forked from mindspore-Ecosystem/mindspore
40 lines
1.6 KiB
Python
40 lines
1.6 KiB
Python
# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""export checkpoint file into air, onnx, mindir models"""
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import numpy as np
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from src.model_utils.config import config
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from src.model_utils.device_adapter import get_device_id
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from src.inception_v3 import InceptionV3
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import mindspore as ms
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from mindspore import Tensor, load_checkpoint, load_param_into_net, export, context
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config.batch_size = 1
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context.set_context(mode=context.GRAPH_MODE, device_target=config.device_target)
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if config.device_target == "Ascend":
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context.set_context(device_id=get_device_id())
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if __name__ == '__main__':
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net = InceptionV3(num_classes=config.num_classes, is_training=False)
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param_dict = load_checkpoint(config.ckpt_file)
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load_param_into_net(net, param_dict)
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input_arr = Tensor(np.random.uniform(0.0, 1.0, size=[config.batch_size, 3, config.width, \
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config.height]), ms.float32)
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export(net, input_arr, file_name=config.file_name, file_format=config.file_format)
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