removed old code not used anymore

theano/tensor/basic.py

@@ -314,11 +314,6 @@ class TensorType(Type):
     When this is True, strict filtering rejects data containing NaN or Inf entries. (Used in `DebugMode`)
     """
 
-    use_shape = False
-    """
-    This should be removed (hardcoded to be False) after AISTATS09
-    """
-
     def __init__(self, dtype, broadcastable, name = None, shape=None):
         """Initialize self.dtype and self.broadcastable.
 
@@ -383,11 +378,6 @@ class TensorType(Type):
             if not data.ndim == self.ndim:
                 raise TypeError("%s expected a ndarray object with %s dimensions (got %s)." % (self, self.ndim, data.ndim))
 
-            if TensorType.use_shape:
-                for si, di in zip(self.shape, data.shape):
-                    if not (si is None or si == di):
-                        raise TypeError('%s requires ndarray with shape matching %s (got %s)'%(
-                            self, self.shape, data.shape))
             return data
         else:
             data = theano._asarray(data, dtype = self.dtype) #TODO - consider to pad shape with ones
@@ -432,13 +422,8 @@ class TensorType(Type):
 
     def __eq__(self, other):
         """Compare True iff other is the same kind of TensorType"""
-        if TensorType.use_shape:
-            return type(self) == type(other) and other.dtype == self.dtype \
-                    and other.broadcastable == self.broadcastable \
-                    and other.shape == self.shape
-        else:
-            return type(self) == type(other) and other.dtype == self.dtype \
-                    and other.broadcastable == self.broadcastable
+        return type(self) == type(other) and other.dtype == self.dtype \
+            and other.broadcastable == self.broadcastable
 
     @staticmethod
     def values_eq(a, b):
@@ -509,10 +494,7 @@ class TensorType(Type):
 
     def __hash__(self):
         """Hash equal for same kinds of TensorType"""
-        if TensorType.use_shape:
-            return hashtype(self) ^ hash(self.dtype) ^ hash(self.broadcastable) ^ hash(self.shape)
-        else:
-            return hashtype(self) ^ hash(self.dtype) ^ hash(self.broadcastable)
+        return hashtype(self) ^ hash(self.dtype) ^ hash(self.broadcastable)
 
     ndim = property(lambda self: len(self.broadcastable), doc = "number of dimensions")
     """Number of dimensions