* Improvize documentation
1. Add formula for erf, erfinv
2. Make exp, expm1 similar to log, log1p
3. Symbol change in ge, le, ne, isnan
* Fix minor nit in the docstring
* More doc improvements
1. Added some formulae
2. Complete scanning till "Other Operations" in Tensor docs
* Add more changes
1. Modify all torch.Tensor wherever required
* Fix Conv docs
1. Fix minor nits in the references for LAPACK routines
* Improve Pooling docs
1. Fix lint error
* Improve docs for RNN, Normalization and Padding
1. Fix flake8 error for pooling
* Final fixes for torch.nn.* docs.
1. Improve Loss Function documentation
2. Improve Vision Layers documentation
* Fix lint error
* Improve docstrings in torch.nn.init
* Fix lint error
* Fix minor error in torch.nn.init.sparse
* Fix Activation and Utils Docs
1. Fix Math Errors
2. Add explicit clean to Makefile in docs to prevent running graph generation script
while cleaning
3. Fix utils docs
* Make PYCMD a Makefile argument, clear up prints in the build_activation_images.py
* Fix batch norm doc error
The nn.* counterpart of #5443 . Mostly removed Variable wrapper. Also added doc for nn.RReLU.
Notice that torch.randn(*, requires_grad=True) isn't documented until #5462 is done.
Adds a missing bias term to the __repr__ functions of the
Linear and Bilinear modules. Fixes the spacing in the Conv2d
__repr__ to make it consistent with other modules.
* Add a bit of notation explanation
For a first time user of Conv1d, it is not clear from documentation what N, C and L exactly mean. This should clarify this. Same for Conv2d.
3D modules apply padding on all three sides. "Both" doesn't make sense here.
I used the wording of the AvgPool3d docstring, where it was already correct.
Here's the command I used to invoke autopep8 (in parallel!):
git ls-files | grep '\.py$' | xargs -n1 -P`nproc` autopep8 -i
Several rules are ignored in setup.cfg. The goal is to let autopep8
handle everything which it can handle safely, and to disable any rules
which are tricky or controversial to address. We may want to come back
and re-enable some of these rules later, but I'm trying to make this
patch as safe as possible.
Also configures flake8 to match pep8's behavior.
Also configures TravisCI to check the whole project for lint.
Transposed convolutions are often (but incorrectly) referred to as Deconvolutional operations. Made mention of this in the docstring to make it easier for people to search for this operation in the documentation.
Uses the assignment syntax to get deterministic ordering of parameters.
The ordering of parameters using the constructor syntax is
non-deterministic because kwargs use dict() in Python 3.5 and earlier.
* Conv2d, MaxPool2d, and AvgPool2d have one argument for each of ksize,
stride, and pad. This argument can be either a single number or a
tuple of (h, w)
* _forward is renamed forward since users should override it
* some __call__ overrides are changed to forward
* function which return a single variable are changed to return that
variable instead of a one-element tuple
