add assertion to test in mpi_adam; fix trpo_mpi failure without MPI on cartpole

baselines/common/mpi_adam.py

@@ -26,11 +26,13 @@ class MpiAdam(object):
         if self.t % 100 == 0:
             self.check_synced()
         localg = localg.astype('float32')
-        globalg = np.zeros_like(localg)
         if self.comm is not None:
+            globalg = np.zeros_like(localg)
             self.comm.Allreduce(localg, globalg, op=MPI.SUM)
-        if self.scale_grad_by_procs:
-            globalg /= self.comm.Get_size()
+            if self.scale_grad_by_procs:
+                globalg /= self.comm.Get_size()
+        else:
+            globalg = np.copy(localg)
 
         self.t += 1
         a = stepsize * np.sqrt(1 - self.beta2**self.t)/(1 - self.beta1**self.t)
@@ -40,19 +42,22 @@ class MpiAdam(object):
         self.setfromflat(self.getflat() + step)
 
     def sync(self):
+        if self.comm is None:
+            return
         theta = self.getflat()
         self.comm.Bcast(theta, root=0)
         self.setfromflat(theta)
 
     def check_synced(self):
+        if self.comm is None:
+            return
         if self.comm.Get_rank() == 0: # this is root
             theta = self.getflat()
             self.comm.Bcast(theta, root=0)
         else:
             thetalocal = self.getflat()
             thetaroot = np.empty_like(thetalocal)
-            if self.comm is not None:
-                self.comm.Bcast(thetaroot, root=0)
+            self.comm.Bcast(thetaroot, root=0)
             assert (thetaroot == thetalocal).all(), (thetaroot, thetalocal)
 
 @U.in_session
@@ -69,17 +74,30 @@ def test_MpiAdam():
     do_update = U.function([], loss, updates=[update_op])
 
     tf.get_default_session().run(tf.global_variables_initializer())
+    losslist_ref = []
     for i in range(10):
-        print(i,do_update())
+        l = do_update()
+        print(i, l)
+        losslist_ref.append(l)
+
+
 
     tf.set_random_seed(0)
     tf.get_default_session().run(tf.global_variables_initializer())
 
     var_list = [a,b]
-    lossandgrad = U.function([], [loss, U.flatgrad(loss, var_list)], updates=[update_op])
+    lossandgrad = U.function([], [loss, U.flatgrad(loss, var_list)])
     adam = MpiAdam(var_list)
 
+    losslist_test = []
     for i in range(10):
         l,g = lossandgrad()
         adam.update(g, stepsize)
         print(i,l)
+        losslist_test.append(l)
+
+    np.testing.assert_allclose(np.array(losslist_ref), np.array(losslist_test), atol=1e-4)
+
+
+if __name__ == '__main__':
+    test_MpiAdam()

baselines/trpo_mpi/trpo_mpi.py

@@ -244,10 +244,13 @@ def learn(*,
 
     def allmean(x):
         assert isinstance(x, np.ndarray)
-        out = np.empty_like(x)
         if MPI is not None:
+            out = np.empty_like(x)
             MPI.COMM_WORLD.Allreduce(x, out, op=MPI.SUM)
             out /= nworkers
+        else:
+            out = np.copy(x)
+
         return out
 
     U.initialize()