Move MRG RandomStream test to tests.sandbox.test_rng_mrg

tests/sandbox/test_rng_mrg.py

@@ -853,6 +853,25 @@ def test_gradient_scan():
     f(np.arange(1, dtype="float32"))
 
 
+def test_simple_shared_mrg_random():
+    theano_rng = MRG_RandomStreams(10)
+
+    values, updates = theano.scan(
+        lambda: theano_rng.uniform((2,), -1, 1),
+        [],
+        [],
+        [],
+        n_steps=5,
+        truncate_gradient=-1,
+        go_backwards=False,
+    )
+    my_f = theano.function([], values, updates=updates, allow_input_downcast=True)
+
+    # Just check for run-time errors
+    my_f()
+    my_f()
+
+
 def test_multMatVect():
     A1 = tensor.lmatrix("A1")
     s1 = tensor.ivector("s1")

tests/scan/test_basic.py

@@ -1141,24 +1141,6 @@ class TestScan:
         # Check for runtime errors
         f(np.int32(0), np.float32(1.0), np.float32(0.5))
 
-    def test_simple_shared_mrg_random(self):
-        theano_rng = theano.sandbox.rng_mrg.MRG_RandomStreams(utt.fetch_seed())
-
-        values, updates = scan(
-            lambda: theano_rng.uniform((2,), -1, 1),
-            [],
-            [],
-            [],
-            n_steps=5,
-            truncate_gradient=-1,
-            go_backwards=False,
-        )
-        my_f = theano.function([], values, updates=updates, allow_input_downcast=True)
-
-        # Just check for run-time errors
-        my_f()
-        my_f()
-
     def test_simple_shared_random(self):
         theano_rng = theano.tensor.shared_randomstreams.RandomStreams(utt.fetch_seed())