Add Clone

Author: lantiga

test/base.py

@@ -32,7 +32,7 @@ def base_test():
     model1 = lambda x: F.softmax(F.elu(fc3(x)))
     model2 = lambda x: F.softmax(F.tanh(fc3(x)))
     model3 = lambda x: F.softmax(F.sigmoid(fc3(x)))
-    model4 = lambda x: softmax(F.leaky_relu(fc4(x)))
+    model4 = lambda x: softmax(F.leaky_relu(fc4(x))).clone()
     model5 = lambda x: softmax(F.logsigmoid(fc4(x.transpose(0,1))))
     model6 = lambda x: fc3(F.max_pool2d(x.unsqueeze(dim=0),2).squeeze())
     model7 = lambda x: fc3(F.max_pool2d(x.unsqueeze(dim=0),2).squeeze(dim=0))

torch2c/emitters.py

@@ -663,6 +663,28 @@ def free_tpl(self):
 register(Abs, torch.autograd._functions.pointwise.Abs)
 
 
+class Clone(Emitter):
+
+    def __init__(self, obj, prevfns):
+        Emitter.__init__(self, obj, prevfns)
+        self.def_vars({
+            'input': id(prevfns[0]),
+        })
+        self.infer_type_var = 'input'
+
+    def call_tpl(self):
+        return '''
+            TH${T}Tensor *$id = TH${T}Tensor_newClone($input);
+            '''
+
+    def free_tpl(self):
+        return '''
+            TH${T}Tensor_free($id);
+            '''
+
+register(Clone, torch.autograd._functions.tensor.Clone)
+
+
 class Sigmoid(Emitter):
 
     def __init__(self, obj, prevfns):