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- # 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.
- # ============================================================================
-
- """export ckpt to model"""
-
- import argparse
-
- import numpy as np
-
- import mindspore
- from mindspore.train.serialization import export
- from mindspore import context, Tensor
- from mindspore.common import set_seed
- from src.config import yolact_plus_resnet50_config as cfg
- from src.yolact.yolactpp import Yolact
-
- parser = argparse.ArgumentParser(description="SOLO export")
- parser.add_argument("--device_id", type=int, default=2, help="Device id")
- parser.add_argument("--ckpt_file", type=str, default="./yolact-20_619.ckpt", help="Checkpoint file path.")
- # parser.add_argument("--ckpt_file", type=str, required=True, help="Checkpoint file path.")
- parser.add_argument("--file_name", type=str, default="Yolact", 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=["Ascend", "GPU", "CPU"], default="Ascend",
- help="device target")
- args = parser.parse_args()
- set_seed(1)
-
- context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target)
- if args.device_target == "Ascend":
- context.set_context(device_id=args.device_id)
-
- if __name__ == "__main__":
- net = SOLO()
- net.set_train(False)
- #param_dict = load_checkpoint(args.ckpt_file)
- #load_param_into_net(net, param_dict)
- img = Tensor(np.ones([1, 3, cfg['img_height'], cfg['img_width']]), mindspore.float32)
- export(net, img, file_name=args.file_name, file_format=args.file_format)
- #net(img)
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