code: def test_ActivationRegularizationLoss(alpha: float):
      ar = ActivationRegularizationLoss(alpha, batch_axis=0)
      inputs = [
          nd.arange(1000).reshape(10, 10, 10),
          nd.arange(1000).reshape(10, 10, 10),
          nd.arange(1000).reshape(10, 10, 10),
      ]
      ar_result = ar(*inputs)
      outputs = [
          alpha * nd.mean((array * array), axis=0, exclude=True)
          for array in inputs
      ]
      assert np.isclose(
          nd.add_n(*outputs).asnumpy(), ar_result.asnumpy()
      ).all()
  
imports: import numpy
  import pytest
  from mxnet import nd
  from gluonts.mx.block.regularization import ActivationRegularizationLoss, TemporalActivationRegularizationLoss
label_desc: Use image node_id 1 for calling a global function with example usage: test_ActivationRegularizationLoss(alpha) without return types