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Remove links to docs.amd.com (#2200)

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* Remove links to docs.amd.com

* Fix linking to list item (not possible)
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Nagy-Egri Máté Ferenc
2023-06-01 16:16:38 +02:00
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docs/examples/troubleshooting.md
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@@ -7,13 +7,15 @@
hipErrorNoBinaryForGPU: Unable to find code object for all current devices!
```
Ans: The error denotes that the installation of PyTorch and/or other dependencies or libraries do not support the current GPU.
Ans: The error denotes that the installation of PyTorch and/or other
dependencies or libraries do not support the current GPU.
**Workaround:**
To implement a workaround, follow these steps:
1. Confirm that the hardware supports the ROCm stack. Refer to the Hardware and Software Support document at [https://docs.amd.com](https://docs.amd.com).
1. Confirm that the hardware supports the ROCm stack. Refer to
{ref}`supported_gpus`.
2. Determine the gfx target.
@@ -29,16 +31,21 @@ To implement a workaround, follow these steps:
```
:::{note}
Recompile PyTorch with the right gfx target if compiling from the source if the hardware is not supported. For wheels or Docker installation, contact ROCm support [^ROCm_issues].
Recompile PyTorch with the right gfx target if compiling from the source if
the hardware is not supported. For wheels or Docker installation, contact
ROCm support [^ROCm_issues].
:::
**Q: Why am I unable to access Docker or GPU in user accounts?**
Ans: Ensure that the user is added to docker, video, and render Linux groups as described in the ROCm Installation Guide at [https://docs.amd.com](https://docs.amd.com).
Ans: Ensure that the user is added to docker, video, and render Linux groups as
described in the ROCm Installation Guide at {ref}`setting_group_permissions`.
**Q: Can I install PyTorch directly on bare metal?**
Ans: Bare-metal installation of PyTorch is supported through wheels. Refer to Option 2: Install PyTorch Using Wheels Package in the section [Installing PyTorch](/ROCm/docs/how_to/pytorch_install/pytorch_install) of this guide for more information.
Ans: Bare-metal installation of PyTorch is supported through wheels. Refer to
Option 2: Install PyTorch Using Wheels Package in the section
{ref}`install_pytorch_using_wheels` of this guide for more information.
**Q: How do I profile PyTorch workloads?**