The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
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""" Layer/Module Helpers
Hacked together by / Copyright 2020 Ross Wightman
"""
import collections.abc
from itertools import repeat
# From PyTorch internals
def _ntuple(n):
def parse(x):
if isinstance(x, collections.abc.Iterable) and not isinstance(x, str):
return x
return tuple(repeat(x, n))
return parse
to_1tuple = _ntuple(1)
to_2tuple = _ntuple(2)
to_3tuple = _ntuple(3)
to_4tuple = _ntuple(4)
to_ntuple = _ntuple
def make_divisible(v, divisor=8, min_value=None, round_limit=0.9):
min_value = min_value or divisor
new_v = max(min_value, int(v + divisor / 2) // divisor * divisor)
# Make sure that round down does not go down by more than 10%.
if new_v < round_limit * v:
new_v += divisor
return new_v