Remove global toFree list from Python interop module

test/library/packages/Python/examples/torch/myModel.chpl

@@ -17,7 +17,8 @@ proc main() {
 
   // create the model
   var model = myModelClass();
-  var input_tensor = tensor(owned Value, [[1.0,]], kwargs=["requires_grad" => true]);
+  var input_tensor = tensor(owned Value, [[1.0,]], kwargs=["requires_grad" => false]);
+  writeln("Input tensor: ", input_tensor);
 
   // init model weights to 0.9
   {
@@ -34,6 +35,7 @@ proc main() {
   // compute the loss
   var loss_fn = MSELoss();
   var target = tensor(owned Value, [[2.0,]]);
+  writeln("Target: ", target);
   var loss = loss_fn(owned ClassObject, pred, target);
   loss.call(NoneType, "backward");
 

test/library/packages/Python/examples/torch/mymodel.py

@@ -11,7 +11,8 @@ def forward(self, x):
 def main():
     # create the model
     model = MyModel()
-    input_tensor = torch.tensor([[1.0]], requires_grad=True)
+    input_tensor = torch.tensor([[1.0]], requires_grad=False)
+    print("Input tensor:", input_tensor)
 
     # init model weights to 0.9
     for p in model.parameters():
@@ -23,6 +24,7 @@ def main():
     # compute the loss
     loss_fn = torch.nn.MSELoss()
     target = torch.tensor([[2.0]])
+    print("Target:", target)
     loss = loss_fn(pred, target)
     loss.backward()
 

test/library/packages/Python/memleaks/lambdas.chpl

@@ -8,6 +8,18 @@ proc main() {
   writeln(l(list(int), 1));
   writeln(l(list(string), "hi"));
 
-  // this has a an extra lis
+  // this has an extra list
   writeln(l(list(list(int)), [1, 2, 3]));
+
+  // chapelList([4,5,6])
+  var l2 = new Function(interp, "lambda x,y,z,: [x,y,z]");
+  // printing this out will cause a memleak, the __str__ method for list leaks
+  // e.g., 'print([[1,2,3])' in python leaks memory
+  l2(list(owned Value?), 1, "hi", [4, 5, 6]);
+  writeln("skipping potentially leaking print");
+
+
+  var l3 = new Function(interp, "lambda x,: x");
+  writeln(l3(list(int), [1,]));
+  writeln(l3(NoneType, [1,]));
 }

test/library/packages/Python/memleaks/lambdas.good

@@ -1,3 +1,6 @@
 [1, 1]
 [hi, hi]
 [[1, 2, 3], [1, 2, 3]]
+skipping potentially leaking print
+[1]
+()