code: def testGEVShape(self):
      loc = np.array([3.0] * 5, dtype=self._dtype)
      scale = np.array([3.0] * 5, dtype=self._dtype)
      conc = np.array([3.0] * 5, dtype=self._dtype)
      dist = gev.GeneralizedExtremeValue(
          loc=loc, scale=scale, concentration=conc, validate_args=True
      )
  
      self.assertEqual((5,), self.evaluate(dist.batch_shape_tensor()))
      self.assertEqual(tf.TensorShape([5]), dist.batch_shape)
      self.assertAllEqual([], self.evaluate(dist.event_shape_tensor()))
      self.assertEqual(tf.TensorShape([]), dist.event_shape)
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import gev
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 2 for calling the _GEVTest obj's underlying member method code with example usage: obj.testGEVShape() without return types