class_docstr: Random Forest model (scikit-learn): https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html
code: def _get_num_trees_per_estimator(self):
      # Very rough guess to size of a single tree before training
      if self.problem_type in [MULTICLASS, SOFTCLASS]:
          if self.num_classes is None:
              num_trees_per_estimator = 10  # Guess since it wasn't passed in, could also check y for a better value
          else:
              num_trees_per_estimator = self.num_classes
      else:
          num_trees_per_estimator = 1
      return num_trees_per_estimator
  
imports: import logging
  import math
  import os
  import pickle
  import sys
  import time
  import numpy
  from autogluon.common.features.types import R_BOOL, R_CATEGORY, R_FLOAT, R_INT
  from autogluon.common.utils.resource_utils import ResourceManager
  from autogluon.core.constants import MULTICLASS, QUANTILE, REGRESSION, SOFTCLASS
  from autogluon.core.models import AbstractModel
  from autogluon.core.utils.exceptions import NotEnoughMemoryError, TimeLimitExceeded
  from autogluon.core.utils.utils import normalize_pred_probas
  from autogluon.features.generators import LabelEncoderFeatureGenerator
  from .compilers.native import RFNativeCompiler
  from .compilers.onnx import RFOnnxCompiler
label_desc: Use image node_id 6 for calling the RFModel obj's underlying member method code with example usage: obj._get_num_trees_per_estimator() and returns: num_trees_per_estimator