Public/automatic
1
0
Fork 0
mirror of https://github.com/vladmandic/automatic synced 2026-09-19 09:14:35 +02:00
Code Issues Packages Projects Releases Wiki Activity

restart server redesign

Browse Source
This commit is contained in:
Vladimir Mandic
2023-05-03 17:20:22 -04:00
parent 0af6c70b94
commit 5d8c787a7b
11 changed files with 117 additions and 78 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/mac_specific.py
+6 -6
View File
@@ -1,11 +1,11 @@
import platform
from packaging import version
import torch
try:
import intel_extension_for_pytorch as ipex
import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import
except:
pass
import platform
from modules.sd_hijack_utils import CondFunc
from packaging import version
# has_mps is only available in nightly pytorch (for now) and macOS 12.3+.
@@ -22,7 +22,7 @@ has_mps = check_for_mps()
# MPS workaround for https://github.com/pytorch/pytorch/issues/89784
def cumsum_fix(input, cumsum_func, *args, **kwargs):
def cumsum_fix(input, cumsum_func, *args, **kwargs): # pylint: disable=redefined-builtin
if input.device.type == 'mps':
output_dtype = kwargs.get('dtype', input.dtype)
if output_dtype == torch.int64:
@@ -46,14 +46,14 @@ if has_mps:
# MPS workaround for https://github.com/pytorch/pytorch/issues/79383
CondFunc('torch.Tensor.to', lambda orig_func, self, *args, **kwargs: orig_func(self.contiguous(), *args, **kwargs),
lambda _, self, *args, **kwargs: self.device.type != 'mps' and (args and isinstance(args[0], torch.device) and args[0].type == 'mps' or isinstance(kwargs.get('device'), torch.device) and kwargs['device'].type == 'mps'))
# MPS workaround for https://github.com/pytorch/pytorch/issues/80800
# MPS workaround for https://github.com/pytorch/pytorch/issues/80800
CondFunc('torch.nn.functional.layer_norm', lambda orig_func, *args, **kwargs: orig_func(*([args[0].contiguous()] + list(args[1:])), **kwargs),
lambda _, *args, **kwargs: args and isinstance(args[0], torch.Tensor) and args[0].device.type == 'mps')
# MPS workaround for https://github.com/pytorch/pytorch/issues/90532
CondFunc('torch.Tensor.numpy', lambda orig_func, self, *args, **kwargs: orig_func(self.detach(), *args, **kwargs), lambda _, self, *args, **kwargs: self.requires_grad)
elif version.parse(torch.__version__) > version.parse("1.13.1"):
cumsum_needs_int_fix = not torch.Tensor([1,2]).to(torch.device("mps")).equal(torch.ShortTensor([1,1]).to(torch.device("mps")).cumsum(0))
cumsum_fix_func = lambda orig_func, input, *args, **kwargs: cumsum_fix(input, orig_func, *args, **kwargs)
cumsum_fix_func = lambda orig_func, input, *args, **kwargs: cumsum_fix(input, orig_func, *args, **kwargs) # pylint: disable=unnecessary-lambda-assignment
CondFunc('torch.cumsum', cumsum_fix_func, None)
CondFunc('torch.Tensor.cumsum', cumsum_fix_func, None)
CondFunc('torch.narrow', lambda orig_func, *args, **kwargs: orig_func(*args, **kwargs).clone(), None)