code: def check_data_formats_diff(name):
      x_train, x_test, y_train, y_test = make_dataset()
      alg_results = []
      for data_format in DATA_FORMATS:
          for order in ORDERS:
              x_train_copy = convert_data(
                  x_train.copy(), data_format, order
              )
              x_test_copy = convert_data(
                  x_test.copy(), data_format, order
              )
              y_train_copy = convert_data(
                  y_train.copy(), data_format, order
              )
              alg = ESTIMATORS[name]
              alg.fit(x_train_copy, y_train_copy)
              labels = alg.predict(x_test_copy)
              alg_results.append(labels)
  
      for i in range(1, len(alg_results)):
          for j, res in enumerate(alg_results[i]):
              assert (res == alg_results[0][j]).mean() == 1, (
                  "Results are different between formats: estimator=%s"
                  % (name)
              )
  
file_path: scikit-learn-intelex/daal4py/sklearn/test/test_common.py
imports: import numpy
  import pandas
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.model_selection import train_test_split
  from daal4py.sklearn.ensemble import RandomForestClassifier
  from daal4py.sklearn.ensemble import RandomForestRegressor
  from daal4py.sklearn.neighbors import KNeighborsClassifier
label_desc: Use image node_id 3 for calling a global function with example usage: check_data_formats_diff(name) without return types