forked from mindspore-Ecosystem/mindspore
46 lines
2.2 KiB
Python
46 lines
2.2 KiB
Python
# 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 checkpoint file into models"""
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import argparse
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import numpy as np
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import mindspore as ms
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from mindspore import Tensor, context
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from mindspore.train.serialization import load_checkpoint, export, load_param_into_net
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from src.alexnet import SiameseAlexNet
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parser = argparse.ArgumentParser(description='siamfc export')
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parser.add_argument("--device_id", type=int, default=0, help="Device id")
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parser.add_argument('--model_path', default='/root/HRBEU-MedAI/SiamFC/models/siamfc_{}.ckpt/',
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type=str, help='eval one special video')
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parser.add_argument('--file_name', type=str, default='/root/HRBEU-MedAI/SiamFC/models',
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help='SiamFc output file name.')
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parser.add_argument('--file_format', type=str, choices=["AIR", "ONNX", "MINDIR"], default='MINDIR',
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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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net = SiameseAlexNet(train=False)
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load_param_into_net(net, load_checkpoint(args.model_path), strict_load=True)
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net.set_train(False)
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input_data_exemplar = Tensor(np.zeros([3, 256, 6, 6]), ms.float32)
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input_data_instance = Tensor(np.zeros([3, 3, 255, 255]), ms.float32)
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export(net, input_data_exemplar, input_data_instance, file_name=args.file_name,
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file_format=args.file_format)
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