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[IPEX] Fix batch_norm for Tiled VAE

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Tiled VAE invokes `torch.nn.functional.batch_norm` without providing the
`weight` and `bias` parameter, so torch backend creates default empty
tensors for them but bails out with "tensor does not have a device" error.

This patch overrides the `weight` and `bias` parameters to all-ones and
all-zeros if they are `None`.
This commit is contained in:
Nuullll
2023-07-27 18:48:16 +08:00
parent 86a0cb5f7e
commit 6acb3ef131
1 changed files with 8 additions and 8 deletions
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modules/devices.py
+8 -8
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@@ -250,14 +250,6 @@ if backend == 'ipex':
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"),
args[1].to("cpu") if args[1] is not None else args[1],
args[2].to("cpu") if args[2] is not None else args[2],
args[3].to("cpu") if args[3] is not None else args[3],
args[4].to("cpu") if args[4] is not None else args[4],
args[5], args[6], args[7], args[8]).to(get_cuda_device_string()),
lambda *args, **kwargs: args[1].device != torch.device("cpu"))
CondFunc('torch.instance_norm',
lambda orig_func, *args, **kwargs: orig_func(args[0].to("cpu"),
args[1].to("cpu") if args[1] is not None else args[1],
@@ -266,6 +258,14 @@ if backend == 'ipex':
args[4].to("cpu") if args[4] is not None else args[4],
args[5], args[6], args[7], args[8]).to(get_cuda_device_string()),
lambda *args, **kwargs: args[1].device != torch.device("cpu"))
#Tiled VAE:
#Create xpu tensors for weight (ones) and bias (zeros) if they're not provided
CondFunc('torch.batch_norm',
lambda orig_func, *args, **kwargs: orig_func(args[0],
args[1] or torch.ones(args[0].size()[1], device=get_cuda_device_string()),
args[2] or torch.zeros(args[0].size()[1], device=get_cuda_device_string()),
args[3], args[4], args[5], args[6], args[7], args[8]),
lambda orig_func, *args, **kwargs: args[0].device != torch.device("cpu"))
if backend == "directml":
directml_init()