a70dfb64a8
change import statements for #14478
2023-12-31 22:38:30 +03:00
5768afc776
Add utility to inspect a model's parameters (to get dtype/device)
2023-12-31 13:22:43 +02:00
9a15ae2a92
Merge branch 'dev' into test-fp8
2023-12-03 10:54:54 +08:00
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
110485d5bb
Merge branch 'dev' into test-fp8
2023-12-02 17:00:09 +08:00
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
7499148ad4
Disable ipex autocast due to its bad perf
2023-12-02 14:00:46 +08:00
8b40f475a3
Initial IPEX support
2023-11-30 20:22:46 +08:00
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
043d2edcf6
Better naming
2023-11-19 15:56:31 +08:00
598da5cd49
Use options instead of cmd_args
2023-11-19 15:50:06 +08:00
ddc2a3499b
Add MPS manual cast
2023-10-28 16:52:35 +08:00
d4d3134f6d
ManualCast for 10/16 series gpu
2023-10-28 15:24:26 +08:00
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
46375f0592
fix for crash when running #12924 without --device-id
2023-09-09 09:39:37 +03:00
5681bf8016
More accurate check for enabling cuDNN benchmark on 16XX cards
2023-08-31 14:57:16 -04:00
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
0d5dc9a6e7
rework RNG to use generators instead of generating noises beforehand
2023-08-09 08:43:31 +03:00
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
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
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
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
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
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
028d3f6425
ruff auto fixes
2023-05-10 11:05:02 +03:00
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
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
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
2217331cd1
Refactor MPS fixes to CondFunc
2023-02-01 06:36:22 -05:00
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
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
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
ada17dbd7c
Refactor conditional casting, fix upscalers
2023-01-28 04:16:25 -05:00
9beb794e0b
clarify the option to disable NaN check.
2023-01-27 13:08:00 +03:00
d2ac95fa7b
remove the need to place configs near models
2023-01-27 11:28:12 +03:00
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
84d9ce30cb
Add option for float32 sampling with float16 UNet
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This also handles type casting so that ROCm and MPS torch devices work correctly without --no-half. One cast is required for deepbooru in deepbooru_model.py, some explicit casting is required for img2img and inpainting. depth_model can't be converted to float16 or it won't work correctly on some systems (it's known to have issues on MPS) so in sd_models.py model.depth_model is removed for model.half().
2023-01-25 01:13:02 -05:00
aa60fc6660
Merge pull request #6922 from brkirch/cumsum-fix
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Improve cumsum fix for MPS
2023-01-19 13:18:34 +03:00
a255dac4f8
Fix cumsum for MPS in newer torch
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The prior fix assumed that testing int16 was enough to determine if a fix is needed, but a recent fix for cumsum has int16 working but not bool.
2023-01-17 20:54:18 -05:00
c361b89026
disable the new NaN check for the CI
2023-01-17 11:05:01 +03:00
9991967f40
Add a check and explanation for tensor with all NaNs.
2023-01-16 22:59:46 +03:00
8111b5569d
Add support for PyTorch nightly and local builds
2023-01-05 20:54:52 -05:00
16b4509fa6
Add numpy fix for MPS on PyTorch 1.12.1
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When saving training results with torch.save(), an exception is thrown:
"RuntimeError: Can't call numpy() on Tensor that requires grad. Use tensor.detach().numpy() instead."
So for MPS, check if Tensor.requires_grad and detach() if necessary.
2022-12-17 04:22:58 -05:00
b6e5edd746
add built-in extension system
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add support for adding upscalers in extensions
move LDSR, ScuNET and SwinIR to built-in extensions
2022-12-03 18:06:33 +03:00
46b0d230e7
add comment for #4407 and remove seemingly unnecessary cudnn.enabled
2022-12-03 16:01:23 +03:00
2651267e3a
fix #4407 breaking UI entirely for card other than ones related to the PR
2022-12-03 15:57:52 +03:00
681c0003df
Merge pull request #4407 from yoinked-h/patch-1
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Fix issue with 16xx cards
2022-12-03 10:30:34 +03:00
0fddb4a1c0
Rework MPS randn fix, add randn_like fix
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torch.manual_seed() already sets a CPU generator, so there is no reason to create a CPU generator manually. torch.randn_like also needs a MPS fix for k-diffusion, but a torch hijack with randn_like already exists so it can also be used for that.
2022-11-30 10:33:42 -05:00
cc90dcc933
Merge pull request #4918 from brkirch/pytorch-fixes
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Fixes for PyTorch 1.12.1 when using MPS
2022-11-27 13:47:01 +03:00
5b2c316890
eliminate duplicated code from #5095
2022-11-27 13:08:54 +03:00
AUTOMATIC1111