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- # Copyright 2020-2021 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, onnx, mindir models"""
- import numpy as np
-
- import mindspore as ms
- from mindspore import Tensor
- from src.model_utils.config import config
- from src.model_utils.moxing_adapter import moxing_wrapper
- from src.model_utils.device_adapter import get_device_id
- from src.FasterRcnn.faster_rcnn import FasterRcnn_Infer
-
- ms.set_context(mode=ms.GRAPH_MODE, device_target=config.device_target, max_call_depth=2000)
- if config.device_target == "Ascend":
- ms.set_context(device_id=get_device_id())
-
-
- def modelarts_pre_process():
- pass
-
-
- @moxing_wrapper(pre_process=modelarts_pre_process)
- def export_fasterrcnn():
- """ export_fasterrcnn """
- config.restore_bbox = True
- config.ori_h = None
- config.ori_w = None
- net = FasterRcnn_Infer(config=config)
-
- try:
- param_dict = ms.load_checkpoint(config.ckpt_file)
- except RuntimeError as ex:
- ex = str(ex)
- print("Traceback:\n", ex, flush=True)
- if "reg_scores.weight" in ex:
- exit("[ERROR] The loss calculation of faster_rcnn has been updated. "
- "If the training is on an old version, please set `without_bg_loss` to False.")
-
- param_dict_new = {}
- for key, value in param_dict.items():
- key = key.replace("ncek", "neck")
- param_dict_new["network." + key] = value
-
- ms.load_param_into_net(net, param_dict_new)
-
- device_type = "Ascend" if ms.get_context("device_target") == "Ascend" else "Others"
- if device_type == "Ascend":
- net.to_float(ms.float16)
-
- img = Tensor(np.zeros([config.test_batch_size, 3, config.img_height, config.img_width]), ms.float32)
- img_metas = Tensor(np.random.uniform(0.0, 1.0, size=[config.test_batch_size, 4]), ms.float32)
-
- if not config.restore_bbox:
- print("[WARNING] When parameter 'restore_bbox' set to False, "
- "ascend310_infer of this project provided will not be available "
- "and need to complete 310 infer function by yourself.")
- ms.export(net, img, file_name=config.file_name, file_format=config.file_format)
- else:
- ms.export(net, img, img_metas, file_name=config.file_name, file_format=config.file_format)
-
-
- if __name__ == '__main__':
- export_fasterrcnn()
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