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Local Connection Capability

Some advanced platform functionality is enabled through the use of the trainML CLI and SDK's connection capability. This capability is required to perform the following functions:

  • Create a dataset using the Local storage type
  • Populate a job's model code using the Local model type
  • Receive training or inference job model outputs using the Local storage type
  • Allow workers to access services (databases, other applications) running on your local computer at runtime.

Prerequisites​

In order to use the connection capability, you must meet the following prerequisites.

How to Use​

The trainML CLI is the only way to connect to jobs and other resources. Resources that support the connection capability (jobs, datasets, checkpoints, and models) have connect and disconnect subcommands. To connect to a job run:

trainml job connect <job ID or name>

By default, connecting will automatically attach the terminal to the log output of the resource. To connect without attaching, run:

trainml job connect --no-attach <job ID or name>

If you connect without attaching, you need to disconnect after the job is complete to avoid potential conflicts with future jobs:

trainml job disconnect <job ID or name>

You can view the status of your current connections by running:

trainml connection list

You can also obtain the connection command by clicking the Connect button on a resource in the web interface.

Troubleshooting​

Issues Connecting​

Run:

trainml connection remove-all --all-projects

Run docker ps and ensure there are no running containers using a trainML image.