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# Using a GPU with CellProfiler Plugins
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# RunCellPose
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These CellProfiler modules currently support using a GPU: LIST MODULES
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## Using RunCellPose with a GPU
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## Tips for Setting Up Your GPU (if you have one)
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If you want to use a GPU to run the model (this is recommended for speed), you'll need a compatible version of PyTorch and a supported GPU.
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General instructions are available at this [link](https://pytorch.org/get-started/locally/).
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If you want to use a GPU to run the model (this is recommended for speed), you'll need a compatible version of PyTorch and a supported GPU. General instructions are available at this [link](https://pytorch.org/get-started/locally/).
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1. Your GPU should be visible in Device Manager under Display Adaptors. If your GPU isn't there, you likely need to install drivers.
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*[Here](https://www.nvidia.com/Download/Find.aspx) is where you can find NVIDIA GPU drivers if you need to install them.
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1. Your GPU should be visible in Device Manager under Display Adaptors.
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If your GPU isn't there, you likely need to install drivers.
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[Here](https://www.nvidia.com/Download/Find.aspx) is where you can find NVIDIA GPU drivers if you need to install them.
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2. To test whether the GPU is configured correctly:
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If you have a previous version of torch installed, make sure to run `pip uninstall torch` first.
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**NOTE**: You might get a warning like this:
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```
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W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
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2022-05-26 20:24:21.906286: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
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```
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If you don't have a GPU, this is not a problem. If you do, your configuration is incorrect and you need to try reinstalling drivers and the correct version of CUDA for your system.
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