Try to get_scalar_constant_value for Assert nodes.

theano/tensor/basic.py

@@ -488,6 +488,13 @@ def get_scalar_constant_value(orig_v, elemwise=True,
             elif isinstance(v.owner.op, (ScalarFromTensor, TensorFromScalar)):
                 v = v.owner.inputs[0]
                 continue
+            elif isinstance(v.owner.op, theano.tensor.opt.Assert):
+                # check if all conditions are constant and true
+                cond = [get_scalar_constant_value(c, max_recur=max_recur)
+                        for c in v.owner.inputs[1:]]
+                if builtins.all([0 == c.ndim and c != 0 for c in cond]):
+                    v = v.owner.inputs[0]
+                    continue
             elif isinstance(v.owner.op, scal.ScalarOp):
                 if isinstance(v.owner.op, scal.Second):
                     # We don't need both input to be constant for second

theano/tensor/tests/test_basic.py

@@ -7101,6 +7101,28 @@ class T_get_scalar_constant_value(unittest.TestCase):
         s = tensor.second(c, .4)
         assert numpy.allclose(get_scalar_constant_value(s), .4)
 
+    def test_assert(self):
+        # Make sure we still get the constant value if it is wrapped in
+        # an Assert.
+        c = theano.tensor.constant(2)
+        x = theano.tensor.scalar()
+
+        # condition is always True
+        a = opt.Assert()(c, c > 1)
+        assert get_scalar_constant_value(a) == 2
+
+        # condition is always False
+        a = opt.Assert()(c, c > 2)
+        self.assertRaises(
+            tensor.NotScalarConstantError,
+            get_scalar_constant_value, a)
+
+        # condition is not constant
+        a = opt.Assert()(c, c > x)
+        self.assertRaises(
+            tensor.NotScalarConstantError,
+            get_scalar_constant_value, a)
+
     def test_second(self):
         # Second should apply when the value is constant but not the shape
         c = theano.tensor.constant(numpy.random.rand())