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Problem: The memory will slowly increase with the drawing until restarting.
Observation: GC analysis shows that no occupation has occurred, so it is suspected to be a problem with the underlying allocator.
Reason: Under Linux, glibc is used to allocate memory. glibc uses brk and mmap to allocate memory, and the memory allocated by brk cannot be released until the high-address memory is released. That is to say, if you apply for two pieces of memory A and B through brk, it is impossible to release A before B is released, and it is still occupied by the process. Check the suspected "memory leak" through TOP.
So I replaced TCMalloc, but found that libtcmalloc_minimal could not find ptthread_Key_Create. After analysis, it was found that pthread was not entered during compilation.
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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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AUTOMATIC1111/rework-mask-and-mask_composite-logic
slight optimization for mask and mask_composite
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Fixes #13985
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Fix `save_samples` being checked early when saving masked composite
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Re-add `keyedit_delimiters_whitespace` setting lost as part of commit e294e46
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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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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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Allow use of mutiple styles csv files
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Support XYZ scripts / split hires path from unet
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Update devices.py - Make 'use-cpu all' actually apply to 'all'
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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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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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fix not able to exit metadata popup when pop up is too big
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Add support for SD 2.1 Turbo
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option to not include VAE in infotext, add explanation to infotext settings page, move some options to infotext settings page
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on load
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sd_hijack is only partially undone
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prevent the pop-up from being too big as to making exiting the pop-up impossible
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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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