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Merge branch 'master' of https://github.com/vladmandic/automatic

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This commit is contained in:
Seunghoon Lee
2023-07-09 01:29:27 +09:00
parent 99c7f23c89 f0a1c01986
commit cf40282faa
2 changed files with 38 additions and 22 deletions
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modules/devices.py
+11 -4
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@@ -175,8 +175,10 @@ else:
backend = 'cpu'
if backend == 'ipex':
#Fix broken function in ipex 1.13.120+xpu
#Fix broken functions with ipex
from modules.sd_hijack_utils import CondFunc
torch.cuda.empty_cache = torch.xpu.empty_cache
#Functions with dtype errors:
CondFunc('torch.nn.modules.GroupNorm.forward',
lambda orig_func, *args, **kwargs: orig_func(args[0], args[1].to(args[0].weight.data.dtype)),
@@ -184,15 +186,20 @@ if backend == 'ipex':
CondFunc('torch.nn.modules.Linear.forward',
lambda orig_func, *args, **kwargs: orig_func(args[0], args[1].to(args[0].weight.data.dtype)),
lambda *args, **kwargs: args[2].dtype != args[1].weight.data.dtype)
#Functions that does not work with the XPU:
#UniPC:
CondFunc('torch.linalg.solve',
lambda orig_func, *args, **kwargs: orig_func(args[0].to("cpu"), args[1].to("cpu")).to(get_cuda_device_string()),
lambda *args, **kwargs: args[1].device != torch.device("cpu"))
#SDE Samplers:
CondFunc('torchsde._brownian.brownian_interval._randn',
lambda _, size, dtype, device, seed: torch.randn(size, dtype=dtype, device=device, generator=torch.xpu.Generator(device).manual_seed(int(seed))),
lambda _, size, dtype, device, seed: device != torch.device("cpu"))
CondFunc('torch.Generator',
lambda orig_func, device: torch.xpu.Generator(device),
lambda orig_func, device: device != torch.device("cpu") and device != "cpu")
#Diffusers Float64 (ARC GPUs doesn't support double or Float64):
CondFunc('torch.from_numpy',
lambda orig_func, *args, **kwargs: orig_func(args[0].astype('float32')),
lambda *args, **kwargs: args[1].dtype == float)
#ControlNet:
CondFunc('torch.batch_norm',
lambda orig_func, *args, **kwargs: orig_func(args[0].to("cpu"),