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I have a previously created jupyter notebook that I'd like to run on the Google Cloud Platform.

I currently have a notebook instance running on a GCP VM and it works fine. I was also able to create a storage bucket and upload all dataset and notebook files to the bucket. However, these files don't show up in the Jupyter Notebook directory tree. I know I can access the dataset files using something like...

client = storage.Client()
bucket = client.getbucket('name-of-bucket')
blob = storage.Blob( 'diretory/to/files', bucket )
fid = BytesIO(blob.downloadas_string())

But I'm not sure how to actually serve up a notebook file to use, and I really don't feel like copying and pasting all my previous work.

All help appreciated!

Zain Rizvi
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Chase Brumfield
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2 Answers2

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Very simple. You can upload directly from within the Jupyter Notebook and bypass the bucket if desired (the icon with the up arrow).

Jupyter Notebook upload icon image

The only issue with this is you can't upload folders, so zip the folder first then upload it.

Chase Brumfield
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You can use Jupyter Lab's git extension to host your Notebooks in GitHub and pull them from there.

Fyi, if you use GCP's AI Platform Notebooks you'll get a pre-configured Jupyter environment with many ML/DL libraries pre-installed. That git extension will be pre-installed as well.

Zain Rizvi
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  • Hi @Zain Rizvi. I'm having an issue actually getting a GCP AI Platform Notebook to run on the GPU. Any chance you could take a look? https://stackoverflow.com/questions/57140254/google-cloud-ai-platform-notebook-instance-wont-use-gpu-with-jupyter – Chase Brumfield Jul 22 '19 at 15:32