PyTorchをインストールする！（Ubuntu Desktop 22.04／GPUなし）
Ubuntu Desktop 22.04で、GPUなしの環境にPyTorchをインストールします。
pipコマンドをインストールする！
pipコマンドをインストールします。
$ sudo apt install python3-pip
PyTorchをインストールする！
以下のコマンドでPyTorchをインストールします。
$ pip3 install torch torchvision torchaudio
Defaulting to user installation because normal site-packages is not writeable
Collecting torch
Downloading torch-2.0.1-cp310-cp310-manylinux1_x86_64.whl (619.9 MB)
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Collecting torchvision
Downloading torchvision-0.15.2-cp310-cp310-manylinux1_x86_64.whl (6.0 MB)
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Collecting torchaudio
Downloading torchaudio-2.0.2-cp310-cp310-manylinux1_x86_64.whl (4.4 MB)
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Collecting nvidia-cuda-runtime-cu11==11.7.99
Downloading nvidia_cuda_runtime_cu11-11.7.99-py3-none-manylinux1_x86_64.whl (849 kB)
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Collecting typing-extensions
Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
Collecting nvidia-cufft-cu11==10.9.0.58
Downloading nvidia_cufft_cu11-10.9.0.58-py3-none-manylinux1_x86_64.whl (168.4 MB)
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Collecting nvidia-nccl-cu11==2.14.3
Downloading nvidia_nccl_cu11-2.14.3-py3-none-manylinux1_x86_64.whl (177.1 MB)
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Collecting nvidia-cudnn-cu11==8.5.0.96
Downloading nvidia_cudnn_cu11-8.5.0.96-2-py3-none-manylinux1_x86_64.whl (557.1 MB)
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Collecting nvidia-cusolver-cu11==11.4.0.1
Downloading nvidia_cusolver_cu11-11.4.0.1-2-py3-none-manylinux1_x86_64.whl (102.6 MB)
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Collecting networkx
Downloading networkx-3.1-py3-none-any.whl (2.1 MB)
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Collecting nvidia-cuda-nvrtc-cu11==11.7.99
Downloading nvidia_cuda_nvrtc_cu11-11.7.99-2-py3-none-manylinux1_x86_64.whl (21.0 MB)
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Collecting nvidia-cusparse-cu11==11.7.4.91
Downloading nvidia_cusparse_cu11-11.7.4.91-py3-none-manylinux1_x86_64.whl (173.2 MB)
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Collecting nvidia-cuda-cupti-cu11==11.7.101
Downloading nvidia_cuda_cupti_cu11-11.7.101-py3-none-manylinux1_x86_64.whl (11.8 MB)
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Collecting triton==2.0.0
Downloading triton-2.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (63.3 MB)
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Collecting nvidia-curand-cu11==10.2.10.91
Downloading nvidia_curand_cu11-10.2.10.91-py3-none-manylinux1_x86_64.whl (54.6 MB)
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Collecting jinja2
Downloading Jinja2-3.1.2-py3-none-any.whl (133 kB)
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Collecting filelock
Downloading filelock-3.12.2-py3-none-any.whl (10 kB)
Collecting sympy
Downloading sympy-1.12-py3-none-any.whl (5.7 MB)
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Collecting nvidia-cublas-cu11==11.10.3.66
Downloading nvidia_cublas_cu11-11.10.3.66-py3-none-manylinux1_x86_64.whl (317.1 MB)
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Collecting nvidia-nvtx-cu11==11.7.91
Downloading nvidia_nvtx_cu11-11.7.91-py3-none-manylinux1_x86_64.whl (98 kB)
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Requirement already satisfied: wheel in /usr/lib/python3/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch) (0.37.1)
Requirement already satisfied: setuptools in /usr/lib/python3/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch) (59.6.0)
Collecting cmake
Downloading cmake-3.27.2-py2.py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (26.1 MB)
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Collecting lit
Downloading lit-16.0.6.tar.gz (153 kB)
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Installing build dependencies ... done
Getting requirements to build wheel ... done
Installing backend dependencies ... done
Preparing metadata (pyproject.toml) ... done
Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/lib/python3/dist-packages (from torchvision) (9.0.1)
Requirement already satisfied: requests in /usr/lib/python3/dist-packages (from torchvision) (2.25.1)
Collecting numpy
Downloading numpy-1.25.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB)
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Requirement already satisfied: MarkupSafe>=2.0 in /usr/lib/python3/dist-packages (from jinja2->torch) (2.0.1)
Collecting mpmath>=0.19
Downloading mpmath-1.3.0-py3-none-any.whl (536 kB)
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Building wheels for collected packages: lit
Building wheel for lit (pyproject.toml) ... done
Created wheel for lit: filename=lit-16.0.6-py3-none-any.whl size=93605 sha256=846379e9ae802b44d3a26e3222faaff4b6e88706ede51ba18729fac9ecb96f4a
Stored in directory: /home/usradmin/.cache/pip/wheels/14/f9/07/bb2308587bc2f57158f905a2325f6a89a2befa7437b2d7e137
Successfully built lit
Installing collected packages: mpmath, lit, cmake, typing-extensions, sympy, nvidia-nvtx-cu11, nvidia-nccl-cu11, nvidia-cusparse-cu11, nvidia-curand-cu11, nvidia-cufft-cu11, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cuda-cupti-cu11, nvidia-cublas-cu11, numpy, networkx, jinja2, filelock, nvidia-cusolver-cu11, nvidia-cudnn-cu11, triton, torch, torchvision, torchaudio
WARNING: The script lit is installed in '/home/usradmin/.local/bin' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
WARNING: The scripts cmake, cpack and ctest are installed in '/home/usradmin/.local/bin' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
WARNING: The script isympy is installed in '/home/usradmin/.local/bin' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
WARNING: The scripts f2py, f2py3 and f2py3.10 are installed in '/home/usradmin/.local/bin' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
WARNING: The scripts convert-caffe2-to-onnx, convert-onnx-to-caffe2 and torchrun are installed in '/home/usradmin/.local/bin' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
Successfully installed cmake-3.27.2 filelock-3.12.2 jinja2-3.1.2 lit-16.0.6 mpmath-1.3.0 networkx-3.1 numpy-1.25.2 nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-cupti-cu11-11.7.101 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 nvidia-cufft-cu11-10.9.0.58 nvidia-curand-cu11-10.2.10.91 nvidia-cusolver-cu11-11.4.0.1 nvidia-cusparse-cu11-11.7.4.91 nvidia-nccl-cu11-2.14.3 nvidia-nvtx-cu11-11.7.91 sympy-1.12 torch-2.0.1 torchaudio-2.0.2 torchvision-0.15.2 triton-2.0.0 typing-extensions-4.7.1
PyTorchの動作確認を行う！
以下実行して、PyTorchが動作することを確認します。私の環境では、以下のエラーが出力されました。
$ python3
Python 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> x = torch.rand(5, 3)
>>> print(x)
tensor([[0.1359, 0.0638, 0.5941],
[0.1376, 0.6351, 0.5440],
[0.1529, 0.4114, 0.0475],
[0.1191, 0.4981, 0.5115],
[0.6708, 0.0850, 0.5077]])
>>> quit()
おわりに
GPUなし環境では、pipコマンドのみで容易にPyTorchをインストールすることができます。
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