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authorAUTOMATIC1111 <16777216c@gmail.com>2023-01-13 11:57:38 +0000
committerGitHub <noreply@github.com>2023-01-13 11:57:38 +0000
commit9cd7716753c5be47f76b8e5555cc3e7c0f17d34d (patch)
tree345be78dd1991b77fcf4519bc44097e975e0b0c4 /modules/sd_hijack_unet.py
parent18f86e41f6f289042c075bff1498e620ab997b8c (diff)
parent544e7a233e994f379dd67df08f5f519290b10293 (diff)
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Merge branch 'master' into tensorboard
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diff --git a/modules/sd_hijack_unet.py b/modules/sd_hijack_unet.py
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+import torch
+
+
+class TorchHijackForUnet:
+ """
+ This is torch, but with cat that resizes tensors to appropriate dimensions if they do not match;
+ this makes it possible to create pictures with dimensions that are multiples of 8 rather than 64
+ """
+
+ def __getattr__(self, item):
+ if item == 'cat':
+ return self.cat
+
+ if hasattr(torch, item):
+ return getattr(torch, item)
+
+ raise AttributeError("'{}' object has no attribute '{}'".format(type(self).__name__, item))
+
+ def cat(self, tensors, *args, **kwargs):
+ if len(tensors) == 2:
+ a, b = tensors
+ if a.shape[-2:] != b.shape[-2:]:
+ a = torch.nn.functional.interpolate(a, b.shape[-2:], mode="nearest")
+
+ tensors = (a, b)
+
+ return torch.cat(tensors, *args, **kwargs)
+
+
+th = TorchHijackForUnet()