laywerrobot/lib/python3.6/site-packages/tensorflow/python/training/basic_loops.py
2020-08-27 21:55:39 +02:00

61 lines
2.3 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.
# ==============================================================================
"""Basic loop for training."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.framework import errors
from tensorflow.python.util.tf_export import tf_export
@tf_export("train.basic_train_loop")
def basic_train_loop(supervisor, train_step_fn, args=None,
kwargs=None, master=""):
"""Basic loop to train a model.
Calls `train_step_fn` in a loop to train a model. The function is called as:
```python
train_step_fn(session, *args, **kwargs)
```
It is passed a `tf.Session` in addition to `args` and `kwargs`. The function
typically runs one training step in the session.
Args:
supervisor: `tf.train.Supervisor` to run the training services.
train_step_fn: Callable to execute one training step. Called
repeatedly as `train_step_fn(session, *args **kwargs)`.
args: Optional positional arguments passed to `train_step_fn`.
kwargs: Optional keyword arguments passed to `train_step_fn`.
master: Master to use to create the training session. Defaults to
`""` which causes the session to be created in the local process.
"""
if args is None:
args = []
if kwargs is None:
kwargs = {}
should_retry = True
while should_retry:
try:
should_retry = False
with supervisor.managed_session(master) as sess:
while not supervisor.should_stop():
train_step_fn(sess, *args, **kwargs)
except errors.AbortedError:
# Always re-run on AbortedError as it indicates a restart of one of the
# distributed tensorflow servers.
should_retry = True