pre-cleanup klass

gof/link.py

@@ -112,6 +112,8 @@ class Linker(object):
 
 class Container(object):
     def __init__(self, r, storage, readonly = False, strict = False, name = None):
+        if not isinstance(storage, list) or not len(storage) >= 1:
+            raise TypeError("storage must be a list of length at least one")
         #self.r = r
         if isinstance(r, Type):
             self.type = r
@@ -127,6 +129,9 @@ class Container(object):
         if self.readonly:
             raise Exception("Cannot set readonly storage: %s" % self.name)
         try:
+            if value is None:
+                self.storage[0] = None
+                return
             if self.strict:
                 self.storage[0] = self.type.filter(value, strict = True)
             else:

tensor.py

@@ -1212,7 +1212,7 @@ class Subtensor(Op):
 
     def __init__(self, idx_list):
         def convert(entry, slice_ok=True):
-            scal_types =[scal.int64, scal.int32, scal.int16, scal.int8]
+            scal_types = [scal.int64, scal.int32, scal.int16, scal.int8]
             tensor_types = [bscalar, iscalar, lscalar]
             if isinstance(entry, gof.Result) and entry.type in scal_types:
                 return entry.type
@@ -2059,7 +2059,7 @@ def grad(cost, wrt, g_cost=None):
                 Tensor(dtype = p.type.dtype, broadcastable = []),
                 numpy.asarray(0, dtype=p.type.dtype))
 
-    if isinstance(wrt, list):
+    if isinstance(wrt, (list, tuple)):
         return [gmap.get(p, zero(p)) for p in wrt]
     else:
         return gmap.get(wrt, zero(wrt))