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mask = th.zeros(*x.shape, device=dist_util.dev())
mask = mask.reshape(-1, 7, 3, image_size, image_size) <-- why to reshape to 7???!!!!
x.shape is [batch_size, 3, 256, 256] in my code.
Is that a bug?
In Algorithm 4 in the paper, they described A as an invertible linear transformation, that maps images to the latent space.
I cannot identify any transformation to the latent space.
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Error: RuntimeError: shape '[-1, 7, 3, 256, 256]' is invalid for input of size 6291456
In
consistency_models/cm/karras_diffusion.py
Line 806 in e32b69e
x.shape
is [batch_size, 3, 256, 256] in my code.Is that a bug?
In Algorithm 4 in the paper, they described A as an invertible linear transformation, that maps images to the latent space.
I cannot identify any transformation to the latent space.
Tasks
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