Install this version:
emerge -a =dev-python/conch-triton-kernels-1.2.1If this version is masked, you can unmask it using the autounmask tool or standard emerge options:
autounmask =dev-python/conch-triton-kernels-1.2.1Or alternatively:
emerge --autounmask-write -a =dev-python/conch-triton-kernels-1.2.1| Version | EAPI | Keywords | Slot |
|---|---|---|---|
| 1.2.1 | 8 | ~amd64 | 0 |
# Copyright 1999-2026 Gentoo Authors
# Distributed under the terms of the GNU General Public License v2
EAPI=8
DISTUTILS_USE_PEP517=setuptools
PYTHON_COMPAT=( python3_{11..14} )
inherit distutils-r1 pypi
DESCRIPTION="Stack AV's Triton kernel repository for GPU-accelerated ML"
HOMEPAGE="
https://github.com/stackav-oss/conch
https://pypi.org/project/conch-triton-kernels/
"
LICENSE="Apache-2.0"
SLOT="0"
KEYWORDS="~amd64"
# Hard runtime dep is just numpy. Triton + torch are pulled in via
# upstream's [cpu]/[cuda]/[rocm]/[xpu] extras and accessed lazily inside
# kernel functions — calling a kernel without triton installed raises
# ImportError, which is the same behavior we'd get from the wheel.
# triton itself is not in any tree we depend on, so we can't declare it.
RDEPEND="
>=dev-python/numpy-1.26.4[${PYTHON_USEDEP}]
"
BDEPEND="
dev-python/setuptools-scm[${PYTHON_USEDEP}]
"
export SETUPTOOLS_SCM_PRETEND_VERSION=${PV}
>=dev-python/numpy-1.26.4[]
dev-python/setuptools-scm[]