Issues for Beginners/Students

kaad01: <p>Hi, I am a Computer Science Student, and my study partner and I would like to contribute to PyTorch. What would be a good issue for beginners?<br>
Our machine learning knowledge is very solid, but our goal is to submit a pull request which gets accepted in the next two weeks or so. So an easier Issue would be more fitting for now.</p>
<p>Thank you!</p>

ptrblck: <p>Hi Kaan!</p>
<p>I think you and your study partner could take a look at the <a href="https://github.com/pytorch/pytorch/labels/good%20first%20issue">“good first issue”</a> section in GitHub and maybe you can find something interesting there.<br>
For a general guide to contribute to PyTorch, check:</p>
<ul>
<li>the <a href="https://pytorch.org/docs/stable/community/contribution_guide.html">Contribution Guide</a>
</li>
<li>these <a href="https://github.com/pytorch/pytorch/blob/master/CONTRIBUTING.md">Contributing docs</a>
</li>
<li>and <a href="https://lernapparat.de/fixing-your-first-pytorch-bug">this video/blog</a> showing how to “fix your first PyTorch bug” by <a class="mention" href="/u/tom">@tom</a>
</li>
</ul>
<p>EDIT: it might also be interesting to take a look at <a href="https://dev-discuss.pytorch.org/t/tracing-with-primitives-update-2/645">this “tracing with primitives” update</a> from ~1h ago, which is also open for contributions, so let me know if anything would fit your interest. <img src="https://discuss.pytorch.org/images/emoji/apple/slight_smile.png?v=12" title=":slight_smile:" class="emoji" alt=":slight_smile:" loading="lazy" width="20" height="20"></p>

kaad01: <p>Thank you very much, we will look into it. <img src="https://discuss.pytorch.org/images/emoji/apple/slight_smile.png?v=12" title=":slight_smile:" class="emoji" alt=":slight_smile:" loading="lazy" width="20" height="20"></p>

kaad01: <p>Hey,<br>
I’m ready to start now.<br>
What do you think of this Issue:</p><aside class="onebox githubissue" data-onebox-src="https://github.com/pytorch/pytorch/issues/80770">
  <header class="source">

      <a href="https://github.com/pytorch/pytorch/issues/80770" target="_blank" rel="noopener nofollow ugc">github.com/pytorch/pytorch</a>
  </header>

  <article class="onebox-body">
    <div class="github-row">
  <div class="github-icon-container" title="Issue">
	  <svg width="60" height="60" class="github-icon" viewbox="0 0 14 16" aria-hidden="true"><path d="M7 2.3c3.14 0 5.7 2.56 5.7 5.7s-2.56 5.7-5.7 5.7A5.71 5.71 0 0 1 1.3 8c0-3.14 2.56-5.7 5.7-5.7zM7 1C3.14 1 0 4.14 0 8s3.14 7 7 7 7-3.14 7-7-3.14-7-7-7zm1 3H6v5h2V4zm0 6H6v2h2v-2z"></path></svg>
  </div>

  <div class="github-info-container">
    <h4>
      <a href="https://github.com/pytorch/pytorch/issues/80770" target="_blank" rel="noopener nofollow ugc">`xlogy` returns wrong gradient when `input` is 0</a>
    </h4>

    <div class="github-info">
      <div class="date">
        opened <span class="discourse-local-date" data-format="ll" data-date="2022-07-01" data-time="13:12:04" data-timezone="UTC">01:12PM - 01 Jul 22 UTC</span>
      </div>


      <div class="user">
        <a href="https://github.com/upupyy" target="_blank" rel="noopener nofollow ugc">
          <img alt="upupyy" src="https://avatars.githubusercontent.com/u/103586022?v=4" class="onebox-avatar-inline" width="20" height="20">
          upupyy
        </a>
      </div>
    </div>

    <div class="labels">
    </div>
  </div>
</div>

  <div class="github-row">
    <p class="github-body-container">### 🐛 Describe the bug

`xlogy` returns wrong gradient when `input` is 0. Since <span class="show-more-container"><a href="" rel="noopener" class="show-more">…</a></span><span class="excerpt hidden">it is continuous and differential at the point 0, it shouldn't return 0 as the gradient.

```py
import torch

def fn(input):
    fn_res = input.xlogy(2)
    return fn_res

input = torch.tensor([[0., 0., 0., 0.]], dtype=torch.float64, requires_grad=True)
torch.autograd.gradcheck(fn, (input))
```

```
torch.autograd.gradcheck.GradcheckError: Jacobian mismatch for output 0 with respect to input 0,
numerical:tensor([[0.6931, 0.0000, 0.0000, 0.0000],
        [0.0000, 0.6931, 0.0000, 0.0000],
        [0.0000, 0.0000, 0.6931, 0.0000],
        [0.0000, 0.0000, 0.0000, 0.6931]], dtype=torch.float64)
analytical:tensor([[0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.]], dtype=torch.float64)
```

### Versions

pytorch: 1.11.0</span></p>
  </div>

  </article>

  <div class="onebox-metadata">
    
    
  </div>

  <div style="clear: both"></div>
</aside>

<p>And how do you find the right File to look at? For example, in this issue, I have to look into the xlogy function. But where do find it?</p>
<p>Thank you for your help <img src="https://discuss.pytorch.org/images/emoji/apple/slight_smile.png?v=12" title=":slight_smile:" class="emoji" alt=":slight_smile:" loading="lazy" width="20" height="20"></p>

ptrblck: <p>Yes, it might be a good task. I’ve added the links to the GitHub issue.</p>

oke-aditya: <p>Hi! Not sure if this issue is specific to PyTorch<br>
Torchvision too has beginner friendly issues <a href="https://github.com/pytorch/vision/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22" class="inline-onebox" rel="noopener nofollow ugc">Issues · pytorch/vision · GitHub</a></p>
<p>Or Some issues for bit intermediate users like <a href="https://github.com/pytorch/vision/issues/5410" class="inline-onebox" rel="noopener nofollow ugc">[RFC] Batteries Included - Phase 2 · Issue #5410 · pytorch/vision · GitHub</a></p>