should_donate should not propagate to the output data (pytorch#7585)

test/dynamo/test_dynamo_aliasing.py

@@ -123,6 +123,7 @@ def test_manual_buffer_donation(self):
     self.assertEqual(met.counter_value('XlaSetBufferDonation'), 1)
     dummy_inplace_add_compiled(input)
     torch.allclose(input_cloned.cpu() + 1, input.cpu())
+    self.assertFalse(torch_xla._XLAC._get_buffer_donation(input))
 
   def test_manual_buffer_donation_for_non_inplce_op(self):
     device = xm.xla_device()

torch_xla/csrc/xla_graph_executor.cpp

@@ -1038,15 +1038,6 @@ void XLAGraphExecutor::ExtractIRAndPrepareXlaData_(
         runtime::GetComputationClient()->CreateDataPlaceholder(
             tensor_device.toString(), std::move(shape));
 
-    // If current IR is a device data, executing the graph will generate a new
-    // Data with the same value. In this case we want to inherit the buffer
-    // donation option from the old Data.
-    auto device_data = torch_xla::DeviceData::Cast(ir_value.node.get());
-    if (device_data && device_data->get_buffer_donation()) {
-      std::dynamic_pointer_cast<runtime::ComputationClient::Data>(handle)
-          ->set_should_donate_buffer(true);
-    }
-
     tensor_data_vec.push_back(handle);
     if (tensor->CurrentDataHandle() == nullptr && config.force_ltc_data) {
       tensor->AssignIrValue(torch::lazy::Value());