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Jupyter.startWithConfig({'resourceProfile': 'BasicGPU'})
Creating new Resource Profile
As a default, tags come with "Basic" and "BasicGpu" profiles. In case these do not fit your needs, it is possible to create a new profile from your static console using:
var rp = ResourceProfile.upsert({'id': 'YourProfileName', 'name': 'YourProfileName', 'cpuCount': <cpus>, 'memoryMb': <cpu_memory>, 'diskGb': <disk_memory>, 'gpuCount': <gpus>, 'gpuMemoryMb': <gpu_memory>});
If you want to make this your default profile whenever launching a Jupyter service, you can do so with:
Jupyter.setDefaultResourceProfile('YourProfileName')
Access Through IDS
Through IDS, clear controls regarding Jupyter are exposed under the 'ML Studio' section for Application. When you've selected a project, you need to start the Jupyter service to access notebooks on that project. In the creation process, you're able to select the container profile to use for your jupyter service. By default, the 'BasicGPU' profile offers a single K80 GPU.
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