You can get started using the same steps you followed for PA1-4. To recap, you'll want to:
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Open a terminal (terminal for macOS and Linux, Ubuntu for Windows for Windows, or SSH into Rice/Myth) the same way you did for PA0-4.
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Clone the git repository for PA5 (this repository) into a folder of your choice by typing this in your terminal:
git clone https://github.com/cs124/pa5-neural-networks.git -
Enter the project root directory:
cd pa5-neural-networks -
Activate your environment. Run:
conda activate cs124You'll need to activate your environment every time you open a new terminal and re-start your notebook server.
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Start up your jupyter notebook server
jupyter notebook -
A window should open automatically in your default browser. If it didn't, the terminal output should contain a URL you can use to open the notebook in a browser of your choice.
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From the Jupyter notebook file explorer window that opens, click on the pa5.ipynb file to open and edit it.
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Go to colab.research.google.com. If prompted to open a notebook, hit cancel for now. You should double-check that you are logged in to your Stanford Google account. If not, you can switch accounts in the top right.
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Now go to File->Open Notebook. Go to the GitHub tab. It will ask you to log in to your GitHub account (if you don't have one it is easy to make one). Once you've done that, copy and paste the URL: https://github.com/cs124/pa5-neural-networks into the search box and hit enter. It should show:
Repository: cs124/pa5-neural-networks Branch: MainClick on pa5.ipynb below to load the notebook.
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You can run the submission cell in the Jupyter notebook to zip up your solution for you. It should generate a zip file
submission.zip. -
Upload the zip file as your solution to the PA5 Neural Networks assignment in Gradescope (http://www.gradescope.com).
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You can run the cell at the bottom of the Jupyter notebook to zip up your solution for you. It should generate a zip file
submission.zip. -
Run the following command to transfer that zip file over from WSL to your local computer:
cp ~/cs124/pa5-neural-networks/submission.zip /mnt/c/Users/YOUR_USER_NAME/OneDrive/Desktop/
Note that you may want to replace OneDrive/Desktop/ with another destination folder based on your preferences.
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Upload the zip file as your solution to the PA5 Neural NEtworks assignment in Gradescope (http://www.gradescope.com).
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You can run the cell at the bottom of the Jupyter notebook to zip up your solution for you. It should generate a zip file
submission.zip. -
You will then need to download/copy the zip file from Rice/Myth to your local machine.
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[macOS/Linux/Ubuntu for Windows]
After you have created the submission zip, cd into a local folder where you'd like to copy the submission zip from Myth, and use the following command to copy the zip from Myth to your local machine:
scp -r [SUNet]@[rice/myth].stanford.edu:/path-to-your-pa5-folder/submission.zip .You can replace . with a relative path to a local directory you'd like to copy the zip file to.
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[Windows] PSCP is another utility that should have been installed automatically when you installed PuTTY earlier. Find and run it. In the terminal window, you can run the command:
pscp [Your SUNet]@rice.stanford.edu:/path/to/submission.zip c:\temp\submission.zip
to download the file from Rice/Myth to your local machine. You should now be able to access the file locally at c:\temp\submission.zip
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Upload the zip file as your solution to the PA5 Neural Networks assignment in Gradescope (http://www.gradescope.com).
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Once you've saved all your changes, go to File->Download .ipynb to download your notebook file to your local machine.
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If your solution required any extra files, make sure they were located in pa5-neural-networks/deps. Go to the file explorer on the left-hand side and download those as well.
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Once you have pa5.ipynb and any deps files you need saved locally, create a zip file (either from your OS's file explorer or the terminal), making sure that it has the following structure:
deps/ pa5.ipynb -
Upload the zip file as your solution to the PA5 Neural Networks assignment in Gradescope (http://www.gradescope.com).