At line 205, I believe the code `x = self.activations[act](x)` should be indented so that it is in the body of the for loop. Otherwise, applying the four linear modules has the same effect as applying a single linear module, in the sense that it is still just a linear map so there is no point in having four of them. In other words, each layer of this network should have a nonlinearity.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/139667
Approved by: https://github.com/malfet
Summary:
This PR expands the [note on modules](https://pytorch.org/docs/stable/notes/modules.html) with additional info for 1.10.
It adds the following:
* Examples of using hooks
* Examples of using apply()
* Examples for ParameterList / ParameterDict
* register_parameter() / register_buffer() usage
* Discussion of train() / eval() modes
* Distributed training overview / links
* TorchScript overview / links
* Quantization overview / links
* FX overview / links
* Parametrization overview / link to tutorial
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63963
Reviewed By: albanD
Differential Revision: D30606604
Pulled By: jbschlosser
fbshipit-source-id: c1030b19162bcb5fe7364bcdc981a2eb6d6e89b4
