fix docs and add docstring check #210
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+ Coverage 94.05% 94.11% +0.05%
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Files 40 40
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docs/tutorials/dqn.rst
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| @@ -83,29 +87,32 @@ Tianshou supports any user-defined PyTorch networks and optimizers but with the | |||
| net = Net(state_shape, action_shape) | |||
| optim = torch.optim.Adam(net.parameters(), lr=1e-3) | |||
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| You can also have a try with those pre-defined networks in :mod:`~tianshou.utils.net.common`, :mod:`~tianshou.utils.net.discrete`, and :mod:`~tianshou.utils.net.continuous`. The rules of self-defined networks are: | |||
| You can have a try with those pre-defined networks in :mod:`~tianshou.utils.net.common`, :mod:`~tianshou.utils.net.discrete`, and :mod:`~tianshou.utils.net.continuous`. The rules of self-defined networks are: | |||
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"It is also possible to use pre-defined networks in ..."
Besides, I would rather present first the pre-defined networks available, rather than the custom one. I think it is more appropriate to come later.
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Besides, I would rather present first the pre-defined networks available, rather than the custom one. I think it is more appropriate to come later.
I don't agree since I want to give users the maximum freedom to define the network.
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Sure, but I think it is better to start with predefined network, to provide a extremely quick and concise way to run a learning algorithm to get the feeling of the dataflow of Tianshou, how easy it is to train a model, and how fast is Tianshou. Then you introduce a more advanced example now that the user is convince the lib fits its need. But that's just my opinion.
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Nice work ! I really appreciate your effort to keep the doc up to date and to clearly explain how to use Tianshou and make the best out of it. It is not so common nowaday. |
- fix broken links and out-of-the-date content - add pydocstyle and doc8 check - remove collector.seed and collector.render
cherry-pick from #200.