Merge pull request !4666 from chengxb7532/mastertags/v0.7.0-beta
| @@ -66,7 +66,7 @@ To train the model, run `train.py`. If the `mindrecord_dir` is empty, it will ge | |||||
| sh run_distribute_train.sh 8 500 0.2 coco /data/hccl.json | sh run_distribute_train.sh 8 500 0.2 coco /data/hccl.json | ||||
| ``` | ``` | ||||
| The input parameters are device numbers, epoch size, learning rate, dataset mode and [hccl json configuration file](https://www.mindspore.cn/tutorial/en/master/advanced_use/distributed_training.html). **It is better to use absolute path.** | |||||
| The input parameters are device numbers, epoch size, learning rate, dataset mode and [hccl json configuration file](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools). **It is better to use absolute path.** | |||||
| You will get the loss value of each step as following: | You will get the loss value of each step as following: | ||||
| @@ -71,7 +71,7 @@ sh run_distribute_train.sh dataset/coco2014 yolov3_darknet_noquant_ckpt/0-320_10 | |||||
| sh run_standalone_train.sh dataset/coco2014 yolov3_darknet_noquant_ckpt/0-320_102400.ckpt | sh run_standalone_train.sh dataset/coco2014 yolov3_darknet_noquant_ckpt/0-320_102400.ckpt | ||||
| ``` | ``` | ||||
| > About rank_table.json, you can refer to the [distributed training tutorial](https://www.mindspore.cn/tutorial/en/master/advanced_use/distributed_training.html). | |||||
| > About rank_table.json, You can generate it by using the [hccl json configuration file](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools). | |||||
| #### Result | #### Result | ||||
| @@ -108,14 +108,14 @@ epoch[134], iter[86500], loss:34.303755, 145.18 imgs/sec, lr:1.6245529650404933e | |||||
| ``` | ``` | ||||
| # infer | # infer | ||||
| sh run_eval.sh [DATASET_PATH] [CHECKPOINT_PATH] | |||||
| sh run_eval.sh [DATASET_PATH] [CHECKPOINT_PATH] [DEVICE_ID] | |||||
| ``` | ``` | ||||
| #### Launch | #### Launch | ||||
| ```bash | ```bash | ||||
| # infer with checkpoint | # infer with checkpoint | ||||
| sh run_eval.sh dataset/coco2014/ checkpoint/0-135.ckpt | |||||
| sh run_eval.sh dataset/coco2014/ checkpoint/0-131.ckpt 0 | |||||
| ``` | ``` | ||||
| @@ -51,7 +51,7 @@ To train the model, run `train.py` with the dataset `image_dir`, `anno_path` and | |||||
| sh run_distribute_train.sh 8 150 /data/Mindrecord_train /data /data/train.txt /data/hccl.json | sh run_distribute_train.sh 8 150 /data/Mindrecord_train /data /data/train.txt /data/hccl.json | ||||
| ``` | ``` | ||||
| The input variables are device numbers, epoch size, mindrecord directory path, dataset directory path, train TXT file path and [hccl json configuration file](https://www.mindspore.cn/tutorial/en/master/advanced_use/distributed_training.html). **It is better to use absolute path.** | |||||
| The input variables are device numbers, epoch size, mindrecord directory path, dataset directory path, train TXT file path and [hccl json configuration file](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools). **It is better to use absolute path.** | |||||
| You will get the loss value and time of each step as following: | You will get the loss value and time of each step as following: | ||||