From c20db06a5fbd5d366ce43f1f9d8aae724ef6e640 Mon Sep 17 00:00:00 2001 From: eshetty <107862033+eshetty@users.noreply.github.com> Date: Fri, 2 Feb 2024 10:53:02 -0500 Subject: [PATCH 1/2] Update lab03 - Pull Request Warning --- labs/lab03.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/labs/lab03.md b/labs/lab03.md index 2846b366..242a3ecf 100644 --- a/labs/lab03.md +++ b/labs/lab03.md @@ -42,6 +42,8 @@ git checkout ## Exercise 3: Create and approve a pull request +**Note: Please ensure you create the pull request to the main branch of your forked repository. Under no circumstances should you create a pull request to the original PyTorch repository.** + 1. Create a new branch called `pull-request` from `main` branch. 2. In the `torch/nn/functional.py` file, navigate to the `l1_loss` function (line 3308) and add code to check if the reduction mode is `sum` and raise an exception: 3. Commit the changes to the `pull-request` branch. Make sure you add a meaningful commit message. From 4f53f824ec4ce5f2b0125cf48d2eb6c18b73e1b7 Mon Sep 17 00:00:00 2001 From: eshetty <107862033+eshetty@users.noreply.github.com> Date: Fri, 2 Feb 2024 11:13:18 -0500 Subject: [PATCH 2/2] Update lab03.md --- labs/lab03.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/labs/lab03.md b/labs/lab03.md index 242a3ecf..3cb483b1 100644 --- a/labs/lab03.md +++ b/labs/lab03.md @@ -42,7 +42,10 @@ git checkout ## Exercise 3: Create and approve a pull request -**Note: Please ensure you create the pull request to the main branch of your forked repository. Under no circumstances should you create a pull request to the original PyTorch repository.** +**Note: Please ensure on GitHub, you create the pull request to the main branch of your forked repository. Under no circumstances should you create a pull request to the original PyTorch repository.** +

+(make sure you choose *username*/pytorch instead of pytorch/pytorch)
+image
1. Create a new branch called `pull-request` from `main` branch. 2. In the `torch/nn/functional.py` file, navigate to the `l1_loss` function (line 3308) and add code to check if the reduction mode is `sum` and raise an exception: