code: def testBijectiveAndFinite(self):
      e = exp.Exp()
      sp = softplus.Softplus()
      aff = scale_matvec_diag.ScaleMatvecDiag(
          scale_diag=[2.0, 3.0, 4.0]
      )
      bijector = blockwise.Blockwise(
          bijectors=[e, sp, aff], block_sizes=[2, 1, 3]
      )
  
      x = tf.cast([0.1, 0.2, 0.3, 0.4, 0.5, 0.6], dtype=tf.float32)
      x = tf1.placeholder_with_default(x, shape=x.shape)
      # Identity to break the caching.
      blockwise_y = tf.identity(bijector.forward(x))
  
      bijector_test_util.assert_bijective_and_finite(
          bijector,
          x=self.evaluate(x),
          y=self.evaluate(blockwise_y),
          eval_func=self.evaluate,
          event_ndims=1,
      )
  
imports: from absl.testing import parameterized
  import mock
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import blockwise
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import inline
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import scale_matvec_diag
  from tensorflow_probability.python.bijectors import softmax_centered
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 3 for calling the BlockwiseBijectorTest obj's underlying member method code with example usage: obj.testBijectiveAndFinite() without return types