Stack

GitHub Actions runners for PyTorch

GitHub-hosted runners have no GPU, so any test that touches CUDA falls back to CPU and times out. Cirun runs your PyTorch CI on a right-sized cloud VM on your own account — pick AWS, GCP, Azure, Oracle, DigitalOcean, OpenStack or on-prem, billed by your cloud, never per CI minute.

Run PyTorch on Cirun Docs

Why this fits

GitHub-hosted runners have no GPU, so any test that touches CUDA falls back to CPU and times out.
Cirun is cloud-neutral — every supported cloud has at least one SKU that fits PyTorch; pick whichever account you already have.
Ephemeral by default — no state from the previous PR leaks into yours, no flaky-cache surprises.

.cirun.yml

1runners:
2  - name: pytorch-runner
3    cloud: aws
4    instance_type: g5.xlarge
5    # Use AWS Deep Learning AMI GPU PyTorch on Ubuntu 22.04
6    # (Marketplace) for pre-installed CUDA + drivers, or the
7    # Cirun-published NVIDIA AMI.
8    machine_image: ami-04823729c75214919
9    labels:
10      - cirun-pytorch

.cirun.yml

1runners:
2  - name: pytorch-runner
3    cloud: gcp
4    instance_type: a2-highgpu-1g
5    # Use a GCP Deep Learning VM image family
6    # (deeplearning-platform-release) for pre-installed CUDA + drivers.
7    machine_image: projects/deeplearning-platform-release/global/images/family/pytorch-latest-cu121
8    labels:
9      - cirun-pytorch

.cirun.yml

1runners:
2  - name: pytorch-runner
3    cloud: azure
4    instance_type: Standard_ND96asr_v4
5    # Use Microsoft's HPC/DSVM Ubuntu image for pre-installed CUDA +
6    # drivers.
7    machine_image: microsoft-dsvm:ubuntu-hpc:2204:latest
8    labels:
9      - cirun-pytorch