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Fix an ASAN failure due to uninitialized RemoteMgr.

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PiperOrigin-RevId: 311003331
Change-Id: I67a8e53c04f6ddf3f18334a3bc18e342dab23bf0
This commit is contained in:
Yujing Zhang 2020-05-11 15:12:02 -07:00 committed by TensorFlower Gardener
parent 28bbc65d66
commit 7c09d15f9f
1 changed files with 18 additions and 2 deletions
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20
tensorflow/core/common_runtime/eager/execute_node_test.cc
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@ -15,6 +15,8 @@ limitations under the License.
#include "tensorflow/core/common_runtime/eager/execute_node.h"
#include <memory>
#include "tensorflow/core/common_runtime/composite_device.h"
#include "tensorflow/core/common_runtime/device_mgr.h"
#include "tensorflow/core/common_runtime/eager/context.h"
@ -49,9 +51,12 @@ TEST(ExecuteNodeTest, ExecuteNodeArgs) {
StaticDeviceMgr device_mgr(
DeviceFactory::NewDevice("CPU", {}, "/job:localhost/replica:0/task:0"));
Device* device0 = device_mgr.ListDevices().at(0);
StaticDeviceMgr remote_device_mgr(
auto remote_device_mgr = absl::make_unique<DynamicDeviceMgr>();
std::vector<std::unique_ptr<Device>> remote_devices;
remote_devices.emplace_back(
DeviceFactory::NewDevice("CPU", {}, "/job:localhost/replica:0/task:1"));
Device* device1 = remote_device_mgr.ListDevices().at(0);
TF_ASSERT_OK(remote_device_mgr->AddDevices(std::move(remote_devices)));
Device* device1 = remote_device_mgr->ListDevices().at(0);
Status s;
std::unique_ptr<CompositeDevice> composite_device =
@ -65,6 +70,17 @@ TEST(ExecuteNodeTest, ExecuteNodeArgs) {
tensorflow::ContextMirroringPolicy::MIRRORING_NONE, false, false,
&device_mgr, false, nullptr, nullptr, nullptr);
// Set a RemoteMgr to the EagerContext.
auto remote_mgr = absl::make_unique<eager::RemoteMgr>(
/*is_master=*/true, ctx);
TF_ASSERT_OK(ctx->InitializeRemoteMaster(
/*server=*/nullptr, /*worker_env=*/nullptr,
/*worker_session=*/nullptr, /*remote_eager_workers=*/nullptr,
std::move(remote_device_mgr), /*remote_contexts=*/{},
EagerContext::NewContextId(),
/*r=*/nullptr, &device_mgr, /*keep_alive_secs*/ 600,
/*cluster_flr=*/nullptr, std::move(remote_mgr)));
DataType dtype = DT_FLOAT;
Tensor t0(dtype, TensorShape({}));
// Create two local TensorHandles