71 lines
2.5 KiB
Python
71 lines
2.5 KiB
Python
# Copyright 2017-2018 The Apache Software Foundation
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#
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# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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#
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# -----------------------------------------------------------------------
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#
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# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import sys
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import argparse
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import logging
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import mxnet as mx
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import numpy as np
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import data, dali
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import fit
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import models
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def parse_args():
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parser = argparse.ArgumentParser(description="Train classification models on ImageNet",
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formatter_class=argparse.ArgumentDefaultsHelpFormatter)
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models.add_model_args(parser)
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fit.add_fit_args(parser)
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data.add_data_args(parser)
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dali.add_dali_args(parser)
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data.add_data_aug_args(parser)
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return parser.parse_args()
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def setup_logging(args):
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head = '{asctime}:{levelname}: {message}'
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logging.basicConfig(level=logging.DEBUG, format=head, style='{',
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handlers=[logging.StreamHandler(sys.stderr), logging.FileHandler(args.log)])
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logging.info('Start with arguments {}'.format(args))
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if __name__ == '__main__':
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args = parse_args()
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setup_logging(args)
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model = models.get_model(**vars(args))
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data_loader = data.get_data_loader(args)
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fit.fit(args, model, data_loader)
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