How does one use Pytorch (+ cuda) with an A100 GPU?

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How does one use Pytorch (+ cuda) with an A100 GPU?

  1. How to solve How does one use Pytorch (+ cuda) with an A100 GPU?

    From the link pytorch site from @SimonB 's answer, I did:
    pip3 install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html
    This solved the problem for me.

  2. How does one use Pytorch (+ cuda) with an A100 GPU?

    From the link pytorch site from @SimonB 's answer, I did:
    pip3 install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html
    This solved the problem for me.

Solution 1

From the link pytorch site from @SimonB ‘s answer, I did:

pip3 install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html

This solved the problem for me.

Original Author James Hirschorn Of This Content

Solution 2

I’ve got an A100 and have had success with

conda install pytorch torchvision torchaudio cudatoolkit=11.1 -c pytorch -c nvidia

Which is now also recommended on the pytorch site

Original Author Simon B Of This Content

Solution 3

I had the same problem. You need to install CUDA 11.0 instead of 10.2 and reinstall PyTorch for this CUDA version.

Original Author guillaumefrd Of This Content

Solution 4

To me this is what worked:

conda update conda
pip install --upgrade pip
pip3 install --upgrade pip

conda create -n meta_learning_a100 python=3.9
conda activate meta_learning_a100

pip3 install torch==1.9.1+cu111 torchvision==0.10.1+cu111 torchaudio==0.9.1 -f https://download.pytorch.org/whl/torch_stable.html

then I tested it, asked for the device and did a matrix multiply, no errors is it worked:

(meta_learning_a100) [[email protected] diversity-for-predictive-success-of-meta-learning]$ python -c "import uutils; uutils.torch_uu.gpu_test()"
device name: A100-SXM4-40GB
Success, no Cuda errors means it worked see:
out=tensor([[ 0.5877],
        [-3.0269]], device='cuda:0')

gpu pytorch code:

def gpu_test():
    """
    python -c "import uutils; uutils.torch_uu.gpu_test()"
    """
    from torch import Tensor

    print(f'device name: {device_name()}')
    x: Tensor = torch.randn(2, 4).cuda()
    y: Tensor = torch.randn(4, 1).cuda()
    out: Tensor = (x @ y)
    assert out.size() == torch.Size([2, 1])
    print(f'Success, no Cuda errors means it worked see:\n{out=}')

Original Author guillaumefrd Of This Content

Conclusion

So This is all About This Tutorial. Hope This Tutorial Helped You. Thank You.

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I am an Information Technology Engineer. I have Completed my MCA And I have 4 Year Plus Experience, I am a web developer with knowledge of multiple back-end platforms Like PHP, Node.js, Python and frontend JavaScript frameworks Like Angular, React, and Vue.

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