class_docstr: Tests correctness of the DiscreteCosineTransform bijector.
code: def testBijector(self):
      bijector = discrete_cosine_transform.DiscreteCosineTransform(
          validate_args=True
      )
      self.assertStartsWith(bijector.name, "dct")
      x = np.random.randn(6, 5, 4).astype(np.float32)
      y = fftpack.dct(x, norm="ortho").astype(np.float32)
      self.assertAllClose(y, self.evaluate(bijector.forward(x)))
      self.assertAllClose(x, self.evaluate(bijector.inverse(y)))
      self.assertAllEqual(
          np.float32(0),
          self.evaluate(
              bijector.forward_log_det_jacobian(x, event_ndims=1)
          ),
      )
      self.assertAllEqual(
          np.float32(0),
          self.evaluate(
              bijector.inverse_log_det_jacobian(x, event_ndims=1)
          ),
      )
  
file_path: probability/tensorflow_probability/python/bijectors/discrete_cosine_transform_test.py
imports: import numpy
  from scipy import fftpack
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import discrete_cosine_transform
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 for calling the DiscreteCosineTransformTest obj's underlying member method code with example usage: obj.testBijector() without return types