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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 checkpoint file into air, onnx, mindir models"""
- import argparse
- import numpy as np
-
- from mindspore import Tensor, context, load_checkpoint, load_param_into_net, export
- from eval import BuildEvalNetwork
- from src.nets import net_factory
-
- parser = argparse.ArgumentParser(description='checkpoint 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("--input_size", type=int, default=513, help="batch size")
- parser.add_argument("--ckpt_file", type=str, required=True, help="Checkpoint file path.")
- parser.add_argument("--file_name", type=str, default="deeplabv3", help="output file name.")
- parser.add_argument('--file_format', type=str, choices=["AIR", "MINDIR"], default='AIR', help='file format')
- parser.add_argument("--device_target", type=str, choices=["Ascend", "GPU", "CPU"], default="Ascend",
- help="device target")
- parser.add_argument('--model', type=str.lower, default='deeplab_v3_s8', choices=['deeplab_v3_s16', 'deeplab_v3_s8'],
- help='Select model structure (Default: deeplab_v3_s8)')
- parser.add_argument('--num_classes', type=int, default=21, help='the number of classes (Default: 21)')
- parser.add_argument("--input_format", type=str, choices=["NCHW", "NHWC"], default="NCHW",
- help="NCHW or NHWC")
- 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__':
- if args.model == 'deeplab_v3_s16':
- network = net_factory.nets_map['deeplab_v3_s16']('eval', args.num_classes, 16, True)
- else:
- network = net_factory.nets_map['deeplab_v3_s8']('eval', args.num_classes, 8, True)
- network = BuildEvalNetwork(network, args.input_format)
- param_dict = load_checkpoint(args.ckpt_file)
-
- # load the parameter into net
- load_param_into_net(network, param_dict)
- if args.input_format == "NHWC":
- input_data = Tensor(np.ones([args.batch_size, args.input_size, args.input_size, 3]).astype(np.float32))
- else:
- input_data = Tensor(np.ones([args.batch_size, 3, args.input_size, args.input_size]).astype(np.float32))
- export(network, input_data, file_name=args.file_name, file_format=args.file_format)
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