class_docstr: A predictor that uses a QRX model for each of the steps in the forecast
  horizon.
  
  (In other words, there's a total of prediction_length many models being
  trained. In particular, this predictor does not learn a multivariate
  distribution.) The list of these models is saved under self.model_list.
docstr: This function loads and returns the serialized model. It loads
  the predictor class with the serialized arguments. It then loads
  the trained model list by reading the pickle file.
docstr_tok: ["This","function","loads","and","returns","the","serialized","model",".","It","loads","the","predictor","class","with","the","serialized","arguments",".","It","then","loads","the","trained","model","list","by","reading","the","pickle","file","."]
code: def deserialize(cls, path: Path, **kwargs: Any) -> "TreePredictor":
      """
      This function loads and returns the serialized model. It loads
      the predictor class with the serialized arguments. It then loads
      the trained model list by reading the pickle file.
      """
  
      predictor = super().deserialize(path)
      assert isinstance(predictor, cls)
      with (path / "predictor.pkl").open("rb") as f:
          predictor.model_list = pickle.load(f)
      return predictor
  
imports: import concurrent.futures
  import logging
  import pickle
  from itertools import chain
  from typing import Iterator, List, Optional, Any, Dict
  from toolz import first
  import numpy
  import pandas
  from pathlib import Path
  from itertools import compress
  from gluonts.core.component import validated
  from gluonts.dataset.common import Dataset
  from gluonts.dataset.util import forecast_start
  from gluonts.model.forecast import Forecast
  from gluonts.model.forecast_generator import log_once
  from gluonts.model.predictor import RepresentablePredictor
  from ._model import QRF, QRX, QuantileReg
  from ._preprocess import Cardinality, PreprocessOnlyLagFeatures
  from ._types import FeatureImportanceResult, ExplanationResult
label_desc: Use image node_id 5 for calling the TreePredictor obj's underlying member method code with example usage: obj.deserialize(cls, path) and returns: predictor