diff --git a/README.md b/README.md
index 73a01a2a0dd..040783fe781 100644
--- a/README.md
+++ b/README.md
@@ -20,7 +20,7 @@ You can reuse your favorite Python packages such as NumPy, SciPy and Cython to e
- [Releases and Contributing](#releases-and-contributing)
- [The Team](#the-team)
-| System | 2.7 | 3.5 | 3.6 |
+| System | 3.6 | 3.7 | 3.8 |
| :---: | :---: | :---: | :--: |
| Linux CPU | [](https://ci.pytorch.org/jenkins/job/pytorch-master/) | [](https://ci.pytorch.org/jenkins/job/pytorch-master/) | — |
| Linux GPU | [](https://ci.pytorch.org/jenkins/job/pytorch-master/) | [](https://ci.pytorch.org/jenkins/job/pytorch-master/) | — |
@@ -139,10 +139,8 @@ Commands to install from binaries via Conda or pip wheels are on our website:
Python wheels for NVIDIA's Jetson Nano, Jetson TX2, and Jetson AGX Xavier are available via the following URLs:
- Stable binaries:
- - Python 2.7: https://nvidia.box.com/v/torch-stable-cp27-jetson-jp42
- Python 3.6: https://nvidia.box.com/v/torch-stable-cp36-jetson-jp42
- Rolling weekly binaries:
- - Python 2.7: https://nvidia.box.com/v/torch-weekly-cp27-jetson-jp42
- Python 3.6: https://nvidia.box.com/v/torch-weekly-cp36-jetson-jp42
They require JetPack 4.2 and above, and @dusty-nv maintains them
@@ -167,9 +165,9 @@ If you are building for NVIDIA's Jetson platforms (Jetson Nano, TX1, TX2, AGX Xa
#### Install Dependencies
-Common (only install `typing` for Python <3.5)
+Common
```
-conda install numpy ninja pyyaml mkl mkl-include setuptools cmake cffi typing
+conda install numpy ninja pyyaml mkl mkl-include setuptools cmake cffi
```
On Linux
@@ -234,9 +232,6 @@ CUDA and MSVC have strong version dependencies, so even if you use VS 2017 / 201
```cmd
cmd
-:: [Optional] Only add the next two lines if you need Python 2.7. If you use Python 3, ignore these two lines.
-set MSSdk=1
-set FORCE_PY27_BUILD=1
:: [Optional] If you want to build with VS 2019 generator, please change the value in the next line to `Visual Studio 16 2019`.
:: Note: This value is useless if Ninja is detected. However, you can force that by using `set USE_NINJA=OFF`.
@@ -246,7 +241,6 @@ set CMAKE_GENERATOR=Visual Studio 15 2017
:: [Optional] If you want to override the underlying toolset used by Ninja and Visual Studio with CUDA, please run the following script block.
:: "Visual Studio 2017 Developer Command Prompt" will be run automatically.
:: Make sure you have CMake >= 3.12 before you do this when you use the Visual Studio generator.
-:: It's an essential step if you use Python 3.5.
set CMAKE_GENERATOR_TOOLSET_VERSION=14.11
set DISTUTILS_USE_SDK=1
for /f "usebackq tokens=*" %i in (`"%ProgramFiles(x86)%\Microsoft Visual Studio\Installer\vswhere.exe" -version [15^,16^) -products * -latest -property installationPath`) do call "%i\VC\Auxiliary\Build\vcvarsall.bat" x64 -vcvars_ver=%CMAKE_GENERATOR_TOOLSET_VERSION%
diff --git a/docs/source/distributed.rst b/docs/source/distributed.rst
index f583dbc0867..f75c43af85e 100644
--- a/docs/source/distributed.rst
+++ b/docs/source/distributed.rst
@@ -433,8 +433,7 @@ Launch utility
The `torch.distributed` package also provides a launch utility in
`torch.distributed.launch`. This helper utility can be used to launch
-multiple processes per node for distributed training. This utility also supports
-both python2 and python3.
+multiple processes per node for distributed training.
.. automodule:: torch.distributed.launch
diff --git a/requirements.txt b/requirements.txt
index f8388b06748..7ca7b433aeb 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -4,4 +4,3 @@ pyyaml
requests
setuptools
six
-typing
\ No newline at end of file