STT-tensorflow/tensorflow/python/training/basic_loops_test.py
Zhenyu Tan 7e95c4abda fixit for basic_loops_test
PiperOrigin-RevId: 322219117
Change-Id: Ie673d9071e7e8c67237c3c87cb067f7a6e99e7ce
2020-07-20 14:01:18 -07:00

102 lines
3.1 KiB
Python

# 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
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import ops
from tensorflow.python.platform import test
from tensorflow.python.training import basic_loops
from tensorflow.python.training import supervisor
def _test_dir(test_name):
test_dir = os.path.join(test.get_temp_dir(), test_name)
if os.path.exists(test_dir):
shutil.rmtree(test_dir)
return test_dir
class BasicTrainLoopTest(test.TestCase):
def testBasicTrainLoop(self):
logdir = _test_dir("basic_train_loop")
# 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 ops.Graph().as_default():
sv = supervisor.Supervisor(logdir=logdir)
basic_loops.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")
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 ops.Graph().as_default():
sv = supervisor.Supervisor(logdir=logdir)
with self.assertRaisesRegex(RuntimeError, "Failed"):
basic_loops.basic_train_loop(sv, train_fn)
def testBasicTrainLoopRetryOnAborted(self):
logdir = _test_dir("basic_train_loop_exception_aborts")
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 errors_impl.AbortedError(None, None, "Aborted here")
else:
raise RuntimeError("Failed Again")
with ops.Graph().as_default():
sv = supervisor.Supervisor(logdir=logdir)
aar = AbortAndRetry()
with self.assertRaisesRegex(RuntimeError, "Failed Again"):
basic_loops.basic_train_loop(sv, aar.train_fn)
self.assertEqual(0, aar.retries_left)
if __name__ == "__main__":
test.main()