!11023 Modify DPN about loading ckpt, README and export.py
From: @penny369 Reviewed-by: @wuxuejian Signed-off-by:pull/11023/MERGE
mindspore-ci-bot
4 years ago
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commit
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# Copyright 2021 Huawei Technologies Co., Ltd
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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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# ============================================================================
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"""Export DPN"""
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import argparse
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import numpy as np
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from mindspore import Tensor, context, load_checkpoint, load_param_into_net, export
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from src.dpn import dpns
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from src.config import config
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parser = argparse.ArgumentParser(description="export dpn")
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parser.add_argument("--device_id", type=int, default=0, help="device id")
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parser.add_argument("--ckpt_file", type=str, required=True, help="dpn ckpt file.")
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parser.add_argument("--width", type=int, default=224, help="input width")
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parser.add_argument("--height", type=int, default=224, help="input height")
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parser.add_argument("--file_name", type=str, default="dpn", help="dpn output file name.")
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parser.add_argument("--file_format", type=str, choices=["AIR", "ONNX", "MINDIR"],
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default="MINDIR", help="file format")
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parser.add_argument("--device_target", type=str, choices=["Ascend", "GPU", "CPU"], default="Ascend",
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help="device target")
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args = parser.parse_args()
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context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target)
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if args.device_target == "Ascend":
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context.set_context(device_id=args.device_id)
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if __name__ == "__main__":
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# define net
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backbone = config.backbone
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num_classes = config.num_classes
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net = dpns[backbone](num_classes=num_classes)
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# load checkpoint
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param_dict = load_checkpoint(args.ckpt_file)
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load_param_into_net(net, param_dict)
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net.set_train(False)
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image = Tensor(np.zeros([config.batch_size, 3, args.height, args.width], np.float32))
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export(net, image, file_name=args.file_name, file_format=args.file_format)
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