Col_lin
/
mindspore2022
forked from huawei/mindspore2022
0
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

!6565 fix launch of inceptionv3 

Merge pull request !6565 from zhouyaqiang0/master
This commit is contained in:
mindspore-ci-bot 2020-09-20 20:07:03 +08:00 committed by Gitee
parent 47c4b873a3 57a6ec3c08
commit e2e1603c49
1 changed files with 10 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

20
model_zoo/official/cv/inceptionv3/README.md
View File

@ -127,9 +127,9 @@ You can start training using python or shell scripts. The usage of shell scripts
- Ascend:
```
# distribute training example(8p)
sh run_distribute_train.sh RANK_TABLE_FILE DATA_PATH
sh scripts/run_distribute_train.sh RANK_TABLE_FILE DATA_PATH
# standalone training
sh run_standalone_train.sh DEVICE_ID DATA_PATH
sh scripts/run_standalone_train.sh DEVICE_ID DATA_PATH
```
> Notes:
RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/tutorial/training/en/master/advanced_use/distributed_training_ascend.html) , and the device_ip can be got as [Link]https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.
@ -139,9 +139,9 @@ sh run_standalone_train.sh DEVICE_ID DATA_PATH
- GPU:
```
# distribute training example(8p)
sh run_distribute_train_gpu.sh DATA_DIR
sh scripts/run_distribute_train_gpu.sh DATA_DIR
# standalone training
sh run_standalone_train_gpu.sh DEVICE_ID DATA_DIR
sh scripts/run_standalone_train_gpu.sh DEVICE_ID DATA_DIR
```
### Launch
@ -155,9 +155,9 @@ sh run_standalone_train_gpu.sh DEVICE_ID DATA_DIR
shell:
Ascend:
# distribute training example(8p)
sh run_distribute_train.sh RANK_TABLE_FILE DATA_PATH
sh scripts/run_distribute_train.sh RANK_TABLE_FILE DATA_PATH
# standalone training
sh run_standalone_train.sh DEVICE_ID DATA_PATH
sh scripts/run_standalone_train.sh DEVICE_ID DATA_PATH
GPU:
# distributed training example(8p)
sh scripts/run_distribute_train_gpu.sh /dataset/train
@ -183,11 +183,11 @@ You can start training using python or shell scripts. The usage of shell scripts
- Ascend:
```
sh run_eval.sh DEVICE_ID DATA_DIR PATH_CHECKPOINT
sh scripts/run_eval.sh DEVICE_ID DATA_DIR PATH_CHECKPOINT
```
- GPU:
```
sh run_eval_gpu.sh DEVICE_ID DATA_DIR PATH_CHECKPOINT
sh scripts/run_eval_gpu.sh DEVICE_ID DATA_DIR PATH_CHECKPOINT
```
### Launch
@ -199,8 +199,8 @@ You can start training using python or shell scripts. The usage of shell scripts
GPU: python eval.py --dataset_path DATA_DIR --checkpoint PATH_CHECKPOINT --platform GPU
shell:
Ascend: sh run_eval.sh DEVICE_ID DATA_DIR PATH_CHECKPOINT
GPU: sh run_eval_gpu.sh DEVICE_ID DATA_DIR PATH_CHECKPOINT
Ascend: sh scripts/run_eval.sh DEVICE_ID DATA_DIR PATH_CHECKPOINT
GPU: sh scripts/run_eval_gpu.sh DEVICE_ID DATA_DIR PATH_CHECKPOINT
```
> checkpoint can be produced in training process.