Merge branch 'main' into fix-3007

README.md

@@ -22,6 +22,8 @@ We use sphinx-gallery's [notebook styled examples](https://sphinx-gallery.github
 
 Here is how you can create a new tutorial (for a detailed description, see [CONTRIBUTING.md](./CONTRIBUTING.md)):
 
+NOTE: Before submitting a new tutorial, read [PyTorch Tutorial Submission Policy](./tutorial_submission_policy.md).
+
 1. Create a Python file. If you want it executed while inserted into documentation, save the file with the suffix `tutorial` so that the file name is `your_tutorial.py`.
 2. Put it in one of the `beginner_source`, `intermediate_source`, `advanced_source` directory based on the level of difficulty. If it is a recipe, add it to `recipes_source`. For tutorials demonstrating unstable prototype features, add to the `prototype_source`.
 3. For Tutorials (except if it is a prototype feature), include it in the `toctree` directive and create a `customcarditem` in [index.rst](./index.rst).

beginner_source/chatbot_tutorial.py

@@ -84,8 +84,7 @@
 # Preparations
 # ------------
 #
-# To start, Download the data ZIP file
-# `here <https://zissou.infosci.cornell.edu/convokit/datasets/movie-corpus/movie-corpus.zip>`__
+# To get started, `download <https://zissou.infosci.cornell.edu/convokit/datasets/movie-corpus/movie-corpus.zip>`__ the Movie-Dialogs Corpus zip file.
 
 # and put in a ``data/`` directory under the current directory.
 #

tutorial_submission_policy.md

@@ -0,0 +1,107 @@
+# PyTorch Tutorial Submission Policy
+
+This policy outlines the criteria and process for submitting new
+tutorials to the PyTorch community.
+Our goal is to ensure that all tutorials are of high quality,
+relevant, and up-to-date, supporting both the growth of the PyTorch
+users and the evolution of the PyTorch framework itself. By following
+these guidelines, contributors can help us maintain a robust and
+informative educational environment.
+
+## Acceptance Criteria For New Tutorials
+
+We accept new tutorials that adhere to one of the following use cases:
+
+* **Demonstrate New PyTorch Features:** Tutorials that support new features
+  for upcoming PyTorch releases are typically authored by the engineers who
+  are developing these features. These tutorials are crucial for showcasing
+  the latest advancements in PyTorch. We typically do not require more than
+  one tutorial per feature.
+
+* **Tutorials showcasing PyTorch usage with other tools and libraries:** We
+  accept community-contributed tutorials that illustrate innovative uses of
+  PyTorch alongside other open-source projects, models, and tools. Please
+  ensure that your tutorial remains neutral and does not promote or endorse
+  proprietary technologies over others.
+
+The first use case does not require going through the submission
+process outlined below. If your tutorial falls under the second category,
+please read and follow the instructions in the
+**Submission Process For Community-Contributed Tutorials** section.
+
+## Submission Process For Community-Contributed Tutorials
+
+To maintain the quality and relevance of tutorials, we request that
+community-contributed tutorials undergo a review process. If you are
+interested in contributing a tutorial, please follow these steps:
+
+1. **Create an issue:**
+   * Open an issue in the pytorch/tutorials repository proposing the
+     new tutorial. Clearly explain the importance of the tutorial and
+     confirm that there is no existing tutorial covering the same or
+     similar topic. A tutorial should not disproportionately endorse
+     one technology over another. Please consult with Core Maintainers
+     to ensure your content adheres to these guidelines.
+     Use the provided [ISSUE_TEMPLATE](https://github.com/pytorch/tutorials/blob/main/.github/ISSUE_TEMPLATE/feature-request.yml) for the new tutorial request - select **Feature request** when submitting an issue.
+
+     * If there is an existing tutorial on the topic that you would
+       like to significantly refactor, you can submit a PR. In the
+       description of the PR, explain why the changes are needed and
+       how they improve the tutorial.
+
+   * These issues will be triaged by PyTorch maintainers on a case-by-case basis. 
+   * Link any supporting materials including discussions in other repositories.
+
+1. **Await Approval:**
+   * Wait for a response from the PyTorch Tutorials maintainers. A PyTorch
+     tutorial maintainer will review your proposal and
+     determine whether a tutorial on the proposed topic is desirable.
+     A comment and an **approved** label will be added to your issue
+     by a maintainer. The review process for new tutorial PRs submitted
+     without the corresponding issue may take longer.
+
+1. **Adhere to writing and styling guidelines:**
+   * Once approved, follow the guidelines outlined in [CONTRIBUTING.md](https://github.com/pytorch/tutorials/blob/main/CONTRIBUTING.md)
+     and use the provided [template](https://github.com/pytorch/tutorials/blob/main/beginner_source/template_tutorial.py) for creating your tutorial.
+   * Link the issue in which you received approval for your tutorial
+     in the PR.
+   * We accept tutorials in both ``.rst`` (ReStructuredText) and ``.py``
+     (Python) formats. However, unless your tutorial involves using
+     multiple GPU, parallel/distributed training, or requires extended
+     execution time (25 minutes or more), we prefer submissions
+     in Python file format.
+
+## Maintaining Tutorials
+
+When you submit a new tutorial, we encourage you to keep it in sync
+with the latest PyTorch updates and features. Additionally, we may
+contact you to review any PRs, issues, and other related matters to
+ensure the tutorial remains a valuable resource.
+
+Please note the following: 
+
+* If a tutorial breaks against the main branch, it will
+  be excluded from the build and an issue will be filed against it,
+  with the author/maintainer notified. If the issue is not resolved
+  within 90 days, the tutorial might be deleted from the repository.
+
+* We recommend that each tutorial is reviewed at least once a year to
+  ensure its relevance.
+
+## Deleting Stale Tutorials
+
+A tutorial might be considered stale when it no longer aligns with
+the latest PyTorch updates, features, or best practices or best
+practices:
+
+* The tutorial is no longer functional due to changes in PyTorch or
+  its dependencies
+* The tutorial has been superseded by a newer, more comprehensive, or
+  more accurate tutorial
+* The tutorial does not run successfully in the (CI), indicating
+  potential compatibility or dependency issues.
+
+If a tutorial is deemed stale, we will attempt to contact the code owner,
+or someone from the tutorial mainatainers might attempt to update it.
+However, if despite those attempts we fail to fix it, the tutorial
+might be removed from the repository.