| Commit message (Collapse) | Author | Age | Files | Lines |
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remove clean_text()
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Update launch_utils.py - fixes repetead package reinstalls
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Fixes failing dependency checks for extensions having a different package name and import name (for example ffmpeg-python / ffmpeg), which currently is causing the unneeded reinstall of packages at runtime.
In fact with current code, the same string is used when installing a package and when checking for its presence, as you can see in the following example:
> launch_utils.run_pip("install ffmpeg-python", "required package")
[ Installing required package: "ffmpeg-python" ... ]
[ Installed ]
> launch_utils.is_installed("ffmpeg-python")
False
... which would actually return true with:
> launch_utils.is_installed("ffmpeg")
True
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Add import_hook hack to work around basicsr/torchvision incompatibility
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Fixes #13985
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Fix `save_samples` being checked early when saving masked composite
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on hijack being applied
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Initial IPEX support for Intel Arc GPU
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batch images mode
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preprocessing upscale: do not do an extra upscale step if it's not needed
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dir buttons start with / so only the correct dir will be shown and no…
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with a substrings as name from the dir
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use extension name for determining an extension is installed in the index
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AUTOMATIC1111/protect-against-bad-ui-creation-scripts
catch uncaught exception with ui creation scripts
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prevent total webui crash
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Allow use of mutiple styles csv files
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* https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/14122
Fix edge case where style text has multiple {prompt} placeholders
* https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/14005
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Update devices.py - Make 'use-cpu all' actually apply to 'all'
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fixes issue where "--use-cpu" all properly makes SD run on CPU but leaves ControlNet (and other extensions, I presume) pointed at GPU, causing a crash in ControlNet caused by a mismatch between devices between SD and CN
https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/14097
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AUTOMATIC1111/fix-Auto-focal-point-crop-for-opencv-4.8.x
Fix auto focal point crop for opencv >= 4.8
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autocrop.download_and_cache_models
in opencv >= 4.8 the face detection model was updated
download the base on opencv version
returns the model path or raise exception
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AUTOMATIC1111/add-Block-component-creation-callback
add Block component creation callback
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Add FP32 fallback support on sd_vae_approx
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This tries to execute interpolate with FP32 if it failed.
Background is that
on some environment such as Mx chip MacOS devices, we get error as follows:
```
"torch/nn/functional.py", line 3931, in interpolate
return torch._C._nn.upsample_nearest2d(input, output_size, scale_factors)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: "upsample_nearest2d_channels_last" not implemented for 'Half'
```
In this case, ```--no-half``` doesn't help to solve. Therefore this commits add the FP32 fallback execution to solve it.
Note that the ```upsample_nearest2d``` is called from ```torch.nn.functional.interpolate```.
And the fallback for torch.nn.functional.interpolate is necessary at
```modules/sd_vae_approx.py``` 's ```VAEApprox.forward```
```repositories/stable-diffusion-stability-ai/ldm/modules/diffusionmodules/openaimodel.py``` 's ```Upsample.forward```
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This reverts commit 58c19545c83fa6925c9ce2216ee64964eb5129ce.
Since the modification is expected to move to mac_specific.py
(https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14046#issuecomment-1826731532)
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This tries to execute interpolate with FP32 if it failed.
Background is that
on some environment such as Mx chip MacOS devices, we get error as follows:
```
"torch/nn/functional.py", line 3931, in interpolate
return torch._C._nn.upsample_nearest2d(input, output_size, scale_factors)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: "upsample_nearest2d_channels_last" not implemented for 'Half'
```
In this case, ```--no-half``` doesn't help to solve. Therefore this commits add the FP32 fallback execution to solve it.
Note that the submodule may require additional modifications. The following is the example modification on the other submodule.
```repositories/stable-diffusion-stability-ai/ldm/modules/diffusionmodules/openaimodel.py
class Upsample(nn.Module):
..snip..
def forward(self, x):
assert x.shape[1] == self.channels
if self.dims == 3:
x = F.interpolate(
x, (x.shape[2], x.shape[3] * 2, x.shape[4] * 2), mode="nearest"
)
else:
try:
x = F.interpolate(x, scale_factor=2, mode="nearest")
except:
x = F.interpolate(x.to(th.float32), scale_factor=2, mode="nearest").to(x.dtype)
if self.use_conv:
x = self.conv(x)
return x
..snip..
```
You can see the FP32 fallback execution as same as sd_vae_approx.py.
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Add support for SD 2.1 Turbo
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on load
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sd_hijack is only partially undone
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