CoCalc Logo Icon
StoreFeaturesDocsShareSupportNewsAboutSign UpSign In
pytorch

CoCalc provides the best real-time collaborative environment for Jupyter Notebooks, LaTeX documents, and SageMath, scalable from individual users to large groups and classes!

GitHub Repository: pytorch/tutorials
 Path: blob/main/beginner_source/template_tutorial.py
Views: 494
1
# -*- coding: utf-8 -*-

2


3
"""

4
Template Tutorial

5
=================

6


7
**Author:** `FirstName LastName <https://github.com/username>`_

8


9
.. grid:: 2

10


11
    .. grid-item-card:: :octicon:`mortar-board;1em;` What you will learn

12
       :class-card: card-prerequisites

13


14
       * Item 1

15
       * Item 2

16
       * Item 3

17


18
    .. grid-item-card:: :octicon:`list-unordered;1em;` Prerequisites

19
       :class-card: card-prerequisites

20


21
       * PyTorch v2.0.0

22
       * GPU ???

23
       * Other items 3

24


25
If you have a video, add it here like this:

26


27
.. raw:: html

28


29
   <div style="margin-top:10px; margin-bottom:10px;">

30
     <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>

31
   </div>

32


33
To test your tutorial locally, you can do one of the following:

34


35
*  You can control specific files that generate the results by using

36
   ``GALLERY_PATTERN`` environment variable. The GALLERY_PATTERN variable

37
   respects regular expressions.

38
   For example to run only ``neural_style_transfer_tutorial.py``,

39
   use the following command:

40


41
   .. code-block:: sh

42


43
      GALLERY_PATTERN="neural_style_transfer_tutorial.py" make html

44


45
   or

46


47
   .. code-block:: sh

48


49
      GALLERY_PATTERN="neural_style_transfer_tutorial.py" sphinx-build . _build

50


51
* Make a copy of this repository and add only your

52
  tutorial to the `beginner_source` directory removing all other tutorials.

53
  Then run ``make html``.

54
  

55
Verify that all outputs were generated correctly in the created HTML.

56
"""

57


58
#########################################################################

59
# Overview

60
# --------

61
#

62
# Describe Why is this topic important? Add Links to relevant research papers.

63
#

64
# This tutorial walks you through the process of....

65
#

66
# Steps

67
# -----

68
#

69
# Example code (the output below is generated automatically):

70
# 

71
import torch

72
x = torch.rand(5, 3)

73
print(x)

74


75
######################################################################

76
# (Optional) Additional Exercises

77
# -------------------------------

78
#

79
# Add additional practice exercises for users to test their knowledge.

80
# Example: `NLP from Scratch <https://pytorch.org/tutorials/intermediate/char_rnn_generation_tutorial.html#exercises>`__.

81
#

82


83
######################################################################

84
# Conclusion

85
# ----------

86
# 

87
# Summarize the steps and concepts covered. Highlight key takeaways.

88
#

89
# Further Reading

90
# ---------------

91
#

92
# * Link1

93
# * Link2

94


95


96