tensorflow / tensorflow/tensorboard
ipython; set iframe source via parameters; SageMaker notebook magic support
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Description
I'm using hosted notebooks on SageMaker and accessing them on https://xxxxx.notebook.eu-west-1.sagemaker.aws/notebooks/shallowlearning.ipynb.
I'm starting TB in ipython context with these commands:
%load_ext tensorboard
%tensorboard --logdir s3://xxxx/shallowlearning/logs
Generated iframe has url https://xxxxx.notebook.eu-west-1.sagemaker.aws:6006/ but exposing dynamic ports publicly is not allowed by SageMaker (and I would expect by other hosted notebook providers too). As a workaround SageMaker provides proxy, so TB could be accessed on https://xxxxx.notebook.eu-west-1.sagemaker.aws/proxy/6006/.
Would be nice to have possibility to have parameters display_port and display_hostname to override default variables in https://github.com/tensorflow/tensorboard/blob/master/tensorboard/notebook.py#L381
Let me know if you would welcome PR for this feature.
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First steps
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Research direction
Read tensorboard/notebook.py around line 381 and trace the IPython %tensorboard entry point that assembles the iframe URL. The work is done when supplied display_port and display_hostname values produce the requested SageMaker proxy-style URL instead of the defaults, with behavior verified in the relevant notebook tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, python
- Domain
- cloud, developer-experience
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100