code: def is_sorted(category, reverse_order=True):
      if reverse_order:
          return np.all(category[:-1] >= category[1:])
      else:
          return np.all(category[:-1] <= category[1:])
  
imports: import numpy
  import pandas
  import pytest
  from erroranalysis._internal.cohort_filter import filter_from_cohort
  from erroranalysis._internal.constants import ARG, COLUMN, METHOD, ROW_INDEX, TRUE_Y, MatrixParams, Metrics, ModelTask, f1_metrics, metric_to_display_name, precision_metrics, recall_metrics
  from erroranalysis._internal.error_analyzer import ModelAnalyzer
  from erroranalysis._internal.matrix_filter import CATEGORY1, CATEGORY2, COUNT, FALSE_COUNT, FN, FP, INTERVAL_MAX, INTERVAL_MIN, MATRIX, METRIC_NAME, METRIC_VALUE, TN, TP, VALUES, bin_data
  from erroranalysis._internal.metrics import get_ordered_classes, is_multi_agg_metric, metric_to_func
  from rai_test_utils.datasets.tabular import create_adult_census_data, create_binary_classification_dataset, create_cancer_data, create_diabetes_data, create_housing_data, create_iris_data, create_simple_titanic_data, create_wine_data
  from rai_test_utils.models.model_utils import create_models_classification, create_models_regression
  from rai_test_utils.models.sklearn import create_kneighbors_classifier, create_titanic_pipeline
  from raiutils.exceptions import UserConfigValidationException
label_desc: Use image node_id 7 for calling a global function with example usage: is_sorted(category, reverse_order) and returns: np, np