merge

gof/result.py

@@ -183,6 +183,9 @@ class Result(object):
         """
         return False
 
+    def c_literal(self):
+        raise AbstractFunctionError()
+    
     def c_declare(self, name, sub):
         """
         Declares variables that will be instantiated by L{c_extract}.

gradient.py

@@ -85,6 +85,22 @@ def grad_sources_inputs(sources, graph_inputs):
         
         output_arg = g_outputs
         input_arg = op.inputs
+
+        try:
+            dinputs = [x[0] for x in op.destroy_map().values()]
+        except AttributeError:
+            dinputs = []
+
+#        input_arg = [input in dinputs and input.copy() or input for input in input_arg]
+
+        new_input_arg = []
+        for input in input_arg:
+            if input in dinputs:
+                new_input_arg.append(input.copy())
+            else:
+                new_input_arg.append(input)
+        input_arg = new_input_arg
+        
         op_grad = op.grad(input_arg, output_arg)
         if not isinstance(op_grad, (list,tuple)):
             raise ValueError(_msg_retType, op.__class__)

scalar.py

@@ -291,7 +291,7 @@ class Identity(UnaryScalarOp):
         return x
     def c_code(self, (x, ), (z, ), sub):
         return "%(z)s = %(x)s;" % locals()
-    def grad(self, (x, y), (gz, )):
+    def grad(self, (x, ), (gz, )):
         return gz,
 
 class Neg(UnaryScalarOp):

tensor.py

@@ -67,6 +67,10 @@ class Tensor(BaseTensor):
     #SLICING
     def __getitem__(self, item): return subtensor(self, item)
     def __getslice__(self, *args): return subtensor(self, slice(*args))
+
+    #COPYING
+    def copy(self): return tensor_copy(self)
+    
 s2t.Tensor = Tensor