Kohaku-Blueleaf
f9ba7e648a
Revert "Try to reverse the dtype checking mechanism"
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This reverts commit d243e24f53
2024-01-29 22:54:12 +08:00
Kohaku-Blueleaf
d243e24f53
Try to reverse the dtype checking mechanism
2024-01-29 22:49:45 +08:00
Kohaku-Blueleaf
6e7f0860f7
linting
2024-01-29 22:46:43 +08:00
Kohaku-Blueleaf
750dd6014a
Fix potential bugs
2024-01-29 22:27:53 +08:00
Kohaku-Blueleaf
4a66d2fb22
Avoid exceptions to be silenced
2024-01-20 16:33:59 +08:00
Kohaku-Blueleaf
81126027f5
Avoid early disable
2024-01-20 16:31:12 +08:00
Kohaku-Blueleaf
0181c1f76b
Fix nested manual cast
2024-01-19 00:14:03 +08:00
Kohaku-Blueleaf
ca671e5d7b
rearrange if-statements for cpu
2024-01-09 23:30:55 +08:00
Kohaku-Blueleaf
58d5b042cd
Apply the correct behavior of precision='full'
2024-01-09 23:23:40 +08:00
Kohaku-Blueleaf
1fd69655fe
Revert "Apply correct inference precision implementation"
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This reverts commit e00365962b
2024-01-09 23:15:05 +08:00
Kohaku-Blueleaf
e00365962b
Apply correct inference precision implementation
2024-01-09 23:13:34 +08:00
Kohaku-Blueleaf
c2c05fcca8
linting and debugs
2024-01-09 22:53:58 +08:00
KohakuBlueleaf
42e6df723c
Fix bugs when arg dtype doesn't match
2024-01-09 22:39:39 +08:00
Kohaku-Blueleaf
209c26a1cb
improve efficiency and support more device
2024-01-09 22:11:44 +08:00
AUTOMATIC1111
a70dfb64a8
change import statements for #14478
2023-12-31 22:38:30 +03:00
Aarni Koskela
5768afc776
Add utility to inspect a model's parameters (to get dtype/device)
2023-12-31 13:22:43 +02:00
Kohaku-Blueleaf
9a15ae2a92
Merge branch 'dev' into test-fp8
2023-12-03 10:54:54 +08:00
AUTOMATIC1111
af5f0734c9
Merge pull request #14171 from Nuullll/ipex
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Initial IPEX support for Intel Arc GPU
2023-12-02 19:22:32 +03:00
Kohaku-Blueleaf
110485d5bb
Merge branch 'dev' into test-fp8
2023-12-02 17:00:09 +08:00
AUTOMATIC1111
88736b5557
Merge pull request #14131 from read-0nly/patch-1
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Update devices.py - Make 'use-cpu all' actually apply to 'all'
2023-12-02 09:46:19 +03:00
Nuullll
7499148ad4
Disable ipex autocast due to its bad perf
2023-12-02 14:00:46 +08:00
Nuullll
8b40f475a3
Initial IPEX support
2023-11-30 20:22:46 +08:00
obsol
3cd6e1d0a0
Update devices.py
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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
2023-11-27 19:21:43 -05:00
Kohaku-Blueleaf
043d2edcf6
Better naming
2023-11-19 15:56:31 +08:00
Kohaku-Blueleaf
598da5cd49
Use options instead of cmd_args
2023-11-19 15:50:06 +08:00
KohakuBlueleaf
ddc2a3499b
Add MPS manual cast
2023-10-28 16:52:35 +08:00
Kohaku-Blueleaf
d4d3134f6d
ManualCast for 10/16 series gpu
2023-10-28 15:24:26 +08:00
Kohaku-Blueleaf
eaa9f5162f
Add CPU fp8 support
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Since norm layer need fp32, I only convert the linear operation layer(conv2d/linear)
And TE have some pytorch function not support bf16 amp in CPU. I add a condition to indicate if the autocast is for unet.
2023-10-24 01:49:05 +08:00
AUTOMATIC1111
46375f0592
fix for crash when running #12924 without --device-id
2023-09-09 09:39:37 +03:00
catboxanon
5681bf8016
More accurate check for enabling cuDNN benchmark on 16XX cards
2023-08-31 14:57:16 -04:00
AUTOMATIC1111
386245a264
split shared.py into multiple files; should resolve all circular reference import errors related to shared.py
2023-08-09 10:25:35 +03:00
AUTOMATIC1111
0d5dc9a6e7
rework RNG to use generators instead of generating noises beforehand
2023-08-09 08:43:31 +03:00
AUTOMATIC1111
fca42949a3
rework torchsde._brownian.brownian_interval replacement to use device.randn_local and respect the NV setting.
2023-08-03 07:18:55 +03:00
AUTOMATIC1111
84b6fcd02c
add NV option for Random number generator source setting, which allows to generate same pictures on CPU/AMD/Mac as on NVidia videocards.
2023-08-03 00:00:23 +03:00
Aarni Koskela
b85fc7187d
Fix MPS cache cleanup
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Importing torch does not import torch.mps so the call failed.
2023-07-11 12:51:05 +03:00
AUTOMATIC1111
da8916f926
added torch.mps.empty_cache() to torch_gc()
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changed a bunch of places that use torch.cuda.empty_cache() to use torch_gc() instead
2023-07-08 17:13:18 +03:00
Aarni Koskela
ba70a220e3
Remove a bunch of unused/vestigial code
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As found by Vulture and some eyes
2023-06-05 22:43:57 +03:00
AUTOMATIC
8faac8b963
run basic torch calculation at startup in parallel to reduce the performance impact of first generation
2023-05-21 21:55:14 +03:00
AUTOMATIC
028d3f6425
ruff auto fixes
2023-05-10 11:05:02 +03:00
AUTOMATIC
5fe0dd79be
rename CPU RNG to RNG source in settings, add infotext and parameters copypaste support to RNG source
2023-04-29 11:29:37 +03:00
Deciare
d40e44ade4
Option to use CPU for random number generation.
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Makes a given manual seed generate the same images across different
platforms, independently of the GPU architecture in use.
Fixes #9613 .
2023-04-18 23:27:46 -04:00
brkirch
1b8af15f13
Refactor Mac specific code to a separate file
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Move most Mac related code to a separate file, don't even load it unless web UI is run under macOS.
2023-02-01 14:05:56 -05:00
brkirch
2217331cd1
Refactor MPS fixes to CondFunc
2023-02-01 06:36:22 -05:00
brkirch
7738c057ce
MPS fix is still needed :(
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Apparently I did not test with large enough images to trigger the bug with torch.narrow on MPS
2023-02-01 05:23:58 -05:00
AUTOMATIC1111
fecb990deb
Merge pull request #7309 from brkirch/fix-embeddings
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Fix embeddings, upscalers, and refactor `--upcast-sampling`
2023-01-28 18:44:36 +03:00
brkirch
f9edd578e9
Remove MPS fix no longer needed for PyTorch
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The torch.narrow fix was required for nightly PyTorch builds for a while to prevent a hard crash, but newer nightly builds don't have this issue.
2023-01-28 04:16:27 -05:00
brkirch
ada17dbd7c
Refactor conditional casting, fix upscalers
2023-01-28 04:16:25 -05:00
AUTOMATIC
9beb794e0b
clarify the option to disable NaN check.
2023-01-27 13:08:00 +03:00
AUTOMATIC
d2ac95fa7b
remove the need to place configs near models
2023-01-27 11:28:12 +03:00
brkirch
e3b53fd295
Add UI setting for upcasting attention to float32
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Adds "Upcast cross attention layer to float32" option in Stable Diffusion settings. This allows for generating images using SD 2.1 models without --no-half or xFormers.
In order to make upcasting cross attention layer optimizations possible it is necessary to indent several sections of code in sd_hijack_optimizations.py so that a context manager can be used to disable autocast. Also, even though Stable Diffusion (and Diffusers) only upcast q and k, unfortunately my findings were that most of the cross attention layer optimizations could not function unless v is upcast also.
2023-01-25 01:13:04 -05:00
