diff --git a/docs/Getting-Started.md b/docs/Getting-Started.md index 05079d5a45..5732135208 100644 --- a/docs/Getting-Started.md +++ b/docs/Getting-Started.md @@ -211,7 +211,7 @@ directory. In order to observe the training process in more detail, you can use TensorBoard. From the command line run: ```sh -tensorboard --logdir=results +tensorboard --logdir results ``` Then navigate to `localhost:6006` in your browser to view the TensorBoard diff --git a/docs/Training-on-Microsoft-Azure.md b/docs/Training-on-Microsoft-Azure.md index f09787d3a2..ee57a9b82e 100644 --- a/docs/Training-on-Microsoft-Azure.md +++ b/docs/Training-on-Microsoft-Azure.md @@ -101,7 +101,7 @@ Once you have started training, you can 2. Unless you started the training as a background process, connect to your VM from another terminal instance. 3. Run the following command from your terminal - `tensorboard --logdir=summaries --host 0.0.0.0` + `tensorboard --logdir results --host 0.0.0.0` 4. You should now be able to open a browser and navigate to `:6060` to view the TensorBoard report. diff --git a/docs/Using-Docker.md b/docs/Using-Docker.md index f2922964f8..000478f345 100644 --- a/docs/Using-Docker.md +++ b/docs/Using-Docker.md @@ -150,13 +150,13 @@ You can run Tensorboard to monitor your training instance on http://localhost:6006: ```sh -docker exec -it tensorboard --logdir=/unity-volume/summaries --host=0.0.0.0 +docker exec -it tensorboard --logdir /unity-volume/results --host 0.0.0.0 ``` With our previous 3DBall example, this command would look like this: ```sh -docker exec -it 3DBallContainer.first.trial tensorboard --logdir=/unity-volume/summaries --host=0.0.0.0 +docker exec -it 3DBallContainer.first.trial tensorboard --logdir /unity-volume/results --host 0.0.0.0 ``` For more details on Tensorboard, check out the documentation about diff --git a/docs/Using-Tensorboard.md b/docs/Using-Tensorboard.md index b2a54a0b2b..1ea2fcbaad 100644 --- a/docs/Using-Tensorboard.md +++ b/docs/Using-Tensorboard.md @@ -12,7 +12,7 @@ start TensorBoard: 1. Open a terminal or console window: 1. Navigate to the directory where the ML-Agents Toolkit is installed. -1. From the command line run: `tensorboard --logdir=results --port=6006` +1. From the command line run: `tensorboard --logdir results --port 6006` 1. Open a browser window and navigate to [localhost:6006](http://localhost:6006). diff --git a/docs/localized/zh-CN/docs/Getting-Started-with-Balance-Ball.md b/docs/localized/zh-CN/docs/Getting-Started-with-Balance-Ball.md index 3feade860e..8e31bc7f41 100755 --- a/docs/localized/zh-CN/docs/Getting-Started-with-Balance-Ball.md +++ b/docs/localized/zh-CN/docs/Getting-Started-with-Balance-Ball.md @@ -274,10 +274,10 @@ python3 python/learn.py --run-id= --train ### 观测训练进度 开始使用 `learn.py` 按照前面部分所述的方式进行训练后，`ml-agents` 文件夹将 -包含一个 `summaries` 目录。为了更详细地观测训练过程， +包含一个 `results` 目录。为了更详细地观测训练过程， 您可以使用 TensorBoard。从命令行中运行： -`tensorboard --logdir=summaries` +`tensorboard --logdir results` 然后导航至 `localhost:6006`。