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It's like bilinear but with slerp.

exponential scheduler is the one recommended with this sampler.

* allow nodes to map over lists

* make work with IS_CHANGED and VALIDATE_INPUTS

* give list outputs distinct socket shape

* add rebatch node

* add batch index logic

* add repeat latent batch

* deal with noise mask edge cases in latentfrombatch

Try batching when cond sizes don't match with smart padding.

More conservative xformers maximum_batch_area.

Remove useless code.

By default, when applying a mask to a condition, the entire image will
still be used for sampling. The new "set_area_to_bounds" option on the
node will allow the user to automatically limit conditioning to the
bounds of the mask.

I've also removed the dependency on torchvision for calculating bounding
boxes. I've taken the opportunity to fix some frustrating details in the
other version:
1. An all-0 mask will no longer cause an error
2. Indices are returned as integers instead of floats so they can be
   used to index into tensors.

Like this for example: --directml 1