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57 lines
1.7 KiB
Markdown
57 lines
1.7 KiB
Markdown
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# Troubleshooting
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**Q: What do I do if I get this error when trying to run PyTorch:**
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```bash
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hipErrorNoBinaryForGPU: Unable to find code object for all current devices!
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```
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Ans: The error denotes that the installation of PyTorch and/or other
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dependencies or libraries do not support the current GPU.
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**Workaround:**
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To implement a workaround, follow these steps:
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1. Confirm that the hardware supports the ROCm stack. Refer to
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{ref}`supported_gpus`.
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2. Determine the gfx target.
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```bash
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rocminfo | grep gfx
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```
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3. Check if PyTorch is compiled with the correct gfx target.
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```bash
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TORCHDIR=$( dirname $( python3 -c 'import torch; print(torch.__file__)' ) )
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roc-obj-ls -v $TORCHDIR/lib/libtorch_hip.so # check for gfx target
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```
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:::{note}
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Recompile PyTorch with the right gfx target if compiling from the source if
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the hardware is not supported. For wheels or Docker installation, contact
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ROCm support [^ROCm_issues].
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:::
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**Q: Why am I unable to access Docker or GPU in user accounts?**
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Ans: Ensure that the user is added to docker, video, and render Linux groups as
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described in the ROCm Installation Guide at {ref}`setting_group_permissions`.
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**Q: Can I install PyTorch directly on bare metal?**
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Ans: Bare-metal installation of PyTorch is supported through wheels. Refer to
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Option 2: Install PyTorch Using Wheels Package in the section
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{ref}`install_pytorch_using_wheels` of this guide for more information.
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**Q: How do I profile PyTorch workloads?**
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Ans: Use the PyTorch Profiler to profile GPU kernels on ROCm.
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------
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[^ROCm_issues]: AMD, "ROCm issues," \[Online\]. Available: [https://github.com/RadeonOpenCompute/ROCm/issues](https://github.com/RadeonOpenCompute/ROCm/issues)
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