added opt.InplaceOptimizer

opt.py

+
+from gof import opt
+from elemwise2 import Broadcast
+
+class InplaceOptimizer(opt.OpSpecificOptimizer):
+
+    opclass = Broadcast
+    
+    def apply_on_op(self, env, op):
+        baseline = op.inplace_pattern
+        candidate_outputs = [i for i in xrange(len(op.outputs)) if i not in baseline]
+        candidate_inputs = [i for i in xrange(len(op.inputs)) if i not in baseline.values()]
+        for candidate_output in candidate_outputs:
+            for candidate_input in candidate_inputs:
+                inplace_pattern = dict(baseline, **{candidate_output: candidate_input})
+                try:
+                    new_op = Broadcast(op.scalar_opclass, op.inputs, inplace_pattern)
+                    env.replace_all(dict(zip(op.outputs, new_op.outputs)))
+                except:
+                    continue
+                candidate_inputs.remove(candidate_input)
+                op = new_op
+                break
+
+inplace_optimizer = InplaceOptimizer()
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
 
 """
 This variable is used in compile.prog as the optimizer for all programs built

scalar_ops.py

@@ -60,12 +60,6 @@ class Second(BinaryScalarOp):
     def grad(self, (x, y), (gz, )):
         return None, gz
 
-# class SquareDiff(BinaryScalarOp):
-#     def impl(self, x, y):
-#         diff = (x - y)
-#         return diff * diff
-#     def c_code(self, (x, y), (z, ), sub):
-#         return "%(z)s = %(x)s - %(y)s; %(z)s *= %(z)s;" % locals()
 
 class Identity(UnaryScalarOp):
     def impl(self, x):

tensor.py

@@ -327,7 +327,6 @@ Div, div, DivInplace, div_inplace = broadcast(scal.Div, 'Div')
 Pow, pow, PowInplace, pow_inplace = broadcast(scal.Pow, 'Pow')
 
 
-
 #########################
 # Linalg : Dot
 #########################