fixed and passing again

core.py

@@ -12,7 +12,7 @@ from scipy import weave
 
 import gof
 from gof import current_mode, set_mode, build_mode, eval_mode, build_eval_mode
-from gof import pop_mode, UNDEFINED, is_result
+from gof import pop_mode, is_result
 
 import type_spec
 import cutils
@@ -251,9 +251,6 @@ class Numpy2(ResultBase):
     __array__ = property(lambda self: self._data.__array__ )
     __array_struct__ = property(lambda self: self._data.__array_struct__ )
 
-    def data_set_inplace(self, data):
-        raise NotImplementedError()
-
     def data_alloc(self):
         self.data = numpy.ndarray(self.shape, self.dtype)
 
@@ -386,7 +383,7 @@ def input(x):
     elif is_result(x):
         raise TypeError("%s is already a result." % x)
     else:
-        return ResultBase(x)
+        return ResultBase(data=x)
 class _testCase_input(unittest.TestCase):
     def setUp(self):
         literal.hdb = {}
@@ -1067,11 +1064,14 @@ if 0:
     
 
 
+
+from grad import Grad
+
 def wrap_producer(f):
     class producer(omega_op):
         impl = f
         def grad(*args):
-            return [UNDEFINED] * (len(args) - 1)
+            return [Grad.Undefined] * (len(args) - 1)
     producer.__name__ = f.__name__
     def ret(dim, dtype = 'float', order = 'C'):
         return producer(dim, dtype, order)
@@ -1811,11 +1811,11 @@ class sum(elemwise):
 
 class ones_like(elemwise):
     impl = numpy.ones_like
-    def grad(x, gz): return UNDEFINED
+    def grad(x, gz): return Grad.Undefined
 
 class zeros_like(elemwise):
     impl = numpy.zeros_like
-    def grad(x, gz): return UNDEFINED
+    def grad(x, gz): return Grad.Undefined
 
 ## Array slicing ##
 

grad.py

@@ -17,6 +17,8 @@ class Grad(object):
     __call__()
     __getitem__()
     """
+    class Undefined: pass
+
     def __init__(self, dct={}):
         self.map = {}
         self.outputs = []
@@ -34,7 +36,7 @@ class Grad(object):
         try:
             return self.map[key]
         except KeyError:
-            return core.UNDEFINED
+            return Grad.Undefined
 
     def __setitem__(self, item, val):
         """Map item to its id and store internally."""
@@ -49,7 +51,7 @@ class Grad(object):
         
         This function should be fed as follows:
 
-        if dr is UNDEFINED:
+        if dr is undefined:
             r could be anything
         else dr might be core.UNCOMPUTED:
             r may be uncomputed or NumpyR
@@ -57,7 +59,7 @@ class Grad(object):
             r may be uncomputed or NumpyR
 
         """
-        if dr is core.UNDEFINED: 
+        if dr is Grad.Undefined: 
             # nothing to do
             return
 
@@ -122,7 +124,7 @@ class Grad(object):
         if not self.did_bprop:
             raise Exception('Grad.__call__ only makes sense after a bprop')
         rval = self[item]
-        if rval is not core.UNDEFINED \
+        if rval is not Grad.Undefined \
                 and core.current_mode() == 'build_eval':
             compute_from([rval], self._compute_history)
         return rval
@@ -297,7 +299,7 @@ class _testCase (unittest.TestCase):
             gb.bprop()
             self.assertEqual('should have raised',0)
         except AttributeError, e:
-            self.assertEqual(str(e), "Keyword instance has no attribute 'shape'")
+            self.assertEqual(str(e), "class Undefined has no attribute 'shape'")
             return
         self.assertEqual("Should have been error", 0)
     
@@ -311,7 +313,7 @@ class _testCase (unittest.TestCase):
             gc.bprop()
             self.assertEqual('should have raised',0)
         except AttributeError, e:
-            self.assertEqual(str(e), "Keyword instance has no attribute 'shape'")
+            self.assertEqual(str(e), "class Undefined has no attribute 'shape'")
             return
         self.assertEqual("Should have been error", 0)
 

sparse.py

@@ -182,7 +182,7 @@ class _testCase_dot(unittest.TestCase):
             m = mtype(a)
             ab = m.dot(b)
             try:
-                z = dot(SparseR(m),gof.lib.ResultValue(b))
+                z = dot(SparseR(m),core.ResultBase(data=b))
                 self.failUnless(z.data.shape == ab.shape)
                 self.failUnless(type(z.data) == type(ab))
             except Exception, e:
@@ -198,7 +198,7 @@ class _testCase_dot(unittest.TestCase):
                 sparse.lil_matrix]:#, sparse.coo_matrix]:
             m = mtype(b)
             ab = m.transpose().dot(a.transpose()).transpose()
-            z = dot(gof.lib.ResultValue(a),SparseR(mtype(b)))
+            z = dot(core.ResultBase(data=a),SparseR(mtype(b)))
             self.failUnless(z.data.shape == ab.shape)
             self.failUnless(type(z.data) == type(ab))
     def test_graph_bprop0(self):