# Pytorch for cuda 10.2

**URL:** <https://discuss.pytorch.org/t/pytorch-for-cuda-10-2/65524>\
**Category:** Uncategorized\
**Created:** [January 1, 2020, 4:13pm UTC](https://discuss.pytorch.org/t/pytorch-for-cuda-10-2/65524 "2020-01-01T16:13:15Z")\
**Posts on this page:** 1\
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**Author:** ![ptrblck](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/ptrblck/32/1823_2.png) [@ptrblck](https://discuss.pytorch.org/u/ptrblck)\
**Post date:** [February 1, 2020, 5:38am UTC](https://discuss.pytorch.org/t/pytorch-for-cuda-10-2/65524/6 "2020-02-01T05:38:14Z")

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1. Linear algebra methods rely on magma (e.g. [here](https://github.com/pytorch/pytorch/blob/877c96cddfebee00385307f9e1b1f3b4ec72bfdc/aten/src/ATen/native/cuda/BatchLinearAlgebra.cu#L22)) so you won’t be able to use them. However, a lot of models don’t use these methods, so as long as you don’t need to e.g. calculate the log determinant of your weight parameter, you should be fine.

2. I would recommend to stick to [pytorch/builder](https://github.com/pytorch/builder/tree/master/conda/magma-cuda101-2.5.1) for the magma build.  
For CUDA10.2 you shouldn’t need any changes in the build script besides the CUDA version change, but let me know, if you get stuck. Also, you could have a look at the [NGC PyTorch container](https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel_20-01.html#rel_20-01), which ships with CUDA10.2.

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