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gnu: Add ctranslate2.
* gnu/packages/machine-learning.scm (ctranslate2): New variable. * gnu/packages/patches/CTranslate2-local-build.patch: New file. * gnu/local.mk: Record patch. Co-authored-by: Nicolas Graves <ngraves@ngraves.fr> Change-Id: I61f04d92c9f4c7bff41b62867ef43e8cf3ad87ea
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@ -30,6 +30,7 @@
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;;; Copyright © 2024 Spencer King <spencer.king@geneoscopy.com>
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;;; Copyright © 2024, 2025 David Elsing <david.elsing@posteo.net>
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;;; Copyright © 2024 Andy Tai <atai@atai.org>
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;;; Copyright © 2025 Lapearldot <lapearldot@disroot.org>
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;;;
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;;; This file is part of GNU Guix.
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;;;
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@ -107,6 +108,7 @@
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#:use-module (gnu packages libffi)
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#:use-module (gnu packages linux)
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#:use-module (gnu packages llvm)
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#:use-module (gnu packages logging)
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#:use-module (gnu packages maths)
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#:use-module (gnu packages mpi)
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#:use-module (gnu packages ninja)
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@ -6291,6 +6293,50 @@ Transformers is backed by the three most popular deep learning libraries —
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Jax, PyTorch and TensorFlow — with a seamless integration between them.")
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(license license:asl2.0)))
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(define-public ctranslate2
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(package
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(name "ctranslate2")
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(version "4.6.0")
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(source
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(origin
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(method git-fetch)
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(uri (git-reference
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(url "https://github.com/OpenNMT/CTranslate2")
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(commit (string-append "v" version))))
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(file-name (git-file-name "CTranslate2" version))
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(sha256 (base32 "0sngxjq5rmrgjabgxfazdnhfn3wpfi62n226f4k47cx1xjjkllcd"))
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(patches (search-patches "ctranslate2-local-build.patch"))))
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(build-system cmake-build-system)
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(arguments
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(list
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#:test-target "ctranslate2_test"
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;; XXX: mkl and openblas seem incompatible.
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#:configure-flags `(list "-DBUILD_TESTS=ON"
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"-DWITH_ACCELERATE=OFF"
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"-DWITH_RUY=OFF"
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"-DWITH_DNNL=ON"
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"-DWITH_CUDA=OFF"
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"-DWITH_CUDNN=OFF"
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"-DWITH_MKL=OFF"
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"-DWITH_OPENBLAS=ON")))
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(native-inputs (list libomp
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cxxopts
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spdlog
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googletest
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cpu-features
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oneapi-dnnl
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openblas))
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(home-page "https://opennmt.net/CTranslate2/")
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(synopsis "Fast inference engine for Transformer models")
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(description "CTranslate2 is a C++ and Python library for efficient
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inference with Transformer models.
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The project implements a custom runtime that applies many performance
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optimization techniques such as weights quantization, layers fusion, batch
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reordering, etc., to accelerate and reduce the memory usage of Transformer
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models on CPU and GPU.")
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(license license:expat)))
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(define-public python-hmmlearn
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(package
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(name "python-hmmlearn")
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