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	# coding=utf-8
	# Copyright 2021 The Deeplab2 Authors.
	#
	# 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.

	"""This file contains code to run a model."""

	import os
	from absl import app
	from absl import flags
	from absl import logging
	import tensorflow as tf

	from google.protobuf import text_format
	from deeplab2 import config_pb2
	from deeplab2.trainer import train_lib

	flags.DEFINE_enum(
	'mode',
	default=None,
	enum_values=['train', 'eval', 'train_and_eval', 'continuous_eval'],
	help='Mode to run: `train`, `eval`, `train_and_eval`, `continuous_eval`.')

	flags.DEFINE_string(
	'model_dir',
	default=None,
	help='The base directory where the model and training/evaluation summaries'
	'are stored. The path will be combined with the `experiment_name` defined '
	'in the config file to create a folder under which all files are stored.')

	flags.DEFINE_string(
	'config_file',
	default=None,
	help='Proto file which specifies the experiment configuration. The proto '
	'definition of ExperimentOptions is specified in config.proto.')

	flags.DEFINE_string(
	'master',
	default=None,
	help='The Cloud TPU to use for training. This should be either the name '
	'used when creating the Cloud TPU, or a grpc://ip.address.of.tpu:8470 '
	'url.')

	flags.DEFINE_integer(
	'num_gpus',
	default=0,
	help='The number of GPUs to use for. If `master` flag is not set, this'
	'parameter specifies whether GPUs should be used and how many of them '
	'(default: 0).')

	FLAGS = flags.FLAGS


	def main(_):
	logging.info('Reading the config file.')
	with tf.io.gfile.GFile(FLAGS.config_file, 'r') as proto_file:
	config = text_format.ParseLines(proto_file, config_pb2.ExperimentOptions())

	logging.info('Starting the experiment.')
	combined_model_dir = os.path.join(FLAGS.model_dir, config.experiment_name)
	train_lib.run_experiment(FLAGS.mode, config, combined_model_dir, FLAGS.master,
	FLAGS.num_gpus)


	if __name__ == '__main__':
	app.run(main)