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56 lines
1.9 KiB
56 lines
1.9 KiB
# 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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"""maskrcnn testing script."""
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import os
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import pytest
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import numpy as np
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from model_zoo.official.cv.maskrcnn.src.maskrcnn.mask_rcnn_r50 import Mask_Rcnn_Resnet50
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from model_zoo.official.cv.maskrcnn.src.config import config
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from mindspore import Tensor, context, export
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
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@pytest.mark.level0
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_maskrcnn_export():
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"""
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export maskrcnn air.
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"""
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net = Mask_Rcnn_Resnet50(config=config)
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net.set_train(False)
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bs = config.test_batch_size
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img = Tensor(np.zeros([bs, 3, 768, 1280], np.float16))
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img_metas = Tensor(np.zeros([bs, 4], np.float16))
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gt_bboxes = Tensor(np.zeros([bs, 128, 4], np.float16))
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gt_labels = Tensor(np.zeros([bs, 128], np.int32))
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gt_num = Tensor(np.zeros([bs, 128], np.bool))
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gt_mask = Tensor(np.zeros([bs, 128], np.bool))
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input_data = [img, img_metas, gt_bboxes, gt_labels, gt_num, gt_mask]
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export(net, *input_data, file_name="maskrcnn", file_format="AIR")
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file_name = "maskrcnn.air"
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assert os.path.exists(file_name)
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os.remove(file_name)
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if __name__ == '__main__':
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test_maskrcnn_export()
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