On Windows, this gets us all the way failing in iree compile of the with SD 2.1 base.
- Fix merge errors with sd right pane config UI tab.
- Remove non-requirement.txt install/build of torch/mlir/iree/SRT in setup_venv.ps1, fixing "torch.compile not supported on Windows" error.
- Fix gradio deprecation warning for `root=` FileExplorer kwarg.
- Comment out `precision` and `max_length` kwargs being passed to unet, as not yet supported on main Turbine branch. Avoids keyword argument error.
* Studio2/SD: Fix sd pipeline up to "Windows not supported"
A number of fixes to the SD pipeline as run from the UI, up until the point that dynamo
complains "Windows not yet supported for torch.compile".
* Remove separate install of iree-runtime and iree-compile in setup_venv.ps1, and rely on the
versions installed via the Turbine requirements.txt. Fixes#2063 for me.
* Replace any "None" strings with python None when pulling the config in the UI.
* Add 'hf_auth_token' param to api StableDiffusion class, defaulting to None, and then pass
that in to the various Models where it is required and wasn't already being done before.
* Fix clip custom_weight_params being passed to export_clip_model as "external_weight_file"
rather than "external_weights"
* Don't pass non-existing "custom_vae" parameter to the Turbine Vae Model, instead
pass custom_vae as the "hf_model_id" if it is set. (this may be wrong in the custom vae
cast, but stops the code *always* breaking).
* Studio2/SD/UI: Improve UI config None handling
* When populating the UI from a JSON Config set controls to "None" for null/None
values.
* When generating a JSON Config from the UI set props to null/None for controls
set to "None".
* Use null rather string 'None' in the default config
---------
Co-authored-by: Ean Garvey <87458719+monorimet@users.noreply.github.com>
- add torchvision to setup_venv.ps1 -- we need this for the torchvision::nms that is now a dependency of controlnet features.
- Don't have bad flashy orange updates when using the chatbot
- Don't limit the height of the chatbot -- there's mixed opinions and solutions around this one. I think the default (400) is just way too small and LLMs generate plenty enough to justify matching the output.
* add KDPM2Discrete and a force flag for setup_venv
* add KDPM2Discrete and a force flag for setup_venv
also made sure that Python 3.11 is used for the venv as 3.10
doesn't work anymore
* add KDPM2Discrete and a force flag for setup_venv
also made sure that Python 3.11 is used for the venv as 3.10
doesn't work anymore
This commit cache some of the model parameters to reduce the response
time of shark web.
Signed-Off-by: Gaurav Shukla <gaurav@nod-labs.com>
Signed-off-by: Gaurav Shukla <gaurav@nod-labs.com>
