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[Documentation] cleaned repo and additional semantic changes

/develop-generalizationTraining-TrainerController
vincentpierre 6 年前
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共有 6 个文件被更改,包括 96 次插入113 次删除
  1. 2
      docs/Learning-Environment-Design-Brains.md
  2. 2
      docs/Using-Docker.md
  3. 202
      docs/images/internal_brain.png
  4. 3
      docs/Installation-Docker.md
  5. 0
      /docs/images/docker_build_settings.png

2
docs/Learning-Environment-Design-Brains.md


* `Graph Model` : This must be the `bytes` file corresponding to the pretrained Tensorflow graph. (You must first drag this file into your Resources folder and then from the Resources folder into the inspector)
* `Graph Scope` : If you set a scope while training your TensorFlow model, all your placeholder name will have a prefix. You must specify that prefix here.
* `Batch Size Node Name` : If the batch size is one of the inputs of your graph, you must specify the name if the placeholder here. The brain will make the batch size equal to the number of agents connected to the brain automatically.
* `State Node Name` : If your graph uses the state as an input, you must specify the name if the placeholder here.
* `Vector Observation Node Name` : If your graph uses a vector observation as an input, you must specify the name if the placeholder here.
* `Recurrent Input Node Name` : If your graph uses a recurrent input / memory as input and outputs new recurrent input / memory, you must specify the name if the input placeholder here.
* `Recurrent Output Node Name` : If your graph uses a recurrent input / memory as input and outputs new recurrent input / memory, you must specify the name if the output placeholder here.
* `Visual Observation Placeholder Name` : If your graph uses observations as input, you must specify it here. Note that the number of observations is equal to the length of `Camera Resolutions` in the brain parameters.

2
docs/Using-Docker.md


Unity environment **has** to be built for the **linux platform**. From the Build Settings Window, please select the architecture to be `x86_64` and choose the build to be `headless` (_This is important because we are running it in a container that does not have graphics drivers installed_).
Save the generated environment in the directory to be mounted (e.g. we have conveniently created an empty directory called at the top level `unity-volume`).
![Build Settings For Docker](../images/docker_build_settings.png)
![Build Settings For Docker](images/docker_build_settings.png)
- Ensure that `unity-volume/<environment-name>.x86_64` and `unity-volume/environment-name_Data`. So for example, `<environment_name>` might be `3Dball` and you might want to ensure that `unity-volume/3Dball.x86_64` and `unity-volume/3Dball_Data` are both present in the directory `unity-volume`.

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docs/images/internal_brain.png

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3
docs/Installation-Docker.md


# Docker Set-up _[Experimental]_
**Work In Progress**

/images/docker_build_settings.png → /docs/images/docker_build_settings.png

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