code: def debug_ml(self, data):
      try:
          features = data[0]
          filters = data[1]
          composite_filters = data[2]
          max_depth = data[3]
          num_leaves = data[4]
          min_child_samples = data[5]
          metric = display_name_to_metric[data[6]]
          self._error_analyzer.update_metric(metric)
          tree = self._error_analyzer.compute_error_tree(
              features,
              filters,
              composite_filters,
              max_depth=max_depth,
              num_leaves=num_leaves,
              min_child_samples=min_child_samples,
          )
          return {WidgetRequestResponseConstants.DATA: tree}
      except Exception as e:
          print(e)
          traceback.print_exc()
          return {
              WidgetRequestResponseConstants.ERROR: "Failed to generate json tree representation",
              WidgetRequestResponseConstants.DATA: [],
          }
  
imports: import traceback
  import numpy
  import pandas
  from erroranalysis._internal.constants import Metrics, display_name_to_metric, metric_to_display_name
  from erroranalysis._internal.error_analyzer import ModelAnalyzer, PredictionsAnalyzer
  from erroranalysis._internal.utils import is_spark
  from raiutils.data_processing import convert_to_list, serialize_json_safe
  from raiutils.models import is_classifier
  from responsibleai._interfaces import ErrorAnalysisData
  from .constants import ModelTask
  from .error_analysis_constants import ErrorAnalysisDashboardInterface, MethodConstants
  from .error_handling import _format_exception
  from .explanation_constants import ExplanationDashboardInterface, WidgetRequestResponseConstants
label_desc: Use image node_id 10 for calling the ErrorAnalysisDashboardInput obj's underlying member method code with example usage: obj.debug_ml(data) and returns: dict, dict