# 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(v1=["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