Installing gsl from the conda-forge channel can be achieved by adding conda-forge to your channels with: conda config --add channels conda-forge Once the conda-forge channel has been enabled, gsl can be installed with: conda install gsl It is possible to list all of the versions of gsl...
active env location:/opt/conda/envs/gsl shell level:2 user config file:/root/.condarc populated config files:/opt/conda/.condarc conda version:24.5.0 conda-build version:not installed python version:3.10.14.final.0 solver:libmamba (default) ...
报错如下: * installing *source* package ‘gsl’ ... ** package ‘gsl’ successfully unpacked and MD5 sums checked...** using staged installation checking for gsl-config...
bcftools: error while loading shared libraries: libgsl.so.25: cannot open shared object file: No such file or directory 资料搜索 gsl是c语言编写的与计算有关的数据库。 conda安装bcftools时,可能启用参数--enable-libgsl。但是本地服务器不存在该库,所以产生报错。摘自链接。 查看动态库: $ ldconfig -...
Xmake 新增了vcpkg清单模式支持,通过它,我们就能支持vcpkg包的版本选择,例如: add_requires("vcpkg::zlib...") add_files("src/*.cpp") add_packages("vcpkg::zlib", "vcpkg::fmt", "vcpkg::libpng") 但是,vcpkg...,Xrepo 还可以安装来自第三方包管理器的包,例如vcpkg/conan/conda/pacman/homebrew/apt...
Check forgsl::target rather than nonexistentgsl-lite::target in Config.cmake (#315, thanks to@Ram-Z) Additions: Addgsl::make_unique<T>()andgsl::make_shared<T>()which resemble the eponymous functions fromstdbut returngsl::not_null<std::unique_ptr<T>>andgsl::not_null<std::shared_ptr...
conda create --name isis_4_2 python=3.6.0 -c defaults < I added the .0 and defaults were my addition, as I was running into issues there as well I decided to enforce some restrictions conda activate isis_4_2 conda config --env --add channels conda-forge...
报错如下: * installing *source* package ‘gsl’ ... ** package ‘gsl’ successfully unpacked and MD5 sums checked...** using staged installation checking for gsl-config...
A conda-smithy repository for gsl. Contribute to conda-forge/gsl-feedstock development by creating an account on GitHub.
Change config in recbole_cdr/properties/model/MFGSLAE.yaml like this: dropout_prob: 0.7 tau: 0.5 factor: 4 epsilon: 5 alpha: 0.1 ratio: 0.99 ratio_threshold: 0.5 l1_rate: 1e-06 learning_rate: 0.001 weight_decay: 0.01 latent_dimension: 64 use_user_loader: true...