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add efficient_unet and update others #11

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@odb9402 odb9402 commented Oct 25, 2023

  • Add EfficientUNet2DConditionModel and related blocks
    • Memory (for forward-backward) efficient UNet for super-resolution tasks, originally proposed by Google (Imagen)
  • Remove type keyword for Linear(*, dtype=) since it raises error for the old version of torch (Linear module does not have dtype kwarg
  • Add encoder_attention_mask to the UNet2DConditionModel and related blocks

  • (MAF specific) bypassing the error in torch.clamp---currently, torch.clamp only allows tensor datatype, not float---with minimum and maximum

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