class_docstr: Defines the ErrorAnalysisManager for discovering errors in a model.
class_docstr_tok: ["Defines","the","ErrorAnalysisManager","for","discovering","errors","in","a","model","."]
docstr: Creates an ErrorReport by running the error analyzer on the model.
          
docstr_tok: ["Creates","an","ErrorReport","by","running","the","error","analyzer","on","the","model","."]
code: def compute(self):
      """Creates an ErrorReport by running the error analyzer on the model."""
      print("Error Analysis")
      print("Current Status: Generating error analysis reports.")
      compute_importances = not any(
          _find_features_having_missing_values(self._dataset)
      )
      if not compute_importances:
          warnings.warn(
              "Test dataset has missing values, "
              "skipping feature importance computation in error analysis."
          )
      for config in self._ea_config_list:
          if config.is_computed:
              continue
          config.is_computed = True
          max_depth = config.max_depth
          num_leaves = config.num_leaves
          min_child_samples = config.min_child_samples
          filter_features = config.filter_features
          report = self._analyzer.create_error_report(
              filter_features,
              max_depth=max_depth,
              min_child_samples=min_child_samples,
              num_leaves=num_leaves,
              compute_importances=compute_importances,
              compute_root_stats=True,
          )
  
          # Validate the serialized output against schema
          schema = ErrorAnalysisManager._get_error_analysis_schema()
          jsonschema.validate(json.loads(report.to_json()), schema)
  
          self._ea_report_list.append(report)
      print(
          "Current Status: Finished generating error analysis reports."
      )
  
imports: import json
  import warnings
  from pathlib import Path
  from typing import Any, List, Optional
  import jsonschema
  import pandas
  from erroranalysis._internal.constants import metric_to_display_name
  from erroranalysis._internal.error_analyzer import ModelAnalyzer
  from erroranalysis._internal.error_report import as_error_report
  from erroranalysis._internal.error_report import json_converter
  from raiutils.exceptions import UserConfigValidationException
  from raiutils.models import ModelTask
  from responsibleai._config.base_config import BaseConfig
  from responsibleai._interfaces import ErrorAnalysisData
  from responsibleai._internal.constants import ErrorAnalysisManagerKeys
  from responsibleai._internal.constants import FileFormats, ListProperties, ManagerNames
  from responsibleai._tools.shared.state_directory_management import DirectoryManager
  from responsibleai.exceptions import ConfigAndResultMismatchException, DuplicateManagerConfigException
  from responsibleai.managers.base_manager import BaseManager
  from responsibleai.utils import _find_features_having_missing_values, _measure_time
label_desc: Use image node_id 3 for calling the ErrorAnalysisManager obj's underlying member method code with example usage: obj.compute() without return types