class_docstr: VowpalWabbit Model: https://vowpalwabbit.org/
  
  VowpalWabbit Command Line args: https://github.com/VowpalWabbit/vowpal_wabbit/wiki/Command-line-arguments
class_docstr_tok: ["VowpalWabbit","Model",":","https",":","\/\/vowpalwabbit.org\/","VowpalWabbit","Command","Line","args",":","https",":","\/\/github.com\/VowpalWabbit\/vowpal_wabbit\/wiki\/Command-line-arguments"]
docstr: There are two files which needs to be loaded.
  First is the Abstract Model pickle dump and second is the internal model file.
  For VW, based on different problem_type/hyperparams, loading arguments will be different
docstr_tok: ["There","are","two","files","which","needs","to","be","loaded",".","First","is","the","Abstract","Model","pickle","dump","and","second","is","the","internal","model","file",".","For","VW",",","based","on","different","problem_type\/hyperparams",",","loading","arguments","will","be","different"]
code: def load(cls, path: str, reset_paths=True, verbose=True):
      """
      There are two files which needs to be loaded.
      First is the Abstract Model pickle dump and second is the internal model file.
      For VW, based on different problem_type/hyperparams, loading arguments will be different
      """
      try_import_vowpalwabbit()
      import vowpalwabbit
  
      # Load Abstract Model. This is without the internal model
      model = super().load(
          path, reset_paths=reset_paths, verbose=verbose
      )
      params = model._get_model_params()
      # Load the internal model file
      if model._load_model:
          file_path = os.path.join(path, cls.model_internals_file_name)
  
          model_load_params = f" -i {file_path} --quiet"
          if model.problem_type in PROBLEM_TYPES_CLASSIFICATION:
              model_load_params += (
                  " --probabilities --loss_function=logistic"
              )
          if params["sparse_weights"]:
              model_load_params += " --sparse_weights"
  
          model.model = vowpalwabbit.Workspace(model_load_params)
      model._load_model = None
      return model
  
imports: import logging
  import os
  import time
  import numpy
  import pandas
  from autogluon.common.features.types import R_CATEGORY, R_FLOAT, R_INT, R_OBJECT, S_IMAGE_PATH, S_TEXT_AS_CATEGORY, S_TEXT_NGRAM, S_TEXT_SPECIAL
  from autogluon.common.utils.try_import import try_import_vowpalwabbit
  from autogluon.core.constants import BINARY, MULTICLASS, PROBLEM_TYPES_CLASSIFICATION, PROBLEM_TYPES_REGRESSION, REGRESSION
  from autogluon.core.models import AbstractModel
  from autogluon.core.utils.exceptions import TimeLimitExceeded
  from .vowpalwabbit_utils import VWFeaturesConverter
label_desc: Use image node_id 8 for calling the VowpalWabbitModel obj's underlying member method code with example usage: obj.load(cls, path, reset_paths, verbose) and returns: model