forked from OSSInnovation/mindspore
!12011 centernet README.md update
From: @caojian05 Reviewed-by: @wuxuejian,@liangchenghui Signed-off-by: @wuxuejian
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166e5f107b
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@ -157,8 +157,8 @@ bash scripts/run_standalone_eval_cpu.sh [RUN_MODE] [DATA_DIR] [LOAD_CHECKPOINT_P
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├── scripts
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│ ├── ascend_distributed_launcher
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│ │ ├──__init__.py
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│ │ ├──hyper_parameter_config.ini // hyper parameter for distributed pretraining
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│ │ ├──get_distribute_pretrain_cmd.py // script for distributed pretraining
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│ │ ├──hyper_parameter_config.ini // hyper parameter for distributed training
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│ │ ├──get_distribute_train_cmd.py // script for distributed training
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│ │ ├──README.md
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│ ├──convert_dataset_to_mindrecord.sh // shell script for converting coco type dataset to mindrecord
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│ ├──run_standalone_train_ascend.sh // shell script for standalone training on ascend
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@ -400,7 +400,7 @@ epoch: 0.0, current epoch percent: 0.00, step: 5, time of per steps: 45.213 s, o
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#### Running on Ascend
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```bash
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bash scripts/run_distributed_pretrain_ascend.sh /path/mindrecord_dataset /path/hccl.json /path/load_ckpt(optional)
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bash scripts/run_distributed_train_ascend.sh /path/mindrecord_dataset /path/hccl.json /path/load_ckpt(optional)
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```
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The command above will run in the background, you can view training logs in LOG*/training_log.txt and LOG*/ms_log/. After training finished, you will get some checkpoint files under the LOG*/ckpt_0 folder by default. The loss value will be displayed as follows:
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