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quark-install

Installs or verifies AMD Quark and ensures the selected Python environment has an accelerator-matched PyTorch. Applies to "install Quark", "set up Quark", "pip install amd-quark", Quark dependency or import failures, ModuleNotFoundError for quark, and Quark kernel compiler errors. Defaults to GPU and requires explicit confirmation before CPU mode. Covers PyPI universal, exactly matched native, local-wheel, and local-source installs. Does not handle standalone PyTorch requests, ONNX Runtime-only setup, or quantization.

skills/quark-install/SKILL.md

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Nov 7, 2026
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MIT

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# Quark Install

## Purpose

Install or verify `amd-quark` without relying on another skill, a Quark checkout, or pre-generated workflow artifacts. Detect the actual hardware, ensure PyTorch matches it, choose the smallest safe Quark install, obtain approval, execute it, and verify the requested capabilities.

## Prerequisites

- GPU support depends on the selected PyTorch build and Quark wheel. Record the actual runtime, host kernel and driver, and GPU architecture (`gfx...` from `gcnArchName` on AMD); verify compatibility with that environment instead of assuming a fixed ROCm version or GPU target.
- No container image is required. If running in a container, record its image name or digest when available and verify GPU device access.
- Inspect and preserve `QUARK_ACCELERATOR`, `PYTORCH_ROCM_ARCH`, `QUARK_BUILD_DISABLE_JIT_FALLBACK`, `HSA_OVERRIDE_GFX_VERSION`, `HIP_VISIBLE_DEVICES`, and `CUDA_VISIBLE_DEVICES`. Include any required changes in the confirmed install plan. Report `PIP_EXTRA_INDEX_URL` only as set or unset because its value may contain credentials.

## Inputs