default broadcasting pattern for shared tensors is all False

theano/compile/sandbox/sharedvalue.py

@@ -151,12 +151,22 @@ class TensorSharedVariable(SharedVariable, theano.tensor.basic._tensor_py_operat
     pass
 @shared_constructor
 def tensor_constructor(value, name=None, strict=False, broadcastable=None):
-    """SharedVariable Constructor for TensorType"""
+    """SharedVariable Constructor for TensorType
+    
+    :note: Regarding the inference of the broadcastable pattern... 
+    The default is to assume that the value might be resized in any dimension, so the default
+    broadcastable is ``(False,)*len(value.shape)``.  The optional `broadcastable` argument will
+    override this default.
+    
+    """
     if not isinstance(value, numpy.ndarray):
         raise TypeError()
 
+    # if no broadcastable is given, then the default is to assume that the value might be
+    # resized in any dimension in the future.
+    # 
     if broadcastable is None:
-        broadcastable = [b==1 for b in value.shape]
+        broadcastable = (False,)*len(value.shape)
     type = TensorType(value.dtype, broadcastable=broadcastable)
     return TensorSharedVariable(type=type, value=value, name=name, strict=strict)
 

theano/compile/sandbox/tests/test_shared.py

@@ -26,7 +26,7 @@ class Test_SharedVariable(unittest.TestCase):
         b = shared(numpy.random.rand(4,5))
         assert b.type == TensorType('float64', broadcastable=[False,False])
         b = shared(numpy.random.rand(5,1,2))
-        assert b.type == TensorType('float64', broadcastable=[False,True,False])
+        assert b.type == TensorType('float64', broadcastable=[False,False,False])
 
         assert shared([]).type == generic
         def badfunc():