Torch7 A Matlab-like Environment for Machine Learning

本文探讨了Lua作为MATLAB-like环境在机器学习领域的应用,比较了Lua与Python的优缺点,强调了Lua在嵌入式开发、性能优势及与其他语言的集成能力。

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Torch7: A Matlab-like Environment for Machine Learning

Why not Python? It is hard to talk about a language without starting a flame war. While Lua is well known in the gaming programmer community (because of its speed advantage and great em- bedding capabilities), Python is more popular in a more general public. With no doubt, Python ships with more libraries. However, with no doubt5, “Integrating Lua with C is so easy a child could do it. Lua was designed for this also, from the beginning, and it shows6. This means that with a few hours’ work, any C or C++ library can become a Lua library.”. Another key advantage of Lua is its embedding capabilities: once code has been prototyped, it can be turned into a final system/product with very little extra work. Extra performance can be obtained using LuaJIT, yielding C-like performance for most of the pure Lua code. Lua being written in pure ANSI C, it can be easily compiled for arbitrary targets (cell-phones, embedded CPUs in FPGAs, DSP processors, …). Adding Lua’ speed advantage, the choice was a “no brainer”.

### 安装 PyG-Lib 及其依赖项 为了成功安装 PyG-Lib (PyTorch Geometric) 和其依赖项 `torch-scatter`, `torch-sparse`, `torch-cluster`, `torch-spline-conv` 以及 `torch-geometric`,建议遵循官方推荐的方法来确保兼容性和稳定性。 对于特定版本的 PyTorch 和 CUDA,可以使用如下命令进行安装: ```bash pip install torch-scatter torch-sparse torch-cluster torch-spline-conv torch-geometric -f https://data.pyg.org/whl/torch-{version}+cu{version}.html[^1] ``` 这里 `{version}` 需要替换为实际使用的 PyTorch 版本号和 CUDA 版本号。例如,如果使用的是 PyTorch 1.12.0 和 CUDA 11.3,则 URL 应该设置为 `https://data.pyg.org/whl/torch-1.12.0+cu113.html`. 需要注意的是,在某些情况下最新版的 PyTorch 或者 PyTorch Geometric 可能尚未完全适配所有环境配置[^2]。因此,当遇到安装问题时,可以选择指定较低版本的 PyTorch 来保证兼容性。比如通过 Conda 安装特定版本的 PyTorch: ```bash conda install pytorch=1.10 torchvision torchaudio cudatoolkit=10.2 -c pytorch ``` 另外一种方式是单独依次安装各个依赖库,并明确指明它们所基于的 PyTorch 和 CUDA 的具体版本: ```bash pip install torch_scatter -f https://pytorch-geometric.com/whl/torch-1.12.0%2Bcu113.html pip install torch_sparse -f https://pytorch-geometric.com/whl/torch-1.12.0%2Bcu113.html pip install torch_cluster -f https://pytorch-geometric.com/whl/torch-1.12.0%2Bcu113.html pip install torch_spline_conv -f https://pytorch-geometric.com/whl/torch-1.12.0%2Bcu113.html pip install torch_geometric[^3] ``` 此过程可能会比较耗时,请保持耐心等待完成。
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