Merge branch 'site' into join

Author: cjyabraham

_events/pytorch-conference-2023.md

@@ -0,0 +1,13 @@
+---
+category: event
+title: "PyTorch Conference 2023"
+date: October 16, 2023
+---
+
+**Date**: October 16 - 17, 2023
+
+The conference will showcase PyTorch 2.0, the next-generation release of the popular machine learning framework. As part of the Linux Foundation, the PyTorch Foundation Conference continues the tradition of bringing together leading researchers, developers, and academic communities to advance the education and development of end-to-end machine learning.
+
+The conference agenda features an engaging lineup of events, including an opening reception, engaging community and partner discussions, informative panels, poster sessions, enlightening use cases and community stories, as well as discussions on the latest trends in machine learning and deep learning development and deployment.
+
+[Find out more and register!](https://events.linuxfoundation.org/pytorch-conference/)

_get_started/previous-versions.md

@@ -53,9 +53,9 @@ pip install torch==2.0.0 torchvision==0.15.1 torchaudio==2.0.1
 # ROCM 5.4.2 (Linux only)
 pip install torch==2.0.0+rocm5.4.2 torchvision==0.15.1+rocm5.4.2 torchaudio==2.0.1 --index-url https://download.pytorch.org/whl/rocm5.4.2
 # CUDA 11.7
-pip install torch==2.0.0+cu117 torchvision==0.15.1+cu116 torchaudio==2.0.1 --index-url https://download.pytorch.org/whl/cu117
+pip install torch==2.0.0+cu117 torchvision==0.15.1+cu117 torchaudio==2.0.1 --index-url https://download.pytorch.org/whl/cu117
 # CUDA 11.8
-pip install torch==2.0.0+cu118 torchvision==0.15.1+cu117 torchaudio==2.0.1 --index-url https://download.pytorch.org/whl/cu118
+pip install torch==2.0.0+cu118 torchvision==0.15.1+cu118 torchaudio==2.0.1 --index-url https://download.pytorch.org/whl/cu118
 # CPU only
 pip install torch==2.0.0+cpu torchvision==0.15.1+cpu torchaudio==2.0.1 --index-url https://download.pytorch.org/whl/cpu
 ```

_posts/2023-05-16-pytorch-conference-2023.md

@@ -0,0 +1,46 @@
+---
+layout: blog_detail
+title: "PyTorch Conference 2023: Join us in San Francisco October 16-17"
+---
+
+![PyTorch Conference 2023](/assets/images/pytorch-conf-2023.png){:style="max-height:800px; width:100%"}   
+
+
+We’re thrilled to announce the upcoming [PyTorch Conference 2023](https://events.linuxfoundation.org/pytorch-conference/)! On October 16-17, the conference will showcase PyTorch 2.0, the next-generation release of the popular machine learning framework. As part of the Linux Foundation, the PyTorch Foundation Conference continues the tradition of bringing together leading researchers, developers, and academic communities to advance the education and development of end-to-end machine learning.
+
+The conference agenda features an engaging lineup of events, including an opening reception, engaging community and partner discussions, informative panels, poster sessions, enlightening use cases and community stories, as well as discussions on the latest trends in machine learning and deep learning development and deployment.
+
+## Call for Proposals
+
+We are now accepting speaker proposals for the conference until **July 21**. The program committee will carefully review all submissions, and selected speakers will be notified by **August 8**. We strongly encourage both experienced and first-time speakers to submit their proposals. This conference provides an excellent opportunity to connect with the PyTorch community, share your ideas, and showcase your work.
+
+When preparing your proposal, please consider the following guidelines:
+
+* What are you hoping to get from your presentation?
+* What do you expect the audience to gain from your presentation?
+* How will your presentation help better the open source ecosystem?
+
+To help you shape your proposal, here are some suggested topics for the conference:
+
+* Deployments on AWS, Azure
+* Use cases and real-world applications
+* Foundational models
+* AI practices
+* Production considerations
+* PyTorch 2.X features and updates
+* Training techniques and best practices
+* Inference methodologies
+* Hardware advancements and optimizations
+* Edge computing applications
+* Scalability solutions
+* Latest research breakthroughs
+* Optimization strategies
+* Extending PyTorch through customizations and plugins
+
+We kindly request that you refrain from submitting sales or marketing pitches and avoid discussing unlicensed or closed-source technologies. Such talks tend to detract from the integrity of our events and are not well-received by conference attendees.
+
+## Register Today
+
+Registration is now open! Get your ticket today and secure your spot: [https://events.linuxfoundation.org/pytorch-conference/register/](https://events.linuxfoundation.org/pytorch-conference/register/) 
+
+Thank you for your interest, and we look forward to a successful PyTorch Conference 2023!

assets/images/pytorch-conf-2023.png

@@ -236,7 +236,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.1.0a0+gitfcf2fb2 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.1.0a0+git66a2600 ) &#x25BC</a>
     </div>
 
 
@@ -310,7 +310,12 @@
 <li class="toctree-l1"><a class="reference internal" href="compile/custom-backends.html">Custom Backends</a></li>
 <li class="toctree-l1"><a class="reference internal" href="compile/deep-dive.html">TorchDynamo Deeper Dive</a></li>
 <li class="toctree-l1"><a class="reference internal" href="compile/performance-dashboard.html">PyTorch 2.0 Performance Dashboard</a></li>
+<li class="toctree-l1"><a class="reference internal" href="compile/torchfunc-and-torchcompile.html">torch.func interaction with torch.compile</a></li>
 <li class="toctree-l1"><a class="reference internal" href="ir.html">IRs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="compile/dynamic-shapes.html">Dynamic shapes</a></li>
+<li class="toctree-l1"><a class="reference internal" href="compile/fake-tensor.html">Fake tensor</a></li>
+<li class="toctree-l1"><a class="reference internal" href="logging.html">torch._logging</a></li>
+<li class="toctree-l1"><a class="reference internal" href="compile/transformations.html">Writing Graph Transformations on ATen IR</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Language Bindings</span></p>
 <ul>

docs/main/_dynamo.html

@@ -235,7 +235,7 @@
           <div class="pytorch-left-menu-search">
 
     <div class="version">
-      <a href='https://pytorch.org/docs/versions.html'>main (2.1.0a0+gitfcf2fb2 ) &#x25BC</a>
+      <a href='https://pytorch.org/docs/versions.html'>main (2.1.0a0+git66a2600 ) &#x25BC</a>
     </div>
 
 
@@ -309,7 +309,12 @@
 <li class="toctree-l1"><a class="reference internal" href="../compile/custom-backends.html">Custom Backends</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../compile/deep-dive.html">TorchDynamo Deeper Dive</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../compile/performance-dashboard.html">PyTorch 2.0 Performance Dashboard</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../compile/torchfunc-and-torchcompile.html">torch.func interaction with torch.compile</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../ir.html">IRs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../compile/dynamic-shapes.html">Dynamic shapes</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../compile/fake-tensor.html">Fake tensor</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../logging.html">torch._logging</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../compile/transformations.html">Writing Graph Transformations on ATen IR</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Language Bindings</span></p>
 <ul>