add simple unit test

edward/inferences/implicit_klqp.py

@@ -54,7 +54,7 @@ def __init__(self, latent_vars, data=None, discriminator=None,
     necessary as the discriminator can take an arbitrary set of data,
     latent, and global variables.
 
-    Note the type for ``discriminator``'s output change when one
+    Note the type for ``discriminator``'s output changes when one
     passes in the ``scale`` argument to ``initialize()``.
 
     + If ``scale`` has at most one item, then ``discriminator``

tests/test-inferences/test_implicitklqp.py

@@ -0,0 +1,47 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import edward as ed
+import tensorflow as tf
+
+from edward.models import Normal
+from tensorflow.contrib import slim
+
+
+class test_implicit_klqp_class(tf.test.TestCase):
+
+  def test_normal_run(self):
+    def ratio_estimator(data, local_vars, global_vars):
+      input = tf.reshape(local_vars[z], [1, 1])  # reshape scalar as matrix
+      h1 = slim.fully_connected(input, 10, activation_fn=tf.nn.relu)
+      h2 = slim.fully_connected(h1, 1, activation_fn=None)
+      return h2
+
+    with self.test_session() as sess:
+      z = Normal(mu=5.0, sigma=1.0)
+
+      qz = Normal(mu=tf.Variable(tf.random_normal([])),
+                  sigma=tf.nn.softplus(tf.Variable(tf.random_normal([]))))
+
+      inference = ed.ImplicitKLqp({z: qz}, discriminator=ratio_estimator)
+      # inference.run(n_iter=1000)
+      inference.initialize(n_iter=1000, n_print=100)
+
+      sess = ed.get_session()
+      tf.global_variables_initializer().run()
+
+      for _ in range(inference.n_iter):
+        info_dict = inference.update()
+        t = info_dict['t']
+        inference.print_progress(info_dict)
+        if t == 1 or t % inference.n_print == 0:
+          # Check inferred posterior parameters.
+          mean, std = sess.run([qz.mean(), qz.std()])
+          print("Inferred mean & std: {} {}".format(mean, std))
+
+      self.assertAllClose(qz.mean().eval(), 5.0, atol=1.0)
+
+if __name__ == '__main__':
+  ed.set_seed(47324)
+  tf.test.main()