Merge branch 'site' into credits

Author: cjyabraham

_events/pytorch-conference-2025.md

@@ -0,0 +1,13 @@
+---
+category: event
+title: "PyTorch Conference 2025"
+date: October 23, 2025
+poster: assets/images/pytorch-conf-2025.jpg
+---
+**Date**: October 22 - 23, 2025
+
+<a href="https://events.linuxfoundation.org/pytorch-conference-2025/">
+<img style="width:100%" src="/assets/images/pytorch-conf-2025.jpg" alt="PyTorch Conference banner">
+</a>
+
+Join us in San Francisco on **October 22-23, 2025** to learn about AI and PyTorch, the cutting-edge renowned open source machine learning framework. This two-day event that brings together top-tier researchers, developers, and academic communities, fostering collaboration and advancing end-to-end machine learning.

_get_started/installation/linux.md

@@ -25,7 +25,7 @@ PyTorch is supported on Linux distributions that use [glibc](https://www.gnu.org
 ### Python
 {: #linux-python}
 
-Python 3.8-3.11 is generally installed by default on any of our supported Linux distributions, which meets our recommendation.
+Python 3.9-3.12 is generally installed by default on any of our supported Linux distributions, which meets our recommendation.
 
 > Tip: By default, you will have to use the command `python3` to run Python. If you want to use just the command `python`, instead of `python3`, you can symlink `python` to the `python3` binary.
 

_get_started/installation/mac.md

@@ -13,29 +13,19 @@ PyTorch is supported on macOS 10.15 (Catalina) or above.
 ### Python
 {: #mac-python}
 
-It is recommended that you use Python 3.8 - 3.11.
+It is recommended that you use Python 3.9 - 3.12.
 You can install Python either through the Anaconda
 package manager (see [below](#anaconda)), [Homebrew](https://brew.sh/), or
 the [Python website](https://www.python.org/downloads/mac-osx/).
 
-In one of the upcoming PyTorch releases, support for Python 3.8 will be deprecated.
-
 ### Package Manager
 {: #mac-package-manager}
 
-To install the PyTorch binaries, you will need to use one of two supported package managers: [Anaconda](https://www.anaconda.com/download/#macos) or [pip](https://pypi.org/project/pip/). Anaconda is the recommended package manager as it will provide you all of the PyTorch dependencies in one, sandboxed install, including Python.
-
+To install the PyTorch binaries, you will need to use one of two supported package managers: [pip](https://pypi.org/project/pip/) or [Anaconda](https://www.anaconda.com/download/#macos). 
 #### Anaconda
 
-To install Anaconda, you can [download graphical installer](https://www.anaconda.com/download/#macos) or use the command-line installer. If you use the command-line installer, you can right-click on the installer link, select `Copy Link Address`, or use the following commands on Intel Mac:
+To install Anaconda, you can [download graphical installer](https://www.anaconda.com/download/#macos) or use the command-line installer. If you use the command-line installer, you can right-click on the installer link, select `Copy Link Address`, or use the following commands on Mac computer with Apple silicon:
 
-```bash
-# The version of Anaconda may be different depending on when you are installing`
-curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
-sh Miniconda3-latest-MacOSX-x86_64.sh
-# and follow the prompts. The defaults are generally good.`
-```
-or following commands on M1 Mac:
 ```bash
 # The version of Anaconda may be different depending on when you are installing`
 curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh

_get_started/installation/windows.md

@@ -18,7 +18,7 @@ PyTorch is supported on the following Windows distributions:
 ### Python
 {: #windows-python}
 
-Currently, PyTorch on Windows only supports Python 3.8-3.11; Python 2.x is not supported.
+Currently, PyTorch on Windows only supports Python 3.9-3.12; Python 2.x is not supported.
 
 As it is not installed by default on Windows, there are multiple ways to install Python:
 

_get_started/previous-versions.md

@@ -17,6 +17,43 @@ your convenience.
 
 ## Commands for Versions >= 1.0.0
 
+### v2.4.1
+#### Conda
+##### OSX
+```
+# conda
+conda install pytorch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 -c pytorch
+```
+#####  Linux and Windows
+```
+# CUDA 11.8
+conda install pytorch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1  pytorch-cuda=11.8 -c pytorch -c nvidia
+# CUDA 12.1
+conda install pytorch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 pytorch-cuda=12.1 -c pytorch -c nvidia
+# CUDA 12.4
+conda install pytorch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 pytorch-cuda=12.4 -c pytorch -c nvidia
+# CPU Only
+conda install pytorch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 cpuonly -c pytorch
+```
+#### Wheel
+##### OSX
+```
+pip install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1
+```
+##### Linux and Windows
+```
+# ROCM 6.1 (Linux only)
+pip install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/rocm6.1
+# CUDA 11.8
+pip install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/cu118
+# CUDA 12.1
+pip install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/cu121
+# CUDA 12.4
+pip install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/cu124
+# CPU only
+pip install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/cpu
+```
+
 ### v2.4.0
 
 #### Conda

_get_started/pytorch.md

@@ -1,6 +1,6 @@
 ---
 layout: get_started
-title: PyTorch 2.0
+title: PyTorch 2.x
 permalink: /get-started/pytorch-2.0/
 featured-img: "assets/images/featured-img-pytorch-2.png"
 background-class: get-started-background

_includes/main_menu.html

@@ -52,8 +52,8 @@
             <span class=dropdown-title>Developer Resources</span>
             <p>Find resources and get questions answered</p>
           </a>
-          <a class="nav-dropdown-item" href="{{ site.baseurl}}/ecosystem/contributor-awards-2023">
-            <span class="dropdown-title">Contributor Awards - 2023</span>
+          <a class="nav-dropdown-item" href="{{ site.baseurl}}/ecosystem/contributor-awards-2024">
+            <span class="dropdown-title">Contributor Awards - 2024</span>
             <p>Award winners announced at this year's PyTorch Conference</p>
           </a>
         </div>
@@ -141,6 +141,11 @@
           </a>
           <a class="nav-dropdown-item" href="{{ site.baseurl }}/credits">
             <span class=dropdown-title>Cloud Credit Program</span>
+          <a class="nav-dropdown-item" href="{{ site.baseurl }}/tac">
+            <span class=dropdown-title>Technical Advisory Council</span>
+          </a>
+          <a class="nav-dropdown-item" href="{{ site.baseurl }}/staff">
+            <span class=dropdown-title>Staff</span>
           </a>
           <a class="nav-dropdown-item" href="{{ site.baseurl }}/contact-us">
             <span class=dropdown-title>Contact Us</span>

_includes/mobile_menu.html

@@ -60,7 +60,7 @@
             <a href="{{ site.baseurl }}/resources">Developer Resources</a>
           </li>
           <li>
-            <a href="{{ site.baseurl}}/ecosystem/contributor-awards-2023">Contributor Awards - 2023</a>
+            <a href="{{ site.baseurl}}/ecosystem/contributor-awards-2024">Contributor Awards - 2024</a>
           </li>
         </ul>
         <li class="resources-mobile-menu-title">
@@ -119,6 +119,12 @@
           <li>
             <a href="{{ site.baseurl }}/credits">Cloud Credit Program</a>
           </li>
+          <li>          
+            <a href="{{ site.baseurl }}/tac">Technical Advisory Council</a>
+          </li>
+          <li>
+            <a href="{{ site.baseurl }}/staff">Staff</a>
+          </li>
           <li>
             <a href="{{ site.baseurl }}/contact-us">Contact Us</a>
           </li>

_includes/quick_start_local.html

@@ -5,7 +5,7 @@
   <a href="{{ site.baseurl }}/get-started/previous-versions">install previous versions of PyTorch</a>. Note that LibTorch is only available for C++.
 </p>
 
-<p><b>NOTE:</b> Latest PyTorch requires Python 3.8 or later.</p>
+<p><b>NOTE:</b> Latest PyTorch requires Python 3.9 or later.</p>
 
 <div class="row">
   <div class="col-md-3 headings">

_posts/2021-6-8-overview-of-pytorch-autograd-engine.md

@@ -37,7 +37,7 @@ In the example above, when multiplying x and y to obtain v, the engine will exte
   <p>Figure 2: Computational graph extended after executing the logarithm</p>
 </div>
 
-Continuing, the engine now calculates the <a href="https://www.codecogs.com/eqnedit.php?latex=log(v)" target="_blank"><img src="https://latex.codecogs.com/gif.latex?log(v)" title="log(v)" /></a> operation and extends the graph again with the log derivative that it knows to be <a href="https://www.codecogs.com/eqnedit.php?latex=\frac{1}{v}" target="_blank"><img src="https://latex.codecogs.com/gif.latex?\frac{1}{v}" title="\frac{1}{v}" /></a>. This is shown in figure 3. This operation generates the result <a href="https://www.codecogs.com/eqnedit.php?latex=\frac{\partial&space;w}{\partial&space;v}" target="_blank"><img src="https://latex.codecogs.com/gif.latex?\frac{\partial&space;w}{\partial&space;v}" title="\frac{\partial w}{\partial v}" /></a> that when propagated backward and multiplied by the multiplication derivative as in the chain rule, generates the derivatives <a href="https://www.codecogs.com/eqnedit.php?latex=\frac{\partial&space;w}{\partial&space;x}" target="_blank"><img src="https://latex.codecogs.com/gif.latex?\frac{\partial&space;w}{\partial&space;x}" title="\frac{\partial w}{\partial x}" /></a>, <a href="https://www.codecogs.com/eqnedit.php?latex=\frac{\partial&space;w}{\partial&space;x}" target="_blank"><img src="https://latex.codecogs.com/gif.latex?\frac{\partial&space;w}{\partial&space;x}" title="\frac{\partial w}{\partial x}" /></a>.
+Continuing, the engine now calculates the <a href="https://www.codecogs.com/eqnedit.php?latex=log(v)" target="_blank"><img src="https://latex.codecogs.com/gif.latex?log(v)" title="log(v)" /></a> operation and extends the graph again with the log derivative that it knows to be <a href="https://www.codecogs.com/eqnedit.php?latex=\frac{1}{v}" target="_blank"><img src="https://latex.codecogs.com/gif.latex?\frac{1}{v}" title="\frac{1}{v}" /></a>. This is shown in figure 3. This operation generates the result <a href="https://www.codecogs.com/eqnedit.php?latex=\frac{\partial&space;w}{\partial&space;v}" target="_blank"><img src="https://latex.codecogs.com/gif.latex?\frac{\partial&space;w}{\partial&space;v}" title="\frac{\partial w}{\partial v}" /></a> that when propagated backward and multiplied by the multiplication derivative as in the chain rule, generates the derivatives <a href="https://www.codecogs.com/eqnedit.php?latex=\frac{\partial&space;w}{\partial&space;x}" target="_blank"><img src="https://latex.codecogs.com/gif.latex?\frac{\partial&space;w}{\partial&space;x}" title="\frac{\partial w}{\partial x}" /></a>, <a href="https://www.codecogs.com/eqnedit.php?latex=\frac{\partial&space;w}{\partial&space;y}" target="_blank"><img src="https://latex.codecogs.com/gif.latex?\frac{\partial&space;w}{\partial&space;y}" title="\frac{\partial w}{\partial y}" /></a>.
 
 <div class="text-center">
   <img src="{{ site.baseurl }}/assets/images/extended_computational_graph.png" width="100%">
@@ -111,7 +111,7 @@ We can execute the same expression in PyTorch and calculate the gradient of the
   <pre>>>> y.backward(1.0)</pre>
   <pre>>>> x.grad</pre>
   tensor([1.3633,
-          0.1912])</pre>
+          0.1912])
 </div>
 
 The result is the same as our hand-calculated Jacobian-vector product!