|
- # Copyright 2021 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.
- # ============================================================================
- """
- python export.py
- """
- import argparse
- import numpy as np
-
- from mindspore import Tensor, load_checkpoint, load_param_into_net, export, context
-
- from src import init_model
-
- #parser = argparse.ArgumentParser(description='resnet export')
- parser = argparse.ArgumentParser(description='pvt export')
- parser.add_argument("--device_id", type=int, default=0, help="Device id")
- parser.add_argument("--batch_size", type=int, default=1, help="batch size")
- parser.add_argument("--ckpt_file", type=str, default='resnet50-300_93.ckpt', help="Checkpoint file path.")
- parser.add_argument("--file_name", type=str, default="resnet50_imagenet", help="output file name.")
- parser.add_argument('--width', type=int, default=128, help='input width')
- parser.add_argument('--height', type=int, default=256, help='input height')
- parser.add_argument("--file_format", type=str, choices=["AIR", "ONNX", "MINDIR"], default="MINDIR", help="file format")
- parser.add_argument("--device_target", type=str, default="Ascend", choices=["Ascend", "GPU", "CPU"])
- parser.add_argument('--arch', type=str, default='resnet50')
- parser.add_argument('--outdir', type=str, default='')
- args = parser.parse_args()
-
- context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target, device_id=args.device_id)
-
- if __name__ == '__main__':
- net = init_model(name=args.arch, num_classes=751, loss='softmax and metric', aligned=True, is_train=False)
- net.set_train(False)
- assert args.ckpt_file is not None, "checkpoint_path is None."
-
- param_dict = load_checkpoint(args.ckpt_file)
- load_param_into_net(net, param_dict)
- input_arr = Tensor(np.zeros([args.batch_size, 3, args.height, args.width], np.float32))
- export(net, input_arr, file_name=args.file_name, file_format=args.file_format)
- print('export sucess')
|