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# Copyright 2020 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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import argparse
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import numpy as np
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import mindspore
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from mindspore import context, Tensor
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from mindspore.train.serialization import load_checkpoint, load_param_into_net, export
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from src.ssd import SSD300, ssd_mobilenet_v2, ssd_mobilenet_v1_fpn
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from src.config import config
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parser = argparse.ArgumentParser(description='SSD export')
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parser.add_argument("--device_id", type=int, default=0, help="Device id")
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parser.add_argument("--batch_size", type=int, default=1, help="batch size")
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parser.add_argument("--ckpt_file", type=str, required=True, help="Checkpoint file path.")
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parser.add_argument("--file_name", type=str, default="ssd.air", help="output file name.")
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parser.add_argument('--file_format', type=str, choices=["AIR", "ONNX", "MINDIR"], default='AIR', help='file format')
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args = parser.parse_args()
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", device_id=args.device_id)
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if __name__ == '__main__':
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if config.model == "ssd300":
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net = SSD300(ssd_mobilenet_v2(), config, is_training=False)
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else:
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net = ssd_mobilenet_v1_fpn(config=config)
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param_dict = load_checkpoint(args.ckpt_file)
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net.init_parameters_data()
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load_param_into_net(net, param_dict)
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net.set_train(False)
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input_shp = [args.batch_size, 3] + config.img_shape
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input_array = Tensor(np.random.uniform(-1.0, 1.0, size=input_shp), mindspore.float32)
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export(net, input_array, file_name=args.file_name, file_format=args.file_format)
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