Check Python long are OK iff they fit in int64

theano/tensor/tests/test_basic.py

@@ -6175,7 +6175,7 @@ def _test_autocast_numpy():
     def ok(z):
         assert tensor.constant(z).dtype == numpy.asarray(z).dtype
     for x in ([2 ** i for i in xrange(63)] +
-              [0] +
+              [0, 0L, 1L, 2L ** 63 - 1] +
               [0., 1., 1.1, 1.5]):
         n_x = numpy.asarray(x)
         # Make sure the data type is the same as the one found by numpy.
@@ -6204,11 +6204,11 @@ def _test_autocast_numpy_floatX():
         for floatX in ('float32', 'float64'):
             config.floatX = floatX
             # Go through some typical scalar values.
-            # Note that we only consider integer values that Python considers
-            # to be 'int', because 'long' is not supported by Theano (due to
-            # the fact it is unbounded).
-            for x in ([2 ** i for i in xrange(64) if type(2 ** i) == int] +
-                      [0] +
+            # We only consider 'int' and 'long' Python values that can fit
+            # into int64, as that is the maximal integer type that Theano
+            # supports, and that is the maximal type in Python indexing.
+            for x in ([2 ** i - 1 for i in xrange(64)] +
+                      [0, 0L, 1L, 2L ** 63 - 1] +
                       [0., 1., 1.1, 1.5]):
                 ok(x, floatX)
                 ok(-x, floatX)
@@ -6372,6 +6372,29 @@ class test_arithmetic_cast(unittest.TestCase):
                         category=DeprecationWarning)
 
 
+class T_long_tensor(unittest.TestCase):
+    def test_fit_int64(self):
+        for exp in xrange(64):
+            val = 2L ** exp - 1
+            scalar_ct = constant(val)
+            assert scalar_ct.dtype == 'int64'
+            assert scalar_ct.value == val
+
+            vector_ct = constant([val, val])
+            assert vector_ct.dtype == 'int64'
+            assert numpy.all(vector_ct.value == val)
+
+            matrix_ct = constant([[val, val]])
+            assert matrix_ct.dtype == 'int64'
+            assert numpy.all(matrix_ct.value == val)
+
+    def test_too_big(self):
+        val = 2L ** 63
+        self.assertRaises(Exception, constant, val)
+        self.assertRaises(Exception, constant, [val, val])
+        self.assertRaises(Exception, constant, [[val, val]])
+
+
 class test_broadcast(unittest.TestCase):
     def test_broadcast_bigdim(self):
         def f():