Add core/util/exec_on_stall.h a tool for debugging deadlocks with

less logging.

PiperOrigin-RevId: 199334548

1 files changed, 89 insertions, 0 deletions

diff --git a/tensorflow/core/util/exec_on_stall.h b/tensorflow/core/util/exec_on_stall.h
new file mode 100644
index 0000000000..5c8f9d2324
--- /dev/null
+++ b/tensorflow/core/util/exec_on_stall.h
@@ -0,0 +1,89 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_CORE_UTIL_EXEC_ON_STALL_H_
+#define TENSORFLOW_CORE_UTIL_EXEC_ON_STALL_H_
+
+#include <functional>
+
+#include "tensorflow/core/platform/env.h"
+#include "tensorflow/core/platform/mutex.h"
+
+namespace tensorflow {
+
+// An object that executes a particular function only if it
+// is not deleted within the allotted number of seconds.
+//
+// This can be useful in diagnosing deadlocks, stalls and memory leaks
+// without logging too agressively.
+class ExecuteOnStall {
+ public:
+  // delay_secs: If the object still exists after this many seconds,
+  //     execute f.
+  // f: The function to be executed, for example a detailed log of the
+  //    the state of an object to which this is attached.
+  // poll_microseconds: The spawned thread will wake and test whether
+  //    the destructor has been invoked this frequently.
+  ExecuteOnStall(int delay_secs, std::function<void()> f,
+                 int32 poll_microseconds = 100)
+      : disabled_(false),
+        joined_(false),
+        env_(Env::Default()),
+        f_(f),
+        poll_microseconds_(poll_microseconds) {
+    deadline_ = env_->NowMicros() + 1000000 * delay_secs;
+    env_->SchedClosure([this]() {
+      while (env_->NowMicros() < deadline_) {
+        {
+          mutex_lock l(mu_);
+          if (disabled_) {
+            break;
+          }
+        }
+        env_->SleepForMicroseconds(poll_microseconds_);
+      }
+      {
+        mutex_lock l(mu_);
+        if (!disabled_) {
+          f_();
+        }
+        joined_ = true;
+        cond_var_.notify_all();
+      }
+    });
+  }
+
+  ~ExecuteOnStall() {
+    // Wait for spawned thread to terminate.
+    mutex_lock l(mu_);
+    disabled_ = true;
+    if (!joined_) {
+      cond_var_.wait(l);
+    }
+  }
+
+ private:
+  mutex mu_;
+  condition_variable cond_var_;
+  bool disabled_ GUARDED_BY(mu_);
+  bool joined_ GUARDED_BY(mu_);
+  Env* env_;
+  std::function<void()> f_;
+  int64 deadline_;
+  int32 poll_microseconds_;
+};
+
+}  // namespace tensorflow
+#endif  // TENSORFLOW_CORE_UTIL_EXEC_ON_STALL_H_