class_docstr: A predictor for XGBoost models.
  
  Args:
      model: The XGBoost booster to use for predictions.
      preprocessor: A preprocessor used to transform data batches prior
          to prediction.
docstr: Instantiate the predictor from a Checkpoint.
  
  This is a helper constructor that instantiates the predictor from a
  framework-specific XGBoost checkpoint.
  
  Args:
      checkpoint: The checkpoint to load the model and preprocessor from.
docstr_tok: ["Instantiate","the","predictor","from","a","Checkpoint",".","This","is","a","helper","constructor","that","instantiates","the","predictor","from","a","framework-specific","XGBoost","checkpoint",".","Args",":","checkpoint",":","The","checkpoint","to","load","the","model","and","preprocessor","from","."]
code: def from_checkpoint(
      cls, checkpoint: XGBoostCheckpoint
  ) -> "XGBoostPredictor":
      """Instantiate the predictor from a Checkpoint.
  
      This is a helper constructor that instantiates the predictor from a
      framework-specific XGBoost checkpoint.
  
      Args:
          checkpoint: The checkpoint to load the model and preprocessor from.
  
      """
      model = checkpoint.get_model()
      preprocessor = checkpoint.get_preprocessor()
      return cls(model=model, preprocessor=preprocessor)
  
file_path: ray/python/ray/train/xgboost/xgboost_predictor.py
imports: from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
  import pandas
  import xgboost
  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.predictor import Predictor
  from ray.train.xgboost import XGBoostCheckpoint
  from ray.util.annotations import PublicAPI
label_desc: Use image node_id 3 for calling the XGBoostPredictor obj's underlying member method code with example usage: obj.from_checkpoint(cls, checkpoint) and returns: cls