SDK (Python) - Compute

The Python package you write against is the same one the CLI uploads.

import compute

app = compute.App("my-job")
image = compute.Image.cuda_pytorch()


@app.function(gpu="H100-80GB", image=image, timeout=600)
def train(steps: int = 40) -> dict:
    # imports that need the GPU image go inside the function
    return {"ok": True, "steps": steps}

Then:

compute run train.py::train --gpu H100-SXM --wait

Surface that is documented

Symbol	Role
`compute.App(name)`	Names the app in the upload.
`compute.Image.cuda_pytorch()`	NVIDIA / H100 image.
`compute.Image.rocm_pytorch()`	AMD / MI300X image.
`@app.function(...)`	Marks the entrypoint. `gpu`, `image`, `timeout`.
`fn.remote(**kwargs)`	In-script call shape. Args and return must be JSON.

Put GPU-only imports inside the function so local dry-runs and packaging stay honest.

Not in this manual

Do not treat local process spawning, detached handles you wait on later, persistent disks, or extra decorators as supported customer API. If it is not in the table above, do not build a workflow on it.

Timeout

Decorator timeout= is seconds on the function. The v0.1 public default / cap is 10 minutes. See Limits.

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