Also skip bool and have a real gpuarray test.

theano/compile/nanguardmode.py

@@ -106,7 +106,7 @@ def contains_nan(arr, node=None, var=None):
     """
     if not _is_numeric_value(arr, var):
         return False
-    elif "int" in str(getattr(arr, 'dtype', '')):
+    elif getattr(arr, 'dtype', '') in T.discrete_dtypes:
         return False
     elif pygpu_available and isinstance(arr, GpuArray):
         return np.isnan(f_gpua_min(arr.reshape(arr.size)))
@@ -141,7 +141,7 @@ def contains_inf(arr, node=None, var=None):
     """
     if not _is_numeric_value(arr, var):
         return False
-    elif "int" in str(getattr(arr, 'dtype', '')):
+    elif getattr(arr, 'dtype', '') in T.discrete_dtypes:
         return False
     elif pygpu_available and isinstance(arr, GpuArray):
         return (np.isinf(f_gpua_min(arr.reshape(arr.size))) or

theano/compile/tests/test_nanguardmode.py

@@ -69,14 +69,3 @@ def test_NanGuardMode():
         assert_raises(AssertionError, fun, biga)  # big values
     finally:
         _logger.propagate = True
-
-    # Test with uint, we should not crash
-    x = T.matrix(dtype='uint8')
-    w = theano.shared(np.random.randn(5, 7).astype(theano.config.floatX))
-    y = T.dot(x, w)
-    a = (np.random.randn(3, 5).astype(theano.config.floatX) * 10).astype('uint8')
-    fun = theano.function(
-        [x], y,
-        mode=NanGuardMode(nan_is_error=True, inf_is_error=True)
-    )
-    fun(a)  # normal values

theano/gpuarray/tests/test_misc.py

+# Test that normaly could be outside gpuarray, to have all gpuarray
+# tests in the same directory, we put them here.
+
+import theano
+from theano import tensor
+from theano.compile.nanguardmode import NanGuardMode
+
+from .config import mode_with_gpu
+
+
+def test_nan_guard_mode():
+    x = tensor.vector(dtype='int64')
+    y = x + 1
+    mode = NanGuardMode(nan_is_error=True, optimizer=mode_with_gpu.optimizer)
+    f = theano.function([x], y, mode=mode)
+    theano.printing.debugprint(f)
+    f([23, 7])