PyTorch on Ubuntu 18.04

Last updated on May 7, 2023 pm

[TOC]

Install PyTorch locally

  • https://pytorch.org/get-started/locally/

Conda (Python)

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conda create -n torch python=3.9
conda activate torch

# select one
conda install pytorch -c soumith 
conda install pytorch torchvision cuda80 -c soumith
conda install pytorch==1.0.0 torchvision==0.2.1 cuda80 -c pytorch

# PyTorch 1.10
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch

test

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python
> import torch

Pip (Python)

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pip install torchvision==0.4.0 -f https://download.pytorch.org/whl/torch_stable.html

pip uninstall torchvision

LibTorch (C++)

  • Dowload the prebuilt libs

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    set(CMAKE_PREFIX_PATH "<path>/libtorch/share/cmake/Torch")

  • Build from Source

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    # example
    git clone --recursive -b v1.0.1 https://github.com/pytorch/pytorch

    cd pytorch
    mkdir build
    cd build

    # options
    export NO_CUDA=1
        
    python ../tools/build_libtorch.py

    The built libtorch library is located at pytorch/torch/lib/tmp_install/ in default.

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    set(Torch_DIR "<path>/pytorch/torch/lib/tmp_install/share/cmake/Torch/")

  • use with cmake

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    find_package(Torch REQUIRED)
    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${TORCH_CXX_FLAGS}")
    target_link_libraries(<target> ${TORCH_LIBRARIES})

  • include dir

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    libtorch/include
    libtorch/include/torch/csrc/api/include

PyTorch 模型文件

  • PyTorch的模型文件一般会保存为 .pth 文件，C++接口一般读取的是 .pt 文件
  • .pth 文件通过 torch.jit.trace 转换后得到 .pt 文件

只保存模型参数，不保存模型结构

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// 保存
torch.save(model.state_dict(), mymodel.pth) // 只保存模型权重参数，不保存模型结构

// 调用
model = My_model(*args, **kwargs)  // 这里需要重新模型结构，My_model
model.load_state_dict(torch.load(mymodel.pth)) // 这里根据模型结构，调用存储的模型参数
model.eval()

保存整个模型，包括模型结构+模型参数

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// 保存
torch.save(model, mymodel.pth)  // 保存整个model的状态

// 调用
model=torch.load(mymodel.pth)  // 这里已经不需要重构模型结构了，直接load就可以
model.eval()

FAQ

UserWarning: CUDA initialization: CUDA unknown error - this may be due to an incorrectly set up environment, e.g. changing env variable CUDA_VISIBLE_DEVICES after program start. Setting the available devices to be zero

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# works for me
sudo rmmod nvidia_uvm
sudo modprobe nvidia_uvm
ML
#Machine Learning #Deep Learning #PyTorch
PyTorch on Ubuntu 18.04
https://cgabc.xyz/posts/70f98416/
Author
Gavin Gao
Posted on
June 25, 2022
Licensed under