Fix nanguardmode with slices

theano/compile/nanguardmode.py

@@ -68,6 +68,8 @@ def contains_nan(arr, node=None):
         return False
     elif isinstance(arr, np.random.mtrand.RandomState):
         return False
+    elif isinstance(arr, slice):
+        return False
     elif arr.size == 0:
         return False
     elif cuda.cuda_available and isinstance(arr, cuda.CudaNdarray):
@@ -112,6 +114,8 @@ def contains_inf(arr, node=None):
         return False
     elif isinstance(arr, np.random.mtrand.RandomState):
         return False
+    elif isinstance(arr, slice):
+        return False
     elif arr.size == 0:
         return False
     elif cuda.cuda_available and isinstance(arr, cuda.CudaNdarray):
@@ -246,6 +250,8 @@ class NanGuardMode(Mode):
                     err = False
                 elif isinstance(var, np.random.mtrand.RandomState):
                     err = False
+                elif isinstance(var, slice):
+                    err = False
                 elif var.size == 0:
                     err = False
                 elif cuda.cuda_available and isinstance(var, cuda.CudaNdarray):

theano/compile/tests/test_nanguardmode.py

@@ -46,3 +46,28 @@ def test_NanGuardMode():
         assert_raises(AssertionError, fun, biga)  # big values
     finally:
         _logger.propagate = True
+
+    # slices
+    a = numpy.random.randn(3, 4, 5).astype(theano.config.floatX)
+    infa = numpy.tile(
+        (numpy.asarray(100.) ** 1000000).astype(theano.config.floatX),
+        (3, 4, 5))
+    nana = numpy.tile(
+        numpy.asarray(numpy.nan).astype(theano.config.floatX), (3, 4, 5))
+    biga = numpy.tile(
+        numpy.asarray(1e20).astype(theano.config.floatX), (3, 4, 5))
+
+    x = T.tensor3()
+    y = x[:, T.arange(2), T.arange(2)]
+    fun = theano.function(
+        [x], y,
+        mode=NanGuardMode(nan_is_error=True, inf_is_error=True)
+    )
+    fun(a)  # normal values
+    try:
+        _logger.propagate = False
+        assert_raises(AssertionError, fun, infa)  # INFs
+        assert_raises(AssertionError, fun, nana)  # NANs
+        assert_raises(AssertionError, fun, biga)  # big values
+    finally:
+        _logger.propagate = True