Tensorlake Documentation

Choose the resources for each job with runs-on. Tensorlake supports Linux x64 runners with Ubuntu 22.04 and Docker; use setup actions to install your language toolchain.

Preconfigured sizes

Use one of these labels for a predefined size. Memory and disk use gibibytes (GiB).

Label	vCPUs	Memory	Writable disk
`tensorlake-small`	2	4 GiB	10 GiB
`tensorlake-medium`	4	8 GiB	50 GiB
`tensorlake-large`	8	16 GiB	100 GiB
`tensorlake-xlarge`	16	32 GiB	100 GiB

For example, request 8 vCPUs and 16 GiB of memory:

runs-on: tensorlake-large

The label tensorlake alone selects the small size. You don’t need to include self-hosted.

Custom sizes

Use tensorlake with all three resource labels to choose a custom size. This example requests 6 vCPUs, 12 GiB of memory, and 60 GiB of writable disk:

runs-on:
  - tensorlake
  - tensorlake-cpu-6
  - tensorlake-memory-12gb
  - tensorlake-disk-60gb

Use positive whole numbers without leading zeros and at least 10 GiB of disk. The gb suffix means GiB; don’t combine a preset size with custom resource labels.

Capacity and job lifetime

Runner creation uses your project’s sandbox quotas. A permanent rejection, such as exceeding a resource limit, publishes a failed Tensorlake check and cancels the workflow run; inspect the check for the reason. Each runner has a maximum lifetime of 2 hours, including startup. Set your job’s timeout-minutes below that limit; a higher value doesn’t extend the runner’s lifetime.

GitHub Actions

Choose runner resources

Preconfigured sizes

Custom sizes

Capacity and job lifetime

​Preconfigured sizes

​Custom sizes

​Capacity and job lifetime

Preconfigured sizes

Custom sizes

Capacity and job lifetime