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psenet readme update
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@ -105,7 +105,10 @@ sh scripts/run_eval_ascend.sh
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├── Makefile
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├── config.py // parameter configuration
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├── dataset.py // creating dataset
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├── lr_schedule.py // learning ratio generation
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└── network_define.py // PSENet architecture
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├── export.py // export mindir file
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├── mindspore_hub_conf.py // hub config file
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├── test.py // test script
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└── train.py // training script
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@ -132,6 +135,7 @@ Major parameters in train.py and config.py are:
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sh scripts/run_distribute_train.sh rank_table_file pretrained_model.ckpt
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```
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rank_table_file which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
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The above shell script will run distribute training in the background. You can view the results through the file
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`device[X]/test_*.log`. The loss value will be achieved as follows:
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@ -1,14 +0,0 @@
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# 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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@ -28,6 +28,7 @@
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using std::vector;
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using std::queue;
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using std::swap;
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using cv::Mat;
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using cv::Point;
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