add test to verify debug=True works

edward/inferences/inference.py

@@ -231,7 +231,7 @@ def update(self, feed_dict=None):
     t = sess.run(self.increment_t)
 
     if self.debug:
-      sess.run(self.op_check)
+      sess.run(self.op_check, feed_dict)
 
     if self.logging and self.n_print != 0:
       if t == 1 or t % self.n_print == 0:

tests/test-inferences/test_inference_debug.py

@@ -0,0 +1,41 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import edward as ed
+import numpy as np
+import tensorflow as tf
+
+from edward.models import Normal
+
+
+class test_inference_debug_class(tf.test.TestCase):
+
+  def test_placeholder(self):
+    with self.test_session():
+      N = 5
+      mu = Normal(loc=0.0, scale=1.0)
+      x = Normal(loc=tf.ones(N) * mu, scale=tf.ones(N))
+
+      qmu = Normal(loc=tf.Variable(0.0), scale=tf.constant(1.0))
+
+      x_ph = tf.placeholder(tf.float32, [N])
+      inference = ed.KLqp({mu: qmu}, data={x: x_ph})
+      inference.initialize(debug=True)
+      tf.global_variables_initializer().run()
+      inference.update(feed_dict={x_ph: np.zeros(N, np.float32)})
+
+  def test_tensor(self):
+    with self.test_session():
+      N = 5
+      mu = Normal(loc=0.0, scale=1.0)
+      x = Normal(loc=tf.ones(N) * mu, scale=tf.ones(N))
+
+      qmu = Normal(loc=tf.Variable(0.0), scale=tf.constant(1.0))
+
+      x_data = tf.zeros(N)
+      inference = ed.KLqp({mu: qmu}, data={x: x_data})
+      inference.run(n_iter=1, debug=True)
+
+if __name__ == '__main__':
+  tf.test.main()

tests/test-inferences/test_scale.py → tests/test-inferences/test_inference_scale.py

@@ -21,8 +21,7 @@ def test_scale_0d(self):
       qmu = Normal(loc=tf.Variable(0.0), scale=tf.constant(1.0))
 
       x_ph = tf.placeholder(tf.float32, [M])
-      data = {x: x_ph}
-      inference = ed.KLqp({mu: qmu}, data)
+      inference = ed.KLqp({mu: qmu}, data={x: x_ph})
       inference.initialize(scale={x: float(N) / M})
       self.assertAllEqual(inference.scale[x], float(N) / M)