code: def mase(y_train, y_test, y_fc, s):
      y_train_np = input_to_host_array(y_train).array
      y_test_np = input_to_host_array(y_test).array
      y_fc_np = input_to_host_array(y_fc).array
  
      diff = np.abs(y_train_np[s:] - y_train_np[:-s])
      scale = np.nanmean(diff, axis=0)
  
      error = np.abs(y_fc_np - y_test_np).mean(axis=0)
      return np.mean(error / scale)
  
imports: from cuml.testing.utils import stress_param
  from cuml.internals.input_utils import input_to_host_array
  import cuml.tsa.arima
  from cuml.internals.safe_imports import gpu_only_import
  import statsmodels.api
  from sklearn.model_selection import train_test_split
  from cuml.internals.safe_imports import cpu_only_import_from
  import warnings
  import os
  import pytest
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 4 for calling a global function with example usage: mase(y_train, y_test, y_fc, s) and returns: np