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import torch

import comfy.rmsnorm

def pad_to_patch_size(img, patch_size=(2, 2), padding_mode="circular"):

if padding_mode == "circular" and (torch.jit.is_tracing() or torch.jit.is_scripting()):

padding_mode = "reflect"

pad = ()

for i in range(img.ndim - 2):

pad = (0, (patch_size[i] - img.shape[i + 2] % patch_size[i]) % patch_size[i]) + pad

return torch.nn.functional.pad(img, pad, mode=padding_mode)

rms_norm = comfy.rmsnorm.rms_norm