added test for the new autocast for numpy.int{8,16,32} type.

theano/compile/tests/test_shared.py

@@ -117,6 +117,18 @@ class Test_SharedVariable(unittest.TestCase):
         assert b.type == theano.tensor.lscalar
         self.failUnlessRaises(TypeError, f, b, 8.23)
 
+        b = shared(numpy.int32(7), strict=True)
+        assert b.type == theano.tensor.iscalar
+        self.failUnlessRaises(TypeError, f, b, 8.23)
+        
+        b = shared(numpy.int16(7), strict=True)
+        assert b.type == theano.tensor.wscalar
+        self.failUnlessRaises(TypeError, f, b, 8.23)
+
+        b = shared(numpy.int8(7), strict=True)
+        assert b.type == theano.tensor.bscalar
+        self.failUnlessRaises(TypeError, f, b, 8.23)
+
         b = shared(numpy.float64(7.234), strict=True)
         assert b.type == theano.tensor.dscalar
         self.failUnlessRaises(TypeError, f, b, 8)
@@ -145,6 +157,18 @@ class Test_SharedVariable(unittest.TestCase):
         assert b.type == theano.tensor.lvector
         self.failUnlessRaises(TypeError, f, b, 8.23)
 
+        b = shared(numpy.int32([7]), strict=True)
+        assert b.type == theano.tensor.ivector
+        self.failUnlessRaises(TypeError, f, b, 8.23)
+
+        b = shared(numpy.int16([7]), strict=True)
+        assert b.type == theano.tensor.wvector
+        self.failUnlessRaises(TypeError, f, b, 8.23)
+
+        b = shared(numpy.int8([7]), strict=True)
+        assert b.type == theano.tensor.bvector
+        self.failUnlessRaises(TypeError, f, b, 8.23)
+
         b = shared(numpy.float64([7.234]), strict=True)
         assert b.type == theano.tensor.dvector
         self.failUnlessRaises(TypeError, f, b, 8)
@@ -181,22 +205,42 @@ class Test_SharedVariable(unittest.TestCase):
         b = shared(numpy.int64(7))
         assert b.type == theano.tensor.lscalar
         f(b,8.23)
+        assert b.value==8
+
+        b = shared(numpy.int32(7))
+        assert b.type == theano.tensor.iscalar
+        f(b,8.23)
+        assert b.value==8
+
+        b = shared(numpy.int16(7))
+        assert b.type == theano.tensor.wscalar
+        f(b,8.23)
+        assert b.value==8
+
+        b = shared(numpy.int8(7))
+        assert b.type == theano.tensor.bscalar
+        f(b,8.23)
+        assert b.value==8
 
         b = shared(numpy.float64(7.234))
         assert b.type == theano.tensor.dscalar
         f(b,8)
+        assert b.value==8
         
         b = shared(numpy.float32(7.234))
         assert b.type == theano.tensor.fscalar
         f(b,8)
+        assert b.value==8
 
         b = shared(numpy.float(7.234))
         assert b.type == theano.tensor.dscalar
         f(b,8)
+        assert b.value==8
 
         b = shared(7.234)
         assert b.type == theano.tensor.dscalar
         f(b,8)
+        assert b.value==8
 
         c = shared(numpy.zeros((5,5), dtype='float32'))
         self.failUnlessRaises(TypeError, f, b, numpy.random.rand(5,5))
@@ -209,14 +253,32 @@ class Test_SharedVariable(unittest.TestCase):
         b = shared(numpy.int64([7]))
         assert b.type == theano.tensor.lvector
         f(b,[8.23])
+        assert b.value == 8
+
+        b = shared(numpy.int32([7]))
+        assert b.type == theano.tensor.ivector
+        f(b,[8.23])
+        assert b.value == 8
+
+        b = shared(numpy.int16([7]))
+        assert b.type == theano.tensor.wvector
+        f(b,[8.23])
+        assert b.value == 8
+
+        b = shared(numpy.int8([7]))
+        assert b.type == theano.tensor.bvector
+        f(b,[8.23])
+        assert b.value == 8
 
         b = shared(numpy.float64([7.234]))
         assert b.type == theano.tensor.dvector
         f(b,[8])
+        assert b.value == 8
 
         b = shared(numpy.float32([7.234]))
         assert b.type == theano.tensor.fvector
         f(b,[8])
+        assert b.value == 8
 
 #numpy.float([7.234]) don't work
 #        b = shared(numpy.float([7.234]))
@@ -231,6 +293,7 @@ class Test_SharedVariable(unittest.TestCase):
         b = shared(numpy.asarray([7.234],dtype=theano.config.floatX))
         assert b.dtype == theano.config.floatX
         f(b,[8])
+        assert b.value == 8
 
         c = shared(numpy.zeros((5,5), dtype='float32'))
         self.failUnlessRaises(TypeError, f, b, numpy.random.rand(5,5))

theano/tensor/tests/test_basic.py

@@ -2504,6 +2504,13 @@ def test_autocast():
         assert (fvector()+ numpy.float32(1.1)).dtype == 'float32'
         assert (fvector()+ numpy.float64(1.1)).dtype == 'float64'
         assert (fvector()+ numpy.float(1.1)).dtype   == theano.config.floatX
+        assert (lvector()+ numpy.int64(1)).dtype == 'int64'
+        assert (lvector()+ numpy.int32(1)).dtype == 'int64'
+        assert (lvector()+ numpy.int16(1)).dtype == 'int64'
+        assert (lvector()+ numpy.int8(1)).dtype == 'int64'
+        assert (ivector()+ numpy.int8(1)).dtype == 'int32'
+        assert (wvector()+ numpy.int8(1)).dtype == 'int16'
+        assert (bvector()+ numpy.int8(1)).dtype == 'int8'
         try: #ghetto 2.4 version of with
             ac2 = autocast_float_as('float64')
             ac2.__enter__()