, Optional, Union
  import lightgbm
  import pandas
  from pandas.api.types import is_object_dtype
  from ray.air.constants import TENSOR_COLUMN_NAME
  from ray.air.data_batch_type import DataBatchType
  from ray.air.util.data_batch_conversion import _unwrap_ndarray_object_type_if_needed
  from ray.train.lightgbm import LightGBMCheckpoint
  from ray.train.predictor import Predictor
  from ray.util.annotations import PublicAPI
label_desc: Use image node_id 2 for calling the LightGBMPredictor obj's underlying member method code with example usage: obj.__repr__() and returns: self, str, self, str, self, str