disabling TensorType.shape pending support for partially-known type attributes

theano/tensor/basic.py

@@ -181,9 +181,19 @@ def constant_or_value(x, rtype, name=None, ndim=None, dtype=None):
 
     try:
         if rtype is TensorConstant:
-            # put the shape into the type
+            if 0:
+                # put the shape into the type
+
+                # This is disabled because if a tensor has shape, then the following fails:
+                # theano.lvector == as_tensor_variable([0,1]).type
+                # I think the solution is that we should implement something more like
+                # compatability instead of equality in our Type comparisons... but we're not
+                # there yet.
+                x_shape = x_.shape
+            else:
+                x_shape = None
             return rtype(
-                    TensorType(dtype = x_.dtype, broadcastable = bcastable, shape=x_.shape),
+                    TensorType(dtype = x_.dtype, broadcastable = bcastable, shape=x_shape),
                     x_, name=name)
         else:
             # leave the shape out of the type
@@ -1096,8 +1106,8 @@ def shape(a):
     If the shape of the expression is not known at graph-construction time, then a symbolic
     lvector will be returned, corresponding to the actual shape at graph-execution time.
     """
-    print 'GOT A', a, a.type
     va = as_tensor_variable(a)
+    #print 'HERE', va, va.type
     if None in va.type.shape:
         # Some shape components are unknown at this time
         return _shape(va)
@@ -1106,7 +1116,7 @@ def shape(a):
         # a tuple directly.  This tuple is like the numpy.ndarray.shape tuple.
         return va.type.shape
 
-pprint.assign(shape, printing.MemberPrinter('shape'))
+pprint.assign(_shape, printing.MemberPrinter('shape'))
 
 
 class MaxAndArgmax(Op):
@@ -2403,7 +2413,7 @@ def get_vector_length(v):
             return join.vec_length(v)
         except ValueError:
             pass
-    if v.owner and v.owner.op == shape:
+    if v.owner and v.owner.op == _shape:
         return v.owner.inputs[0].type.ndim
     raise ValueError("length not known")