Main > Live 2 (#2067)

* Final editorial review update (#2063)

Fix oobe delete user path
Rename best practices to recommendations
Minor writing style updates

* Fix backtick in build-custom-distro.md (#2062)

* Remove the duplicate `feedback_product_url` value (#2040)

* Update troubleshooting.md (#2034)

Azure virtual machine does support Nested Virtualization, but cannot use with Trusted Launch. Hence proposing minor correction.

* Update networking.md (#2033)

Updated that the hostname takes a lowercase -i  as the address flag.  This can be seen by running hostname --help.  also made the "under the hood" section more verbose with the full length ip-address command.

* Add the information about the --pre-release option (#2031)

* Add note for blocked Microsoft Store (#2030)

* Add note for blocked Microsoft Store

* Editorial update

---------

Co-authored-by: Matt Wojciakowski <[email protected]>

* Add rule to ignore service account's contribute (#2039)

* Update WSL shutdown instructions for clarity by specifying PowerShell should be run as administrator before executing the shutdown command. (#2028)

* Update WSL shutdown instructions for clarity by specifying PowerShell should be run as administrator before executing the shutdown command.

* Add Docker Desktop error recommendation

---------

Co-authored-by: Matt Wojciakowski <[email protected]>

* Fix warnings (#2065)

* Fix pytorch directml install command (#2066)

Resolves #2044

---------

Co-authored-by: Carlos Nihelton <[email protected]>
Co-authored-by: Caozhi Li <[email protected]>
Co-authored-by: thiruma0203 <[email protected]>
Co-authored-by: Horsevad <[email protected]>
Co-authored-by: Carlos Rafael Ramirez <[email protected]>
Co-authored-by: Chunyao Chan <[email protected]>

WSL/tutorials/gpu-compute.md

@@ -1,7 +1,7 @@
 ---
 title: GPU accelerated ML training in WSL
 description: Learn how to setup the Windows Subsystem for Linux with NVIDIA CUDA, TensorFlow-DirectML, and PyTorch-DirectML. Read about using GPU acceleration with WSL to support machine learning training scenarios.
-ms.date: 05/03/2022
+ms.date: 11/19/2024
 ms.topic: article
 ---
 
@@ -21,7 +21,7 @@ This guide will show how to set up:
 * Ensure you are running [Windows 11](https://microsoft.com/software-download/windows11) or [Windows 10, version 21H2](https://microsoft.com/software-download/windows10) or higher.
 * [Install WSL and set up a username and password for your Linux distribution](/windows/wsl/install).
 
-## Setting up NVIDIA CUDA with Docker
+## Set up NVIDIA CUDA with Docker
 
 1. [Download and install the latest driver for your NVIDIA GPU](https://www.nvidia.com/Download/index.aspx)
 2. Install [Docker Desktop](/windows/wsl/tutorials/wsl-containers#install-docker-desktop) or install the Docker engine directly in WSL by running the following command
@@ -85,7 +85,7 @@ This guide will show how to set up:
 
 Additional ways to get setup and utilize NVIDIA CUDA can be found in the [NVIDIA CUDA on WSL User Guide](https://docs.nvidia.com/cuda/wsl-user-guide/index.html#getting-started-with-cuda-on-wsl).
 
-## Setting up TensorFlow-DirectML or PyTorch-DirectML
+## Set up TensorFlow-DirectML or PyTorch-DirectML
 
 1. Download and install the latest driver from your GPU vendors website: [AMD](https://www.amd.com/en/support), [Intel](https://www.intel.com/content/www/us/en/download/19344/intel-graphics-windows-dch-drivers.html), or [NVIDIA](https://www.nvidia.com/Download/index.aspx).
 
@@ -124,7 +124,7 @@ Additional ways to get setup and utilize NVIDIA CUDA can be found in the [NVIDIA
     ```
 
     ```bash
-    pip install pytorch-directml
+    pip install torch-directml
     ```
 
 4. Run a quick addition sample in an interactive Python session for [TensorFlow-DirectML](/windows/ai/directml/gpu-tensorflow-wsl#install-the-tensorflow-with-directml-package) or [PyTorch-DirectML](/windows/ai/directml/gpu-pytorch-wsl#install-the-pytorch-with-directml-package) to make sure everything is working.