68 lines
2.2 KiB
Python
68 lines
2.2 KiB
Python
# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
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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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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import os
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import argparse
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from ppcls.data import Reader
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from ppcls.utils.config import get_config
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from ppcls.utils.save_load import init_model
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from ppcls.utils import logger
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from paddle.fluid.incubate.fleet.collective import fleet
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from paddle.fluid.incubate.fleet.base import role_maker
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def parse_args():
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parser = argparse.ArgumentParser("PaddleClas eval script")
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parser.add_argument(
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'-c',
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'--config',
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type=str,
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default='./configs/eval.yaml',
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help='config file path')
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parser.add_argument(
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'-o',
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'--override',
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action='append',
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default=[],
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help='config options to be overridden')
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args = parser.parse_args()
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return args
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def main(args):
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# assign the place
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gpu_id = fluid.dygraph.parallel.Env().dev_id
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place = fluid.CUDAPlace(gpu_id)
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with fluid.dygraph.guard(place):
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pre_weights_dict = fluid.dygraph.load_dygraph(config.pretrained_model)[0]
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strategy = fluid.dygraph.parallel.prepare_context()
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net = program.create_model(config.ARCHITECTURE, config.classes_num)
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net = fluid.dygraph.parallel.DataParallel(net, strategy)
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net.set_dict(pre_weights_dict)
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valid_dataloader = program.create_dataloader()
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valid_reader = Reader(config, 'valid')()
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valid_dataloader.set_sample_list_generator(valid_reader, place)
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net.eval()
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top1_acc = program.run(valid_dataloader, config, net, None, 0, 'valid')
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if __name__ == '__main__':
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args = parse_args()
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main(args)
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