mindspore/model_zoo/official/cv/yolov3_darknet53/export.py

50 lines
1.8 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.
# ============================================================================
import os
import numpy as np
import mindspore as ms
from mindspore import context, Tensor
from mindspore.train.serialization import export, load_checkpoint, load_param_into_net
from src.yolo import YOLOV3DarkNet53
from model_utils.config import config
from model_utils.moxing_adapter import moxing_wrapper
def modelarts_pre_process():
'''modelarts pre process function.'''
config.file_name = os.path.join(config.output_path, config.file_name)
@moxing_wrapper(pre_process=modelarts_pre_process)
def run_export():
context.set_context(mode=context.GRAPH_MODE, device_target=config.device_target)
if config.device_target == "Ascend":
context.set_context(device_id=config.device_id)
network = YOLOV3DarkNet53(is_training=False)
param_dict = load_checkpoint(config.ckpt_file)
load_param_into_net(network, param_dict)
network.set_train(False)
shape = [config.batch_size, 3] + config.test_img_shape
input_data = Tensor(np.zeros(shape), ms.float32)
export(network, input_data, file_name=config.file_name, file_format=config.file_format)
if __name__ == "__main__":
run_export()