cs501r_f2018:lab7
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| For this lab, you will modify the | For this lab, you will modify the | ||
| - | [[https://github.com/harvardnlp/annotated-transformer/blob/master/The%20Annotated%20Transformer.ipynb|Annotated Transformer]]. There is link to a coloab notebook in the jupyter notebook that you can use. The code is slightly different between the notebook linked above, and the colab link provided by Harvard. Both will work, you may very likely need to mix and match pieces from each to get a working implementation. While this may feel slightly frustrating, it is good practice for deep learning research strategies. | + | [[https://github.com/harvardnlp/annotated-transformer/blob/master/The%20Annotated%20Transformer.ipynb|Annotated Transformer]]. |
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| + | **There is a link to a coloab notebook in the jupyter notebook that you can use.** | ||
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| + | The code is slightly different between the notebook linked above, and the colab link provided by Harvard. Both will work, you may very likely need to mix and match pieces from each to get a working implementation. While this may feel slightly frustrating, it is good practice for deep learning research strategies. | ||
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| + | If you are experiencing difficulties, you may need to install specific versions of the necessary packages. One student contributed this: | ||
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| + | <code python> | ||
| + | !pip install http://download.pytorch.org/whl/cu80/torch-0.3.0.post4-cp36-cp36m-linux_x86_64.whl numpy matplotlib spacy torchtext==0.2.3 seaborn | ||
| + | </code> | ||
| Often when implementing a novel deep learning method, you will start by using someone's implementation as a reference. This is an extremely valuable, and potentially time-saving skill, for producing workable solutions to many problems solved by deep learning methods. | Often when implementing a novel deep learning method, you will start by using someone's implementation as a reference. This is an extremely valuable, and potentially time-saving skill, for producing workable solutions to many problems solved by deep learning methods. | ||
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| You should expect to see reasonable results after 2-4 hours of training in colab. | You should expect to see reasonable results after 2-4 hours of training in colab. | ||
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| + | [[http://mlexplained.com/2018/02/08/a-comprehensive-tutorial-to-torchtext/|Here is a good tutorial on torchtext.]] | ||
cs501r_f2018/lab7.1539631117.txt.gz · Last modified: 2021/06/30 23:40 (external edit)
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