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83 lines
2.4 KiB
Python
83 lines
2.4 KiB
Python
# Copyright (c) 2020 PaddlePaddle Authors. 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 argparse
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import os
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import sys
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import os.path as osp
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import paddle
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import paddle.nn.functional as F
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from paddle.jit import to_static
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import paddleslim
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__dir__ = os.path.dirname(os.path.abspath(__file__))
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sys.path.append(os.path.abspath(os.path.join(__dir__, '../')))
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from paddlevideo.modeling.builder import build_model
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from paddlevideo.utils import get_config
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def parse_args():
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parser = argparse.ArgumentParser("PaddleVideo Summary")
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parser.add_argument('-c',
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'--config',
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type=str,
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default='configs/example.yaml',
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help='config file path')
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parser.add_argument("--img_size", type=int, default=224)
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parser.add_argument("--num_seg", type=int, default=8)
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parser.add_argument("--FLOPs",
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action="store_true",
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help="whether to print FLOPs")
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return parser.parse_args()
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def _trim(cfg, args):
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"""
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Reuse the trainging config will bring useless attribute, such as: backbone.pretrained model. Trim it here.
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"""
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model_name = cfg.model_name
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cfg = cfg.MODEL
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cfg.backbone.pretrained = ""
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if 'num_seg' in cfg.backbone:
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cfg.backbone.num_seg = args.num_seg
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return cfg, model_name
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def main():
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args = parse_args()
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cfg, model_name = _trim(get_config(args.config, show=False), args)
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print(f"Building model({model_name})...")
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model = build_model(cfg)
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img_size = args.img_size
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num_seg = args.num_seg
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#NOTE: only support tsm now, will refine soon
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params_info = paddle.summary(model, (1, 1, num_seg, 3, img_size, img_size))
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print(params_info)
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if args.FLOPs:
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flops_info = paddleslim.analysis.flops(
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model, [1, 1, num_seg, 3, img_size, img_size])
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print(flops_info)
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if __name__ == "__main__":
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main()
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