code: def test_drop_block(self):
      test_input = np.ones((2, 100, 100, 1))
      dropblock_layer = layers.DropBlock(
          keep_proba=0.9, block_size=(2, 10)
      )
      output = dropblock_layer.output(test_input, training=True)
      actual_output = self.eval(output)
  
      fraction_masked = np.mean(actual_output != 0)
  
      self.assertTrue(0.88 <= fraction_masked <= 0.92)
      self.assertGreater(actual_output.max(), 1)
      self.assertAlmostEqual(
          actual_output.max(),
          1 / fraction_masked,
      )
  
imports: from scipy import stats
  import numpy
  from neupy import layers
  from neupy.exceptions import LayerConnectionError
  from base import BaseTestCase
label_desc: Use image node_id 1 for calling the DropBlockTestCase obj's underlying member method code with example usage: obj.test_drop_block() without return types