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# 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.
# ==============================================================================
"""A configure tuple for high-level APIs for running distribution strategies."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections
class DistributeConfig(
collections.namedtuple(
'DistributeConfig',
['train_distribute', 'eval_distribute', 'remote_cluster'])):
"""A config tuple for distribution strategies.
Attributes:
train_distribute: a `DistributionStrategy` object for training.
eval_distribute: an optional `DistributionStrategy` object for
evaluation.
remote_cluster: a dict, `ClusterDef` or `ClusterSpec` object specifying
the cluster configurations. If this is given, the `train_and_evaluate`
method will be running as a standalone client which connects to the
cluster for training.
"""
def __new__(cls,
train_distribute=None,
eval_distribute=None,
remote_cluster=None):
return super(DistributeConfig, cls).__new__(cls, train_distribute,
eval_distribute, remote_cluster)
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