class_docstr: XGBoost model configuration
  
  Reference: https://xgboost.readthedocs.io/en/stable/parameter.html
  
  Parameters
  ----------
  max_depth : int
      The maximum depth.
  gamma : float
      The gamma.
  min_child_weight : float
      The minimum child weight.
  eta : float
      The eta, learning rate.
  seed : int
      The random seed.
  nthread : Optional[int],
      The number of threads to use.
      Default is None, which means to use physical number of cores.
  tree_method : Literal["auto", "exact", "approx", "hist", "gpu_hist"]
      The tree construction algorithm used in XGBoost.
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docstr: Convert to dict
docstr_tok: ["Convert","to","dict"]
code: def to_dict(self):
      """Convert to dict"""
  
      return {
          "max_depth": self.max_depth,
          "gamma": self.gamma,
          "min_child_weight": self.min_child_weight,
          "eta": self.eta,
          "seed": self.seed,
          "nthread": self.nthread,
          "tree_method": self.tree_method,
      }
  
imports: import os
  import tempfile
  from collections import OrderedDict
  from itertools import chain
  from typing import TYPE_CHECKING, Any, Callable, Dict, List, NamedTuple, Optional, Tuple
  from typing_extensions import Literal
  import numpy
  from ...contrib.tar import tar, untar
  from ...runtime import NDArray
  from ..cost_model import PyCostModel
  from ..feature_extractor import FeatureExtractor
  from ..logging import get_logger
  from ..runner import RunnerResult
  from ..search_strategy import MeasureCandidate
  from ..utils import cpu_count, derived_object, shash2hex
  from .metric import max_curve
label_desc: Use image node_id 1 for calling the XGBConfig obj's underlying member method code with example usage: obj.to_dict() and returns: dict