Add basic_train_loop() as an example for higher level frameworks to copy or

reuse.  It can also be used directly for simple training.

Fix Coordinator.clear_stop() to also clear the exception to raise.  Add test.

Add SummaryWriter.reopen(), with tests. This is needed to properly handle
summaries when create a session more than once in a Supervior.

In Supervisor.prepare_or_wait_for_session() reopen the summary writer.

At then end of Supervisor.managed_session() correctly close the summary write
and clear the running threads even if an exception was reported.
Change: 124500982

1 files changed, 95 insertions, 0 deletions

diff --git a/tensorflow/python/training/basic_loops_test.py b/tensorflow/python/training/basic_loops_test.py
new file mode 100644
index 0000000000..fc442c414c
--- /dev/null
+++ b/tensorflow/python/training/basic_loops_test.py
@@ -0,0 +1,95 @@
+# Copyright 2016 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.
+# ==============================================================================
+"""Tests for basic_loops.py."""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import os
+import shutil
+
+import tensorflow as tf
+
+
+def _test_dir(test_name):
+  test_dir = os.path.join(tf.test.get_temp_dir(), test_name)
+  if os.path.exists(test_dir):
+    shutil.rmtree(test_dir)
+  return test_dir
+
+
+class BasicTrainLoopTest(tf.test.TestCase):
+
+  def testBasicTrainLoop(self):
+    logdir = _test_dir("basic_train_loop")
+    sv = tf.train.Supervisor(logdir=logdir)
+    # Counts the number of calls.
+    num_calls = [0]
+
+    def train_fn(unused_sess, sv, y, a):
+      num_calls[0] += 1
+      self.assertEqual("y", y)
+      self.assertEqual("A", a)
+      if num_calls[0] == 3:
+        sv.request_stop()
+
+    with tf.Graph().as_default():
+      tf.train.basic_train_loop(sv, train_fn, args=(sv, "y"), kwargs={"a": "A"})
+      self.assertEqual(3, num_calls[0])
+
+  def testBasicTrainLoopExceptionAborts(self):
+    logdir = _test_dir("basic_train_loop_exception_aborts")
+    sv = tf.train.Supervisor(logdir=logdir)
+
+    def train_fn(unused_sess):
+      train_fn.counter += 1
+      if train_fn.counter == 3:
+        raise RuntimeError("Failed")
+
+    # Function attribute use to count the number of calls.
+    train_fn.counter = 0
+
+    with tf.Graph().as_default():
+      with self.assertRaisesRegexp(RuntimeError, "Failed"):
+        tf.train.basic_train_loop(sv, train_fn)
+
+  def testBasicTrainLoopRetryOnAborted(self):
+    logdir = _test_dir("basic_train_loop_exception_aborts")
+    sv = tf.train.Supervisor(logdir=logdir)
+
+    class AbortAndRetry(object):
+
+      def __init__(self):
+        self.num_calls = 0
+        self.retries_left = 2
+
+      def train_fn(self, unused_sess):
+        self.num_calls += 1
+        if self.num_calls % 3 == 2:
+          self.retries_left -= 1
+        if self.retries_left > 0:
+          raise tf.errors.AbortedError(None, None, "Aborted here")
+        else:
+          raise RuntimeError("Failed Again")
+
+    with tf.Graph().as_default():
+      aar = AbortAndRetry()
+      with self.assertRaisesRegexp(RuntimeError, "Failed Again"):
+        tf.train.basic_train_loop(sv, aar.train_fn)
+      self.assertEquals(0, aar.retries_left)
+
+
+if __name__ == "__main__":
+  tf.test.main()