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

# Copyright 2021 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, mindir models"""
import argparse
import numpy as np

import mindspore as ms
from mindspore import Tensor, load_checkpoint, load_param_into_net, export, context

from src.Deeptext.deeptext_vgg16 import Deeptext_VGG16_Infer
from src.config import config

parser = argparse.ArgumentParser(description='deeptext 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("--file_name", type=str, default="deeptext", help="output file name.")
parser.add_argument("--file_format", type=str, choices=["AIR", "MINDIR"], default="MINDIR", help="file format")
parser.add_argument("--device_target", type=str, choices=["Ascend", "GPU", "CPU"], default="Ascend",
                    help="device target")
parser.add_argument('--ckpt_file', type=str, default='', help='deeptext ckpt file.')
args = parser.parse_args()

config.test_batch_size = args.batch_size
context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target)
context.set_context(device_id=args.device_id)

if __name__ == '__main__':
    net = Deeptext_VGG16_Infer(config=config)
    net.set_train(False)

    param_dict = load_checkpoint(args.ckpt_file)

    param_dict_new = {}
    for key, value in param_dict.items():
        param_dict_new["network." + key] = value

    load_param_into_net(net, param_dict_new)

    img_data = Tensor(np.zeros([config.test_batch_size, 3, config.img_height, config.img_width]), ms.float32)

    export(net, img_data, file_name=args.file_name, file_format=args.file_format)