Bugfix/issue 722 (#731)

* fix noise std issue in SGLD * use stepsizes annealing schedule of SGLD paper * make SGLD tests pass
blei-lab · Aug 10, 2017 · 79f4193 · 79f4193
1 parent de5d0ac
commit 79f4193
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Showing 2 changed files with 5 additions and 4 deletions.
diff --git a/edward/inferences/sgld.py b/edward/inferences/sgld.py
@@ -67,15 +67,16 @@ def build_update(self):
                   for z, qz in six.iteritems(self.latent_vars)}
 
     # Simulate Langevin dynamics.
-    learning_rate = self.step_size / tf.cast(self.t + 1, tf.float32)
+    learning_rate = self.step_size / tf.pow(tf.cast(self.t + 1, tf.float32),
+                                            0.55)
     grad_log_joint = tf.gradients(self._log_joint(old_sample),
                                   list(six.itervalues(old_sample)))
     sample = {}
     for z, grad_log_p in zip(six.iterkeys(old_sample), grad_log_joint):
       qz = self.latent_vars[z]
       event_shape = qz.event_shape
       normal = Normal(loc=tf.zeros(event_shape),
-                      scale=learning_rate * tf.ones(event_shape))
+                      scale=tf.sqrt(learning_rate) * tf.ones(event_shape))
       sample[z] = old_sample[z] + \
           0.5 * learning_rate * tf.convert_to_tensor(grad_log_p) + \
           normal.sample()

diff --git a/tests/test-inferences/test_sgld.py b/tests/test-inferences/test_sgld.py
@@ -22,9 +22,9 @@ def test_normalnormal_run(self):
 
       # analytic solution: N(loc=0.0, scale=\sqrt{1/51}=0.140)
       inference = ed.SGLD({mu: qmu}, data={x: x_data})
-      inference.run(step_size=0.2)
+      inference.run(step_size=0.10)
 
-      self.assertAllClose(qmu.mean().eval(), 0, rtol=1e-2, atol=1e-2)
+      self.assertAllClose(qmu.mean().eval(), 0, rtol=1e-2, atol=1.5e-2)
       self.assertAllClose(qmu.stddev().eval(), np.sqrt(1 / 51),
                           rtol=5e-2, atol=5e-2)