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work around an apparent MPS torch bug that causes conditioning to have no effect

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Damian Stewart 2022-11-30 22:05:11 +01:00 committed by Kevin Turner
parent e9a0f07033
commit adaa1c7c3e
1 changed files with 5 additions and 2 deletions
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ldm/models/diffusion/shared_invokeai_diffusion.py
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@ -102,8 +102,11 @@ class InvokeAIDiffuserComponent:
x_twice = torch.cat([x] * 2) x_twice = torch.cat([x] * 2)
sigma_twice = torch.cat([sigma] * 2) sigma_twice = torch.cat([sigma] * 2)
both_conditionings = torch.cat([unconditioning, conditioning]) both_conditionings = torch.cat([unconditioning, conditioning])
unconditioned_next_x, conditioned_next_x = self.model_forward_callback(x_twice, sigma_twice, both_results = self.model_forward_callback(x_twice, sigma_twice, both_conditionings)
both_conditionings).chunk(2) unconditioned_next_x, conditioned_next_x = both_results.chunk(2)
if conditioned_next_x.device.type == 'mps':
# prevent a result filled with zeros. seems to be a torch bug.
conditioned_next_x = conditioned_next_x.clone()
return unconditioned_next_x, conditioned_next_x return unconditioned_next_x, conditioned_next_x