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Chris Elion
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Add installation section and known issues (#2920)
* Add installation section and known issues * update wording
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docs/FAQ.md

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# Frequently Asked Questions
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## Installation problems
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### Tensorflow dependency
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ML Agents requires TensorFlow; if you don't already have it installed, `pip` will try to install it when you install
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the ml-agents package.
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If you see a message like this
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```console
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ERROR: Could not find a version that satisfies the requirement tensorflow<2.0,>=1.7 (from mlagents) (from versions: none)
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ERROR: No matching distribution found for tensorflow<2.0,>=1.7 (from mlagents)
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```
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it means that there is no version of TensorFlow for your python environment. Some known potential causes are:
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* You're using 32-bit python instead of 64-bit. See the answer [here](https://stackoverflow.com/a/1405971/224264)
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for how to tell which you have installed.
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* You're using python 3.8. Tensorflow plans to release packages for this as soon as possible; see
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[this issue](https://github.com/tensorflow/tensorflow/issues/33374) for more details.
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* You have the `tensorflow-gpu` package installed. This is equivalent to `tensorflow`, however `pip` doesn't recognize
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this. The best way to resolve this is to update to `tensorflow==1.15.0` which provides GPU support in the same package
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(see the [release notes](https://github.com/tensorflow/tensorflow/issues/33374) for more details.)
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* You're on another architecture (e.g. ARM) which requires vendor provided packages.
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In all of these cases, the issue is a pip/python environment setup issue. Please search the tensorflow github issues
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for similar problems and solutions before creating a new issue.
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## Scripting Runtime Environment not setup correctly
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If you haven't switched your scripting runtime version from .NET 3.5 to .NET 4.6
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## Problems with training on AWS
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Please refer to [Training on Amazon Web Service FAQ](Training-on-Amazon-Web-Service.md#faq)
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# Known Issues
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## Release 0.10.0
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* ml-agents 0.10.0 and earlier were incompatible with TensorFlow 1.15.0; the graph could contain
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an operator that `tensorflow_to_barracuda` didn't handle. This was fixed in the 0.11.0 release.

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