Fix bug in tensorflow tests. (ray-project#218)

* Fix bug in tensorflow tests.

* Address comment.

test/tensorflow_test.py

@@ -86,7 +86,7 @@ def testVariableNameCollision(self):
 
     ray.env.net1 = ray.EnvironmentVariable(net_vars_initializer, net_vars_reinitializer)
     ray.env.net2 = ray.EnvironmentVariable(net_vars_initializer, net_vars_reinitializer)
-    
+
     net_vars1, init1, sess1 = ray.env.net1
     net_vars2, init2, sess2 = ray.env.net2
 
@@ -108,7 +108,7 @@ def testNetworksIndependent(self):
 
     ray.env.net1 = ray.EnvironmentVariable(net_vars_initializer, net_vars_reinitializer)
     ray.env.net2 = ray.EnvironmentVariable(net_vars_initializer, net_vars_reinitializer)
-    
+
     net_vars1, init1, sess1 = ray.env.net1
     net_vars2, init2, sess2 = ray.env.net2
 
@@ -117,41 +117,32 @@ def testNetworksIndependent(self):
     sess2.run(init2)
 
     @ray.remote
-    def get_vars1():
-      return ray.env.net1[0].get_weights()
-
-    @ray.remote
-    def get_vars2():
-      return ray.env.net2[0].get_weights()
-
-    @ray.remote
-    def set_vars1(weights):
-      ray.env.net1[0].set_weights(weights)
-
-    @ray.remote
-    def set_vars2(weights):
-      ray.env.net2[0].set_weights(weights)
-
-    # Get the weights.
+    def set_and_get_weights(weights1, weights2):
+      ray.env.net1[0].set_weights(weights1)
+      ray.env.net2[0].set_weights(weights2)
+      return ray.env.net1[0].get_weights(), ray.env.net2[0].get_weights()
+
+    # Make sure the two networks have different weights. TODO(rkn): Note that
+    # equality comparisons of numpy arrays normally does not work. This only
+    # works because at the moment they have size 1.
     weights1 = net_vars1.get_weights()
     weights2 = net_vars2.get_weights()
     self.assertNotEqual(weights1, weights2)
 
-    # Swap the weights.
-    set_vars2.remote(weights1)
-    set_vars1.remote(weights2)
-
-    # Get the new weights.
-    new_weights1 = ray.get(get_vars1.remote())
-    new_weights2 = ray.get(get_vars2.remote())
-    self.assertNotEqual(new_weights1, new_weights2)
+    # Set the weights and get the weights, and make sure they are unchanged.
+    new_weights1, new_weights2 = ray.get(set_and_get_weights.remote(weights1, weights2))
+    self.assertEqual(weights1, new_weights1)
+    self.assertEqual(weights2, new_weights2)
 
-    # Check that the weights were swapped.
-    self.assertEqual(weights1, new_weights2)
-    self.assertEqual(weights2, new_weights1)
+    # Swap the weights.
+    new_weights2, new_weights1 = ray.get(set_and_get_weights.remote(weights2, weights1))
+    self.assertEqual(weights1, new_weights1)
+    self.assertEqual(weights2, new_weights2)
 
     ray.worker.cleanup()
 
+  # This test creates an additional network on the driver so that the tensorflow
+  # variables on the driver and the worker differ.
   def testNetworkDriverWorkerIndependent(self):
     ray.init(num_workers=1)
 
@@ -167,23 +158,15 @@ def testNetworkDriverWorkerIndependent(self):
     net_vars2, init2, sess2 = ray.env.net
     sess2.run(init2)
 
-    # Get the weights.
-    weights1 = net_vars1.get_weights()
     weights2 = net_vars2.get_weights()
-    self.assertNotEqual(weights1, weights2)
-
-    # Swap the weights.
-    net_vars1.set_weights(weights2)
-    net_vars2.set_weights(weights1)
 
-    # Get the new weights.
-    new_weights1 = net_vars1.get_weights()
-    new_weights2 = net_vars2.get_weights()
-    self.assertNotEqual(new_weights1, new_weights2)
+    @ray.remote
+    def set_and_get_weights(weights):
+      ray.env.net[0].set_weights(weights)
+      return ray.env.net[0].get_weights()
 
-    # Check that the weights were swapped.
-    self.assertEqual(weights1, new_weights2)
-    self.assertEqual(weights2, new_weights1)
+    new_weights2 = ray.get(set_and_get_weights.remote(net_vars2.get_weights()))
+    self.assertEqual(weights2, new_weights2)
 
     ray.worker.cleanup()