From 4cacd650a3ed45d3d3d8a9a347c7d1a2b5367764 Mon Sep 17 00:00:00 2001 From: chenzomi Date: Fri, 10 Jul 2020 15:33:23 +0800 Subject: [PATCH] change log --- .../advanced_use/distributed_training.md | 20 ++++++++--------- .../source_en/quick_start/quick_start.md | 21 ++++++------------ .../advanced_use/distributed_training.md | 22 +++++++++---------- .../source_zh_cn/quick_start/quick_start.md | 14 ++++-------- 4 files changed, 32 insertions(+), 45 deletions(-) diff --git a/tutorials/source_en/advanced_use/distributed_training.md b/tutorials/source_en/advanced_use/distributed_training.md index 20cd61d625..f3e67908ad 100644 --- a/tutorials/source_en/advanced_use/distributed_training.md +++ b/tutorials/source_en/advanced_use/distributed_training.md @@ -344,14 +344,14 @@ The running time is about 5 minutes, which is mainly occupied by operator compil Log files are saved in the `device` directory. The `env.log` file records environment variable information. The `train.log` file records the loss function information. The following is an example: ``` -epoch: 1 step: 156, loss is 2.0084016 -epoch: 2 step: 156, loss is 1.6407638 -epoch: 3 step: 156, loss is 1.6164391 -epoch: 4 step: 156, loss is 1.6838071 -epoch: 5 step: 156, loss is 1.6320667 -epoch: 6 step: 156, loss is 1.3098773 -epoch: 7 step: 156, loss is 1.3515002 -epoch: 8 step: 156, loss is 1.2943741 -epoch: 9 step: 156, loss is 1.2316195 -epoch: 10 step: 156, loss is 1.1533381 +Epoch: [1 /10], step: [156/156], loss: [2.0084], avg loss: [2.0000] +Epoch: [2 /10], step: [156/156], loss: [1.6407], avg loss: [1.8000] +Epoch: [3 /10], step: [156/156], loss: [1.6164], avg loss: [1.7066] +Epoch: [4 /10], step: [156/156], loss: [1.6838], avg loss: [1.7597] +Epoch: [5 /10], step: [156/156], loss: [1.6320], avg loss: [1.6504] +Epoch: [6 /10], step: [156/156], loss: [1.3098], avg loss: [1.4504] +Epoch: [7 /10], step: [156/156], loss: [1.3515], avg loss: [1.3940] +Epoch: [8 /10], step: [156/156], loss: [1.2943], avg loss: [1.3089] +Epoch: [9 /10], step: [156/156], loss: [1.2316], avg loss: [1.2694] +Epoch: [10/10], step: [156/156], loss: [1.1533], avg loss: [1.1504] ``` diff --git a/tutorials/source_en/quick_start/quick_start.md b/tutorials/source_en/quick_start/quick_start.md index 500c9614e3..757d5bb416 100644 --- a/tutorials/source_en/quick_start/quick_start.md +++ b/tutorials/source_en/quick_start/quick_start.md @@ -373,23 +373,16 @@ In the preceding information: `Lenet. Py`: the script file you wrote. `--device_target CPU`: Specify the hardware platform.The parameters are 'CPU', 'GPU' or 'Ascend'. -Loss values are output during training, as shown in the following figure. Although loss values may fluctuate, they gradually decrease and the accuracy gradually increases in general. Loss values displayed each time may be different because of their randomicity. +Loss values are output during training. Although loss values may fluctuate, they gradually decrease and the accuracy gradually increases in general. Loss values displayed each time may be different because of their randomicity. The following is an example of loss values output during training: ```bash ... -epoch: 1 step: 262, loss is 1.9212162 -epoch: 1 step: 263, loss is 1.8498616 -epoch: 1 step: 264, loss is 1.7990671 -epoch: 1 step: 265, loss is 1.9492403 -epoch: 1 step: 266, loss is 2.0305142 -epoch: 1 step: 267, loss is 2.0657792 -epoch: 1 step: 268, loss is 1.9582214 -epoch: 1 step: 269, loss is 0.9459006 -epoch: 1 step: 270, loss is 0.8167224 -epoch: 1 step: 271, loss is 0.7432692 -... +Epoch: [1 /10], step: [262/900], loss: [1.9212], avg loss: [1.9222] +Epoch: [1 /10], step: [263/900], loss: [1.8498], avg loss: [1.9200] +Epoch: [1 /10], step: [264/900], loss: [1.7990], avg loss: [1.8542] +Epoch: [1 /10], step: [265/900], loss: [1.9492], avg loss: [1.8640] ``` The following is an example of model files saved after training: @@ -419,7 +412,7 @@ def test_net(args,network,model,mnist_path): #load testing dataset ds_eval = create_dataset(os.path.join(mnist_path, "test")) # test acc = model.eval(ds_eval, dataset_sink_mode=False) - print("============== Accuracy:{} ==============".format(acc)) + print("============== {} ==============".format(acc)) if __name__ == "__main__": ... @@ -444,7 +437,7 @@ Command output similar to the following is displayed: ``` ============== Starting Testing ============== -============== Accuracy:{'Accuracy': 0.9742588141025641} ============== +============== {'Accuracy': 0.9742588141025641} ============== ``` The model accuracy data is displayed in the output content. In the example, the accuracy reaches 97.4%, indicating a good model quality. diff --git a/tutorials/source_zh_cn/advanced_use/distributed_training.md b/tutorials/source_zh_cn/advanced_use/distributed_training.md index 52627db1c5..22bc41e4a3 100644 --- a/tutorials/source_zh_cn/advanced_use/distributed_training.md +++ b/tutorials/source_zh_cn/advanced_use/distributed_training.md @@ -342,14 +342,14 @@ cd ../ 日志文件保存`device`目录下，`env.log`中记录了环境变量的相关信息，关于Loss部分结果保存在`train.log`中，示例如下： ``` -epoch: 1 step: 156, loss is 2.0084016 -epoch: 2 step: 156, loss is 1.6407638 -epoch: 3 step: 156, loss is 1.6164391 -epoch: 4 step: 156, loss is 1.6838071 -epoch: 5 step: 156, loss is 1.6320667 -epoch: 6 step: 156, loss is 1.3098773 -epoch: 7 step: 156, loss is 1.3515002 -epoch: 8 step: 156, loss is 1.2943741 -epoch: 9 step: 156, loss is 1.2316195 -epoch: 10 step: 156, loss is 1.1533381 -``` +Epoch: [1 /10], step: [156/156], loss: [2.0084], avg loss: [2.0000] +Epoch: [2 /10], step: [156/156], loss: [1.6407], avg loss: [1.8000] +Epoch: [3 /10], step: [156/156], loss: [1.6164], avg loss: [1.7066] +Epoch: [4 /10], step: [156/156], loss: [1.6838], avg loss: [1.7597] +Epoch: [5 /10], step: [156/156], loss: [1.6320], avg loss: [1.6504] +Epoch: [6 /10], step: [156/156], loss: [1.3098], avg loss: [1.4504] +Epoch: [7 /10], step: [156/156], loss: [1.3515], avg loss: [1.3940] +Epoch: [8 /10], step: [156/156], loss: [1.2943], avg loss: [1.3089] +Epoch: [9 /10], step: [156/156], loss: [1.2316], avg loss: [1.2694] +Epoch: [10/10], step: [156/156], loss: [1.1533], avg loss: [1.1504] +``` \ No newline at end of file diff --git a/tutorials/source_zh_cn/quick_start/quick_start.md b/tutorials/source_zh_cn/quick_start/quick_start.md index 19a7c8e7a4..606820414a 100644 --- a/tutorials/source_zh_cn/quick_start/quick_start.md +++ b/tutorials/source_zh_cn/quick_start/quick_start.md @@ -380,16 +380,10 @@ python lenet.py --device_target=CPU ```bash ... -epoch: 1 step: 262, loss is 1.9212162 -epoch: 1 step: 263, loss is 1.8498616 -epoch: 1 step: 264, loss is 1.7990671 -epoch: 1 step: 265, loss is 1.9492403 -epoch: 1 step: 266, loss is 2.0305142 -epoch: 1 step: 267, loss is 2.0657792 -epoch: 1 step: 268, loss is 1.9582214 -epoch: 1 step: 269, loss is 0.9459006 -epoch: 1 step: 270, loss is 0.8167224 -epoch: 1 step: 271, loss is 0.7432692 +Epoch: [1 /10], step: [262/900], loss: [1.9212], avg loss: [1.9222] +Epoch: [1 /10], step: [263/900], loss: [1.8498], avg loss: [1.9200] +Epoch: [1 /10], step: [264/900], loss: [1.7990], avg loss: [1.8542] +Epoch: [1 /10], step: [265/900], loss: [1.9492], avg loss: [1.8640] ... ``` -- Gitee