Alexander Miroshnichenko
ab88b09ceb
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Package FreeToken (FlashML-org/FreeToken) — edge-native MoE serving engine with OpenAI/Anthropic-compatible APIs, serving the `ft` CLI. - torch-bin 2.11 (CUDA 12.9 wheel build) satisfies the torch>=2.11,<2.12 pin; extensions link the same cudaPackages.cuda_cudart via a synthetic CUDA_HOME (cudart headers + nvcc crt/ headers, no nvcc needed). - flashlib==0.3.0 vendored from the PyPI wheel (Triton-only; freetoken never imports the CuTeDSL GEMM backends, so nvidia-cutlass-dsl is omitted via pythonRemoveDeps). - apache-tvm-ffi overridden to the pinned 0.1.13.post3 with a vendored cython 3.3.0 (build needs >=3.2.8, nixpkgs has 3.2.4); pytest skipped (upstream runs pytest-xdist with GPU tests). - Unfree (CUDA EULA) is self-scoped: the package re-imports nixpkgs with config.allowUnfree so no flake-level or user config change is needed. - Optional accel extras (flashinfer/sglang-kernel) and the kernel-cache wheel are not packaged; runtime falls back to pure-Triton kernels. - Verified: nix build .#freetoken, ft --version, python imports check, extension RPATHs.
52 lines
1.5 KiB
Nix
52 lines
1.5 KiB
Nix
{
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lib,
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buildPythonPackage,
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fetchurl,
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# dependencies
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numpy,
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numba,
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# torch-bin (CUDA wheel build) and triton-bin are passed by the caller;
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# the python scope defaults are the source-built torch (CPU-only) and
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# triton — using them would duplicate torch/triton in the closure.
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torch,
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triton,
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tqdm,
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}:
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buildPythonPackage rec {
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pname = "flashlib";
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version = "0.3.0";
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format = "wheel";
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src = fetchurl {
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url = "https://files.pythonhosted.org/packages/e5/b8/4c085892462e521bb9f2d943ff34fa219e3a5a206798f3c96a983538039f/flashlib-0.3.0-py3-none-any.whl";
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hash = "sha256-kDeRHzFf7zyfRFMmFZc2Ory4OGiBOtGyWKsTCLNP0Ro=";
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};
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# freetoken pins flashlib==0.3.0 (not in nixpkgs) and only uses its Triton
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# kernels (flashlib.kernels.slot_cache). nvidia-cutlass-dsl — needed only by
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# the CuTeDSL GEMM backends in flashlib.linalg, which drag in cuda-python and
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# nvdisasm binary wheels — is deliberately not packaged (and removed from
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# the wheel metadata so the runtime deps check passes).
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pythonRemoveDeps = [ "nvidia-cutlass-dsl" ];
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dependencies = [
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numpy
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numba
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torch
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triton
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tqdm
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];
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# flashlib is CPU-safe at import time: CuteDSL imports are lazy and hardware
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# detection (flashlib._hw) is cuda-optional.
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pythonImportsCheck = [ "flashlib" ];
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meta = {
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description = "High-performance ML primitives — Triton and CuteDSL kernels for NVIDIA GPUs";
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homepage = "https://pypi.org/project/flashlib/";
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license = lib.licenses.asl20;
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platforms = lib.platforms.linux;
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};
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}
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