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- # Copyright 2020 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ============================================================================
- """export file"""
- import argparse
- import numpy as np
-
- from mindspore import Tensor, context, load_checkpoint, load_param_into_net, export
- from src.efficientnet import efficientnet_b0
- from src.config import dataset_config
-
- parser = argparse.ArgumentParser(description="efficientnet export")
- parser.add_argument("--width", type=int, default=224, help="input width")
- parser.add_argument("--height", type=int, default=224, help="input height")
- parser.add_argument('--dataset', type=str, default='ImageNet', choices=['ImageNet', 'CIFAR10'],
- help='ImageNet or CIFAR10')
- parser.add_argument("--ckpt_file", type=str, required=True, help="Checkpoint file path.")
- parser.add_argument("--file_name", type=str, default="efficientnet", help="output file name.")
- parser.add_argument("--file_format", type=str, choices=["AIR", "ONNX", "MINDIR"],
- default="MINDIR", help="file format")
- parser.add_argument("--device_target", type=str, choices=["GPU", "CPU"], default="GPU",
- help="device target")
- args = parser.parse_args()
-
- context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target)
-
-
- if __name__ == "__main__":
- if args.device_target not in ("GPU", "CPU"):
- raise ValueError("Only supported CPU and GPU now.")
-
- dataset_type = args.dataset.lower()
- cfg = dataset_config[dataset_type].cfg
-
- net = efficientnet_b0(num_classes=cfg.num_classes,
- drop_rate=cfg.drop,
- drop_connect_rate=cfg.drop_connect,
- global_pool=cfg.gp,
- bn_tf=cfg.bn_tf,
- )
-
- ckpt = load_checkpoint(args.ckpt_file)
- load_param_into_net(net, ckpt)
- net.set_train(False)
-
- image = Tensor(np.ones([cfg.batch_size, 3, args.height, args.width], np.float32))
- export(net, image, file_name=args.file_name, file_format=args.file_format)
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