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docs: change links to https (#12258)

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Summary:
Hi, I think it might be better to use https instead of http in the README.md.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12258

Differential Revision: D10162279

Pulled By: soumith

fbshipit-source-id: 4658aa75175909b4fea6972b437765d8b49c749f
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Ir1dXD
2018-10-03 06:26:16 -07:00
committed by Facebook Github Bot
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@ -77,7 +77,7 @@ change the way your network behaves arbitrarily with zero lag or overhead. Our i
from several research papers on this topic, as well as current and past work such as
[torch-autograd](https://github.com/twitter/torch-autograd),
[autograd](https://github.com/HIPS/autograd),
[Chainer](http://chainer.org), etc.
[Chainer](https://chainer.org), etc.
While this technique is not unique to PyTorch, it's one of the fastest implementations of it to date.
You get the best of speed and flexibility for your crazy research.
@ -121,10 +121,10 @@ Writing new neural network modules, or interfacing with PyTorch's Tensor API was
and with minimal abstractions.
You can write new neural network layers in Python using the torch API
[or your favorite NumPy-based libraries such as SciPy](http://pytorch.org/tutorials/advanced/numpy_extensions_tutorial.html).
[or your favorite NumPy-based libraries such as SciPy](https://pytorch.org/tutorials/advanced/numpy_extensions_tutorial.html).
If you want to write your layers in C/C++, we provide a convenient extension API that is efficient and with minimal boilerplate.
There is no wrapper code that needs to be written. You can see [a tutorial here](http://pytorch.org/tutorials/advanced/cpp_extension.html) and [an example here](https://github.com/pytorch/extension-cpp).
There is no wrapper code that needs to be written. You can see [a tutorial here](https://pytorch.org/tutorials/advanced/cpp_extension.html) and [an example here](https://github.com/pytorch/extension-cpp).
## Installation
@ -132,7 +132,7 @@ There is no wrapper code that needs to be written. You can see [a tutorial here]
### Binaries
Commands to install from binaries via Conda or pip wheels are on our website:
[http://pytorch.org](http://pytorch.org)
[https://pytorch.org](https://pytorch.org)
### From Source
@ -239,7 +239,7 @@ You can then build the documentation by running ``make <format>`` from the
### Previous Versions
Installation instructions and binaries for previous PyTorch versions may be found
on [our website](http://pytorch.org/previous-versions).
on [our website](https://pytorch.org/previous-versions).
## Getting Started
@ -247,13 +247,13 @@ on [our website](http://pytorch.org/previous-versions).
Three pointers to get you started:
- [Tutorials: get you started with understanding and using PyTorch](https://pytorch.org/tutorials/)
- [Examples: easy to understand pytorch code across all domains](https://github.com/pytorch/examples)
- [The API Reference](http://pytorch.org/docs/)
- [The API Reference](https://pytorch.org/docs/)
## Communication
* forums: discuss implementations, research, etc. http://discuss.pytorch.org
* forums: discuss implementations, research, etc. https://discuss.pytorch.org
* GitHub issues: bug reports, feature requests, install issues, RFCs, thoughts, etc.
* Slack: general chat, online discussions, collaboration etc. https://pytorch.slack.com/ . Our slack channel is invite-only to promote a healthy balance between power-users and beginners. If you need a slack invite, ping us at slack@pytorch.org
* newsletter: no-noise, one-way email newsletter with important announcements about pytorch. You can sign-up here: http://eepurl.com/cbG0rv
* newsletter: no-noise, one-way email newsletter with important announcements about pytorch. You can sign-up here: https://eepurl.com/cbG0rv
## Releases and Contributing