CODEWITHSUNDEEP
pythonrestgoogle-cloud-platformgoogle-cloud-vertex-ai
ronak roy
ronak roy

Reputation: 29

How to use custom python version by passing Python version argument in rest API call to create vertex AI managed notebook runtime?

RUNTIME_BODY="{
  'access_config': {
        'access_type': 'SINGLE_USER',
        'runtime_owner': '[email protected]'
        },
        'labels': {'user_name':'abc-def'},
  'software_config': {
        'idle_shutdown': true,
        'idle_shutdown_timeout': 120
      },
  'virtual_machine': {
    'virtual_machine_config': {
      'network': 'projects/prj-bde-01/global/networks/',
      'subnet': 'projects/prj01/regions/$LOCATION/subnetworks/prj-wxft-001',
      'data_disk': {
         'initialize_params': {
            'disk_size_gb': 120,
            'disk_type': 'PD_SSD',
        }
      },
      'machine_type':'n1-standard-4'
    }
  }

}

The above code created jupyter runtime with default Python version. Modify it to provide custom Python version.

Upvotes: 0

Views: 69

Answers (1)

gogasca
gogasca

Reputation: 10058

You will need to use custom containers. https://cloud.google.com/vertex-ai/docs/workbench/managed/custom-container

Upvotes: 0

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