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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 models"""
- import argparse
- import numpy as np
-
- from mindspore import Tensor, context, load_checkpoint, export
-
- from src.gcn import GCN
- from src.config import ConfigGCN
-
- parser = argparse.ArgumentParser(description="GCN export")
- parser.add_argument("--device_id", type=int, default=0, help="Device id")
- parser.add_argument("--ckpt_file", type=str, required=True, help="Checkpoint file path.")
- parser.add_argument("--dataset", type=str, default="cora", choices=["cora", "citeseer"], help="Dataset.")
- parser.add_argument("--file_name", type=str, default="gcn", 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, default="Ascend",
- choices=["Ascend", "GPU", "CPU"], help="device target (default: Ascend)")
- args = parser.parse_args()
-
- context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target, device_id=args.device_id)
-
- if __name__ == "__main__":
- config = ConfigGCN()
-
- if args.dataset == "cora":
- input_dim = 1433
- class_num = 7
- adj = Tensor(np.zeros((2708, 2708), np.float64))
- feature = Tensor(np.zeros((2708, 1433), np.float32))
- else:
- input_dim = 3703
- class_num = 6
- adj = Tensor(np.zeros((3312, 3312), np.float64))
- feature = Tensor(np.zeros((3312, 3703), np.float32))
-
- gcn_net = GCN(config, input_dim, class_num)
-
- gcn_net.set_train(False)
- load_checkpoint(args.ckpt_file, net=gcn_net)
- gcn_net.add_flags_recursive(fp16=True)
-
- export(gcn_net, adj, feature, file_name=args.file_name, file_format=args.file_format)
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