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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 checkpoint file into air, onnx, mindir models"""
-
- import argparse
- import numpy as np
- import mindspore
- from mindspore import Tensor, context, load_checkpoint, load_param_into_net, export
- from src.config import crowd_cfg as cfg
- from src.mcnn import MCNN
-
- parser = argparse.ArgumentParser(description='MindSpore MNIST Example')
- parser.add_argument("--device_id", type=int, default=4, help="Device id")
- parser.add_argument("--batch_size", type=int, default=1, help="batch size")
- parser.add_argument("--ckpt_file", type=str, required=True, help="Checkpoint file path.")
- parser.add_argument("--file_name", type=str, default="mcnn", help="output file name.")
- parser.add_argument("--file_format", type=str, choices=["AIR", "ONNX", "MINDIR"], default="AIR", help="file format")
- parser.add_argument("--device_target", type=str, choices=["Ascend", "GPU", "CPU"], default="Ascend",
- help="device target")
- args = parser.parse_args()
-
- 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__":
-
- # define fusion network
- network = MCNN()
- # load network checkpoint
- param_dict = load_checkpoint(args.ckpt_file)
- load_param_into_net(network, param_dict)
-
- # export network
- inputs = Tensor(np.ones([args.batch_size, 1, cfg.image_height, cfg.image_width]), mindspore.float32)
- export(network, inputs, file_name=args.file_name, file_format=args.file_format)
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