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ColossalAI/examples/images/diffusion/ldm/models/diffusion/sampling_util.py
Hongxin Liu 079bf3cb26 [misc] update pre-commit and run all files (#4752)
* [misc] update pre-commit

* [misc] run pre-commit

* [misc] remove useless configuration files

* [misc] ignore cuda for clang-format
2023-09-19 14:20:26 +08:00

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Python

def append_dims(x, target_dims):
"""Appends dimensions to the end of a tensor until it has target_dims dimensions.
From https://github.com/crowsonkb/k-diffusion/blob/master/k_diffusion/utils.py"""
dims_to_append = target_dims - x.ndim
if dims_to_append < 0:
raise ValueError(f"input has {x.ndim} dims but target_dims is {target_dims}, which is less")
return x[(...,) + (None,) * dims_to_append]
def norm_thresholding(x0, value):
s = append_dims(x0.pow(2).flatten(1).mean(1).sqrt().clamp(min=value), x0.ndim)
return x0 * (value / s)
def spatial_norm_thresholding(x0, value):
# b c h w
s = x0.pow(2).mean(1, keepdim=True).sqrt().clamp(min=value)
return x0 * (value / s)