Automated tutorials push

Author: pytorchbot

_downloads/4355e2cef7d17548f1e25f97a62828c4/template_tutorial.ipynb

@@ -0,0 +1,75 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "# For tips on running notebooks in Google Colab, see\n# https://pytorch.org/tutorials/beginner/colab\n%matplotlib inline"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Template Tutorial\n\n**Author:** [FirstName LastName](https://github.com/username)\n\n.. grid:: 2\n\n   .. grid-item-card:: :octicon:`mortar-board;1em;` What you will learn\n\n      * Item 1\n      * Item 2\n      * Item 3\n\n   .. grid-item-card:: :octicon:`list-unordered;1em;` Prerequisites\n\n      * PyTorch v2.0.0\n      * GPU ???\n      * Other items 3\n\nIf you have a video, add it here like this:\n\n.. raw:: html\n\n   <div style=\"margin-top:10px; margin-bottom:10px;\">\n     <iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/IC0_FRiX-sw\" frameborder=\"0\" allow=\"accelerometer; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen></iframe>\n   </div>\n\nTo test your tutorial locally, you can do one of the following:\n\n*  You can control specific files that generate the results by using\n   ``GALLERY_PATTERN`` environment variable. The GALLERY_PATTERN variable\n   respects regular expressions.\n   For example to run only ``neural_style_transfer_tutorial.py``,\n   use the following command:\n   \n```sh\nGALLERY_PATTERN=\"neural_style_transfer_tutorial.py\" make html\n```\n   or\n   \n```sh\nGALLERY_PATTERN=\"neural_style_transfer_tutorial.py\" sphinx-build . _build\n```\n* Make a copy of this repo and add only your\n  tutorial to the `beginner_source` directory removing all other tutorials.\n  Then run ``make html``.\n  \nVerify that all outputs were generated correctly in the created HTML.\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Overview\n\nDescribe Why is this topic important? Add Links to relevant research papers.\n\nThis tutorial walks you through the process of....\n\n## Steps\n\nExample code (the output below is generated automatically):\n\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import torch\nx = torch.rand(5, 3)\nprint(x)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## (Optional) Additional Exercises\n\nAdd additional practice exercises for users to test their knowledge.\nExample: [NLP from Scratch](https://pytorch.org/tutorials/intermediate/char_rnn_generation_tutorial.html#exercises)_.\n\n\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Conclusion\n\nSummarize the steps and concepts covered. Highlight key takeaways.\n\n## Further Reading\n\n* Link1\n* Link2\n\n"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.10.9"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

_downloads/822c69800d15c38ee5556b071c0d1eda/template_tutorial.py

@@ -0,0 +1,92 @@
+# -*- coding: utf-8 -*-
+
+"""
+Template Tutorial
+=================
+
+**Author:** `FirstName LastName <https://github.com/username>`_
+
+.. grid:: 2
+
+   .. grid-item-card:: :octicon:`mortar-board;1em;` What you will learn
+
+      * Item 1
+      * Item 2
+      * Item 3
+
+   .. grid-item-card:: :octicon:`list-unordered;1em;` Prerequisites
+
+      * PyTorch v2.0.0
+      * GPU ???
+      * Other items 3
+
+If you have a video, add it here like this:
+
+.. raw:: html
+
+   <div style="margin-top:10px; margin-bottom:10px;">
+     <iframe width="560" height="315" src="https://www.youtube.com/embed/IC0_FRiX-sw" frameborder="0" allow="accelerometer; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
+   </div>
+
+To test your tutorial locally, you can do one of the following:
+
+*  You can control specific files that generate the results by using
+   ``GALLERY_PATTERN`` environment variable. The GALLERY_PATTERN variable
+   respects regular expressions.
+   For example to run only ``neural_style_transfer_tutorial.py``,
+   use the following command:
+   
+   .. code-block:: sh
+   
+      GALLERY_PATTERN="neural_style_transfer_tutorial.py" make html
+    
+   or
+   
+   .. code-block:: sh
+      
+      GALLERY_PATTERN="neural_style_transfer_tutorial.py" sphinx-build . _build
+  
+* Make a copy of this repo and add only your
+  tutorial to the `beginner_source` directory removing all other tutorials.
+  Then run ``make html``.
+  
+Verify that all outputs were generated correctly in the created HTML.
+"""
+
+#########################################################################
+# Overview
+# --------
+#
+# Describe Why is this topic important? Add Links to relevant research papers.
+#
+# This tutorial walks you through the process of....
+#
+# Steps
+# -----
+#
+# Example code (the output below is generated automatically):
+# 
+import torch
+x = torch.rand(5, 3)
+print(x)
+
+######################################################################
+# (Optional) Additional Exercises
+# -------------------------------
+#
+# Add additional practice exercises for users to test their knowledge.
+# Example: `NLP from Scratch <https://pytorch.org/tutorials/intermediate/char_rnn_generation_tutorial.html#exercises>`__.
+#
+
+######################################################################
+# Conclusion
+# ----------
+# 
+# Summarize the steps and concepts covered. Highlight key takeaways.
+#
+# Further Reading
+# ---------------
+#
+# * Link1
+# * Link2
+