Each version of torch is only available for specific versions of CUDA and ROCm.
The Invoke installer and dockerfile try to install torch 2.4.1 with ROCm 5.6
support, which does not exist. As a result, the installation falls back to the
default CUDA version so AMD GPUs aren't detected. This commits fixes that by
bumping the ROCm version to 6.1, as suggested by the PyTorch documentation. [1]
The specified CUDA version of 12.4 is still correct according to [1] so it does
need to be changed.
Closes#7006Closes#7146
[1]: https://pytorch.org/get-started/previous-versions/#v241
When invoke.sh is executed using a symlink with a working directory outside of InvokeAI's root directory, it will fail.
invoke.sh attempts to cd into the correct directory at the start of the script, but will cd into the directory of the symlink instead. This commit fixes that.
This commit corrects a broken link on line 16 that was pointing to the latest release but causing a 404 error (page not found) when clicked. The issue was identified as a trailing dot at the end of the URL, which has now been removed. This ensures users can access the intended latest release page.
We have had a few bugs with v4 related to file encodings, especially on Windows.
Windows uses its own character encodings instead of `utf-8`, often `cp1252`. Some characters cannot be decoded using `utf-8`, causing `UnicodeDecodeError`.
There are a couple places where this can cause problems:
- In the installer bootstrap, we install or upgrade `pip` and decode the result, using `subprocess`.
The input to this includes the user's home dir. In #6105, the user had one of the problematic characters in their username. `subprocess` attempts and fails to decode the username, which crashes the installer.
To fix this, we need to use `locale.getpreferredencoding()` when executing the command.
- Similarly, in the model install service and config class, we attempt to load a yaml config file. If a problematic character is in the path to the file (which often includes the user's home dir), we can get the same error.
One example is #6129 in which the models.yaml migration fails.
To fix this, we need to open the file with `locale.getpreferredencoding()`.
- Remove `CUDA_AND_DML`. This was for onnx, which we have since removed.
- Remove `AUTODETECT`. This option causes problems for windows users, as it falls back on default pypi index resulting in a non-CUDA torch being installed.
- Add more explicit settings for extra index URL, based on the torch website
- Fix bug where `xformers` wasn't installed on linux and/or windows when autodetect was selected
This allows us to easily test the installer without needing the desired version to be published on PyPI:
```sh
python3 installer/lib/main.py --wheel installer/dist/InvokeAI-4.0.0rc6-py3-none-any.whl
```
A warning message and confirmation are displayed when the arg is used.
The rest of the installer is unchanged.
Updating should always be done via the installer. We initially planned to only deprecate the updater, but given the scale of changes for v4, there's no point in waiting to remove it entirely.
- Restructure & update code check workflows
- Add release workflow to handle checks/tests, build and publish to PyPI
- Add docs/RELEASE.md explaining the workflow & process
- `create_installer.sh`: Update to work with the release workflow
- `create_installer.sh` & `tag_release.sh`: Fix the ANSI escape codes for macOS
- `tag_release.sh`: Add check for python binary name
- `tag_release.sh`: Print `git remote -v` output
- `tag_release.sh`: Fix error when deleting nonexistant tags
