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fix dpn&xception spelling error

This commit is contained in:
pengyanjun 2021-01-30 10:53:57 +08:00
parent 8a61767f32
commit f6eccdb4b0
3 changed files with 4 additions and 4 deletions
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2
model_zoo/official/cv/dpn/README.md
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@ -183,7 +183,7 @@ For example, you can run the shell command below to launch the training procedur
sh scripts/train_standalone.sh 0 /data/dataset/imagenet/ scripts/pretrian/ 0
```
If eval_each_epoch is 1, it will evaluate after each epoch and save the parameters with the max accurracy. But in this case, the time of one epoch will be longer.
If eval_each_epoch is 1, it will evaluate after each epoch and save the parameters with the max accuracy. But in this case, the time of one epoch will be longer.
If eval_each_epoch is 0, it will save parameters every some epochs instead of evaluating in the training process.

2
model_zoo/official/cv/dpn/train.py
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@ -91,7 +91,7 @@ def dpn_train(args):
context.set_auto_parallel_context(device_num=args.group_size, parallel_mode=ParallelMode.DATA_PARALLEL,
gradients_mean=True)
# select for master rank save ckpt or all rank save, compatiable for model parallel
# select for master rank save ckpt or all rank save, compatible for model parallel
args.rank_save_ckpt_flag = 0
if args.is_save_on_master:
if args.rank == 0:

4
model_zoo/official/cv/xception/README.md
View File

@ -148,7 +148,7 @@ sh scripts/run_standalone_train.sh DEVICE_ID DATA_PATH
### Result
Training result will be stored in the example path. Checkpoints will be stored at `. /ckpt_0` by default, and training log will be redirected to `log.txt` like followings.
Training result will be stored in the example path. Checkpoints will be stored at `. /ckpt_0` by default, and training log will be redirected to `log.txt` like following.
``` shell
epoch: 1 step: 1251, loss is 4.8427444
@ -182,7 +182,7 @@ sh scripts/run_eval.sh DEVICE_ID DATA_DIR PATH_CHECKPOINT
### Result
Evaluation result will be stored in the example path, you can find result like the followings in `eval.log`.
Evaluation result will be stored in the example path, you can find result like the following in `eval.log`.
```shell
result: {'Loss': 1.7797744848789312, 'Top_1_Acc': 0.7985777243589743, 'Top_5_Acc': 0.9485777243589744}