Fix bug in windowed_mcmc related to constrained distributions having …

…different event_shapes from unconstrained.

PiperOrigin-RevId: 390202596

tensorflow_probability/python/experimental/mcmc/windowed_sampling.py

@@ -168,8 +168,8 @@ def _get_flat_unconstraining_bijector(jd_model):
   event_space_bij = jd_model.experimental_default_event_space_bijector()
   flat_bijector = restructure.pack_sequence_as(jd_model.event_shape_tensor())
 
-  unconstrained_shapes = flat_bijector.inverse_event_shape_tensor(
-      jd_model.event_shape_tensor())
+  unconstrained_shapes = event_space_bij(
+      flat_bijector).inverse_event_shape_tensor(jd_model.event_shape_tensor())
 
   # this reshaping is required as as split can produce a tensor of shape [1]
   # when the distribution event shape is []

tensorflow_probability/python/experimental/mcmc/windowed_sampling_test.py

@@ -459,6 +459,12 @@ def mk_y(x):
     self.assertEqual((2, 64, 10, 3), states['x'].shape)
     self.assertEqual((2, 10, 1), trace['step_size'].shape)
 
+  def test_bijector(self):
+    dist = tfd.JointDistributionSequential([tfd.Dirichlet(tf.ones(2))])
+    bij, _ = windowed_sampling._get_flat_unconstraining_bijector(dist)
+    draw = dist.sample(seed=test_util.test_seed())
+    self.assertAllCloseNested(bij.inverse(bij(draw)), draw)
+
 
 @test_util.test_graph_and_eager_modes
 class WindowedSamplingStepSizeTest(test_util.TestCase):