2022-11-20 03:35:26 +00:00
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from torch.utils.checkpoint import checkpoint
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2023-01-18 20:04:24 +00:00
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import ldm.modules.attention
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import ldm.modules.diffusionmodules.openaimodel
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2022-11-20 03:35:26 +00:00
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def BasicTransformerBlock_forward(self, x, context=None):
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return checkpoint(self._forward, x, context)
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2023-01-18 20:04:24 +00:00
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2022-11-20 03:35:26 +00:00
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def AttentionBlock_forward(self, x):
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return checkpoint(self._forward, x)
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2023-01-18 20:04:24 +00:00
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2022-11-20 03:35:26 +00:00
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def ResBlock_forward(self, x, emb):
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2023-01-18 20:04:24 +00:00
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return checkpoint(self._forward, x, emb)
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stored = []
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def add():
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if len(stored) != 0:
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return
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stored.extend([
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ldm.modules.attention.BasicTransformerBlock.forward,
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ldm.modules.diffusionmodules.openaimodel.ResBlock.forward,
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ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward
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])
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ldm.modules.attention.BasicTransformerBlock.forward = BasicTransformerBlock_forward
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ldm.modules.diffusionmodules.openaimodel.ResBlock.forward = ResBlock_forward
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ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward = AttentionBlock_forward
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def remove():
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if len(stored) == 0:
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return
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ldm.modules.attention.BasicTransformerBlock.forward = stored[0]
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ldm.modules.diffusionmodules.openaimodel.ResBlock.forward = stored[1]
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ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward = stored[2]
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stored.clear()
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