File size: 911 Bytes
7eb3676 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 |
import torch
import comfy.ops
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_h = (patch_size[0] - img.shape[-2] % patch_size[0]) % patch_size[0]
pad_w = (patch_size[1] - img.shape[-1] % patch_size[1]) % patch_size[1]
return torch.nn.functional.pad(img, (0, pad_w, 0, pad_h), mode=padding_mode)
try:
rms_norm_torch = torch.nn.functional.rms_norm
except:
rms_norm_torch = None
def rms_norm(x, weight, eps=1e-6):
if rms_norm_torch is not None:
return rms_norm_torch(x, weight.shape, weight=comfy.ops.cast_to(weight, dtype=x.dtype, device=x.device), eps=eps)
else:
rrms = torch.rsqrt(torch.mean(x**2, dim=-1, keepdim=True) + eps)
return (x * rrms) * comfy.ops.cast_to(weight, dtype=x.dtype, device=x.device)
|