forked from mindspore-Ecosystem/mindspore
38 lines
1.5 KiB
Python
38 lines
1.5 KiB
Python
# 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"""
|
|
|
|
import numpy as np
|
|
from mindspore import Tensor
|
|
from mindspore import context
|
|
from mindspore.train.serialization import load_checkpoint, load_param_into_net, export
|
|
|
|
from src.ssd_ghostnet import SSD300, ssd_ghostnet
|
|
from src.model_utils.config import config
|
|
|
|
context.set_context(mode=context.GRAPH_MODE, device_target=config.device_target, device_id=config.device_id)
|
|
|
|
if __name__ == "__main__":
|
|
context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
|
|
# define net
|
|
net = SSD300(ssd_ghostnet(), is_training=False)
|
|
|
|
# load checkpoint
|
|
param_dict = load_checkpoint(config.checkpoint_file_path)
|
|
load_param_into_net(net, param_dict)
|
|
input_shape = config.img_shape
|
|
inputs = np.ones([config.batch_size, 3, input_shape[0], input_shape[1]]).astype(np.float32)
|
|
export(net, Tensor(inputs), file_name=config.file_name, file_format=config.file_format)
|