class_docstr: Defines the top-level Model Analysis API.
  Use RAIInsights to analyze errors, explain the most important
  features, compute counterfactuals and run causal analysis in a
  single API.
class_docstr_tok: ["Defines","the","top-level","Model","Analysis","API",".","Use","RAIInsights","to","analyze","errors",",","explain","the","most","important","features",",","compute","counterfactuals","and","run","causal","analysis","in","a","single","API","."]
docstr: Store the model output on a suitable field.
  
  :param model_method: the method to use to produce the model output
  :type model_method: ModelMethod
  :param input_data: the data to pass to the model
  :type input_data: Union[pd.DataFrame, np.array]
  :param large: whether or not the output is based on a large (full)
      dataset
  :type large: boolean
docstr_tok: ["Store","the","model","output","on","a","suitable","field",".",":","param","model_method",":","the","method","to","use","to","produce","the","model","output",":","type","model_method",":","ModelMethod",":","param","input_data",":","the","data","to","pass","to","the","model",":","type","input_data",":","Union","[","pd.DataFrame",",","np.array","]",":","param","large",":","whether","or","not","the","output","is","based","on","a","large","(","full",")","dataset",":","type","large",":","boolean"]
code: def _set_model_output(self, *, model_method, input_data, large=False):
      """Store the model output on a suitable field.
  
      :param model_method: the method to use to produce the model output
      :type model_method: ModelMethod
      :param input_data: the data to pass to the model
      :type input_data: Union[pd.DataFrame, np.array]
      :param large: whether or not the output is based on a large (full)
          dataset
      :type large: boolean
      """
      field_name = (
          f"_{'large_' if large else ''}{model_method.name}_output"
      )
      try:
          method = getattr(self.model, model_method.name)
      except AttributeError as err:
          if model_method.optional:
              setattr(self, field_name, None)
              return
          else:
              raise ValueError(
                  f"The model is expected to have a {model_method.name} "
                  "method,"
              ) from err
      setattr(self, field_name, method(input_data))
  
imports: import json
  import pickle
  import warnings
  from enum import Enum
  from pathlib import Path
  from typing import Any, List, Optional, Union
  import numpy
  import pandas
  from erroranalysis._internal.cohort_filter import FilterDataWithCohortFilters
  from erroranalysis._internal.process_categoricals import process_categoricals
  from raiutils.data_processing import convert_to_list
  from raiutils.exceptions import SystemErrorException, UserConfigValidationException
  from raiutils.models import Forecasting, ModelTask, SKLearn
  from responsibleai._interfaces import Dataset, RAIInsightsData, TabularDatasetMetadata
  from responsibleai._internal._forecasting_wrappers import _wrap_model
  from responsibleai._internal.constants import FileFormats, ManagerNames, Metadata, SerializationAttributes
  from responsibleai.feature_metadata import FeatureMetadata
  from responsibleai.managers.causal_manager import CausalManager
  from responsibleai.managers.counterfactual_manager import CounterfactualManager
  from responsibleai.managers.data_balance_manager import DataBalanceManager
  from responsibleai.managers.error_analysis_manager import ErrorAnalysisManager
  from responsibleai.managers.explainer_manager import ExplainerManager
  from responsibleai.rai_insights.rai_base_insights import RAIBaseInsights
label_desc: Use image node_id 32 for calling the RAIInsights obj's underlying member method code with example usage: obj._set_model_output() without return types