fix test_sgld.py

blei-lab · Feb 28, 2017 · 75f878e · 75f878e
1 parent b9d3495
commit 75f878e
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Showing 3 changed files with 13 additions and 14 deletions.
diff --git a/tests/test-inferences/test_hmc.py b/tests/test-inferences/test_hmc.py
@@ -18,7 +18,7 @@ def test_normalnormal_run(self):
       mu = Normal(mu=0.0, sigma=1.0)
       x = Normal(mu=tf.ones(50) * mu, sigma=1.0)
 
-      qmu = Empirical(params=tf.Variable(tf.ones([2000])))
+      qmu = Empirical(params=tf.Variable(tf.ones(2000)))
 
       # analytic solution: N(mu=0.0, sigma=\sqrt{1/51}=0.140)
       inference = ed.HMC({mu: qmu}, data={x: x_data})

diff --git a/tests/test-inferences/test_metropolishastings.py b/tests/test-inferences/test_metropolishastings.py
@@ -18,7 +18,7 @@ def test_normalnormal_run(self):
       mu = Normal(mu=0.0, sigma=1.0)
       x = Normal(mu=tf.ones(50) * mu, sigma=1.0)
 
-      qmu = Empirical(params=tf.Variable(tf.ones([2000])))
+      qmu = Empirical(params=tf.Variable(tf.ones(2000)))
       proposal_mu = Normal(mu=0.0, sigma=1.0)
 
       # analytic solution: N(mu=0.0, sigma=\sqrt{1/51}=0.140)

diff --git a/tests/test-inferences/test_sgld.py b/tests/test-inferences/test_sgld.py
@@ -12,22 +12,21 @@
 class test_sgld_class(tf.test.TestCase):
 
   def test_normalnormal_run(self):
-    return
-    # with self.test_session() as sess:
-    #   x_data = np.array([0.0] * 50, dtype=np.float32)
+    with self.test_session() as sess:
+      x_data = np.array([0.0] * 50, dtype=np.float32)
 
-    #   mu = Normal(mu=0.0, sigma=1.0)
-    #   x = Normal(mu=tf.ones(50) * mu, sigma=1.0)
+      mu = Normal(mu=0.0, sigma=1.0)
+      x = Normal(mu=tf.ones(50) * mu, sigma=1.0)
 
-    #   qmu = Empirical(params=tf.Variable(tf.ones([5000])))
+      qmu = Empirical(params=tf.Variable(tf.ones(5000)))
 
-    #   # analytic solution: N(mu=0.0, sigma=\sqrt{1/51}=0.140)
-    #   inference = ed.SGLD({mu: qmu}, data={x: x_data})
-    #   inference.run(step_size=0.2)
+      # analytic solution: N(mu=0.0, sigma=\sqrt{1/51}=0.140)
+      inference = ed.SGLD({mu: qmu}, data={x: x_data})
+      inference.run(step_size=0.2)
 
-    #   self.assertAllClose(qmu.mean().eval(), 0, rtol=1e-2, atol=1e-2)
-    #   self.assertAllClose(qmu.std().eval(), np.sqrt(1 / 51),
-    #                       rtol=1e-2, atol=1e-2)
+      self.assertAllClose(qmu.mean().eval(), 0, rtol=1e-2, atol=1e-2)
+      self.assertAllClose(qmu.std().eval(), np.sqrt(1 / 51),
+                          rtol=2e-2, atol=2e-2)
 
 if __name__ == '__main__':
   ed.set_seed(42)