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# System prepended metadata

title: CS444 - Assignment 3

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# CS444 - Assignment 3

Due: November 17, 11:59pm

## Instructions
### 1. Open the assignment in Google Colab

[neural_machine_translation.ipynb](https://colab.research.google.com/drive/12YVMmfh0NgN28SavFlXtDNQ3w5S7u2gG?usp=sharing)

Please _do not_ share this link.

### 2. Save a copy to your Google Drive

In Google Colab, click "File" -> "Save a Copy in Drive". This will save a copy of the notebook to your account. By default the name will start with "Copy of ...". Rename the notebook to be the same as the original (in this case, "neural_machine_translation.ipynb").

### 3. Work on the assignment

Make sure you are working with your copy of the assignment. You can save your work ("File" -> "Save") and come back to it at a later time.

Colab collapses the cells by default so please make sure to expand the cells to make sure you do not miss any sections. You can expand all cells with "View" -> "Expand sections".

As indicated in the notebook, there are TODO blocks in the assignment that you will need to modify. **Do not edit any code outside of these blocks.** You may add cells for scratch work as you work through the assignment, but **please make sure to delete any extra cells before submitting.**

For this assignment, we will leverage GPUs for faster training. Please make sure to enable GPUs in Colab (Edit -> Notebook Settings).

**Make sure to run all cells before submitting**. You will only get credit for code that has been run.

This assignment has a bit less guidance than the previous ones so if anything is unclear, please let us know as soon as possible. If you have questions or need clarifications, please email the TA (yifu.wu@rutgers.edu).

### 4. Download the ipynb files

Once you are finished with the notebooks, click "File" -> "Download .ipynb" to download your notebook.

**Make sure your downloaded files has the same name as the original notebook.**

### 5. Submit your notebook on Canvas

Upload your neural_machine_translation.ipynb file to Canvas.

