Add meta tag to torch_export_aoti_python

conf.py

@@ -67,6 +67,12 @@
 #
 # needs_sphinx = '1.0'
 
+html_meta = {
+    'description': 'Master PyTorch with our step-by-step tutorials for all skill levels. Start your journey to becoming a PyTorch expert today!',
+    'keywords': 'PyTorch, tutorials, Getting Started, deep learning, AI',
+    'author': 'PyTorch Contributors'
+}
+
 # Add any Sphinx extension module names here, as strings. They can be
 # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
 # ones.

index.rst

@@ -3,6 +3,7 @@ Welcome to PyTorch Tutorials
 
 **What's new in PyTorch tutorials?**
 
+* `torch.export AOTInductor Tutorial for Python runtime (Beta) <https://pytorch.org/tutorials/recipes/torch_export_aoti_python.html>`__
 * `A guide on good usage of non_blocking and pin_memory() in PyTorch <https://pytorch.org/tutorials/intermediate/pinmem_nonblock.html>`__
 * `Introduction to Distributed Pipeline Parallelism <https://pytorch.org/tutorials/intermediate/pipelining_tutorial.html>`__
 * `Introduction to Libuv TCPStore Backend <https://pytorch.org/tutorials/intermediate/TCPStore_libuv_backend.html>`__ 

recipes_source/torch_export_aoti_python.py

@@ -1,7 +1,11 @@
 # -*- coding: utf-8 -*-
 
 """
-(Beta) ``torch.export`` AOTInductor Tutorial for Python runtime
+.. meta::
+   :description: An end-to-end example of how to use AOTInductor for Python runtime.
+   :keywords: torch.export, AOTInductor, torch._inductor.aot_compile, torch._export.aot_load
+
+``torch.export`` AOTInductor Tutorial for Python runtime (Beta)
 ===============================================================
 **Author:** Ankith Gunapal, Bin Bao, Angela Yi
 """
@@ -18,7 +22,7 @@
 # a shared library that can be run in a non-Python environment.
 #
 #
-# In this tutorial, you will learn an end-to-end example of how to use AOTInductor for python runtime.
+# In this tutorial, you will learn an end-to-end example of how to use AOTInductor for Python runtime.
 # We will look at how  to use :func:`torch._inductor.aot_compile` along with :func:`torch.export.export` to generate a 
 # shared library. Additionally, we will examine how to execute the shared library in Python runtime using :func:`torch._export.aot_load`.
 # You will learn about the speed up seen in the first inference time using AOTInductor, especially when using