128 lines
4.6 KiB
Python
128 lines
4.6 KiB
Python
import torch
|
|
from comfy import model_management
|
|
import comfy.samplers
|
|
from comfy.samplers import get_area_and_mult, can_concat_cond, cond_cat
|
|
|
|
if not hasattr(comfy.samplers, 'calc_cond_uncond_batch_original'):
|
|
comfy.samplers.calc_cond_uncond_batch_original = comfy.samplers.calc_cond_uncond_batch
|
|
def hook_calc_cond_uncond_batch():
|
|
comfy.samplers.calc_cond_uncond_batch = calc_cond_uncond_batch
|
|
def hook_all():
|
|
hook_calc_cond_uncond_batch()
|
|
|
|
def calc_cond_uncond_batch(model, cond, uncond, x_in, timestep, model_options):
|
|
if 'tiled_diffusion' not in model_options:
|
|
return comfy.samplers.calc_cond_uncond_batch_original(model, cond, uncond, x_in, timestep, model_options)
|
|
out_cond = torch.zeros_like(x_in)
|
|
out_count = torch.ones_like(x_in) * 1e-37
|
|
|
|
out_uncond = torch.zeros_like(x_in)
|
|
out_uncond_count = torch.ones_like(x_in) * 1e-37
|
|
|
|
COND = 0
|
|
UNCOND = 1
|
|
|
|
to_run = []
|
|
for x in cond:
|
|
p = get_area_and_mult(x, x_in, timestep)
|
|
if p is None:
|
|
continue
|
|
|
|
to_run += [(p, COND)]
|
|
if uncond is not None:
|
|
for x in uncond:
|
|
p = get_area_and_mult(x, x_in, timestep)
|
|
if p is None:
|
|
continue
|
|
|
|
to_run += [(p, UNCOND)]
|
|
|
|
while len(to_run) > 0:
|
|
first = to_run[0]
|
|
first_shape = first[0][0].shape
|
|
to_batch_temp = []
|
|
for x in range(len(to_run)):
|
|
if can_concat_cond(to_run[x][0], first[0]):
|
|
to_batch_temp += [x]
|
|
|
|
to_batch_temp.reverse()
|
|
to_batch = to_batch_temp[:1]
|
|
|
|
free_memory = model_management.get_free_memory(x_in.device)
|
|
for i in range(1, len(to_batch_temp) + 1):
|
|
batch_amount = to_batch_temp[:len(to_batch_temp)//i]
|
|
input_shape = [len(batch_amount) * first_shape[0]] + list(first_shape)[1:]
|
|
if model.memory_required(input_shape) < free_memory:
|
|
to_batch = batch_amount
|
|
break
|
|
|
|
input_x = []
|
|
mult = []
|
|
c = []
|
|
cond_or_uncond = []
|
|
area = []
|
|
control = None
|
|
patches = None
|
|
for x in to_batch:
|
|
o = to_run.pop(x)
|
|
p = o[0]
|
|
input_x.append(p.input_x)
|
|
mult.append(p.mult)
|
|
c.append(p.conditioning)
|
|
area.append(p.area)
|
|
cond_or_uncond.append(o[1])
|
|
control = p.control
|
|
patches = p.patches
|
|
|
|
batch_chunks = len(cond_or_uncond)
|
|
input_x = torch.cat(input_x)
|
|
c = cond_cat(c)
|
|
timestep_ = torch.cat([timestep] * batch_chunks)
|
|
|
|
if control is not None:
|
|
if 'tiled_diffusion' in model_options:
|
|
c['control'] = control
|
|
else:
|
|
c['control'] = control.get_control(input_x, timestep_, c, len(cond_or_uncond))
|
|
|
|
transformer_options = {}
|
|
if 'transformer_options' in model_options:
|
|
transformer_options = model_options['transformer_options'].copy()
|
|
|
|
if patches is not None:
|
|
if "patches" in transformer_options:
|
|
cur_patches = transformer_options["patches"].copy()
|
|
for p in patches:
|
|
if p in cur_patches:
|
|
cur_patches[p] = cur_patches[p] + patches[p]
|
|
else:
|
|
cur_patches[p] = patches[p]
|
|
else:
|
|
transformer_options["patches"] = patches
|
|
|
|
transformer_options["cond_or_uncond"] = cond_or_uncond[:]
|
|
transformer_options["sigmas"] = timestep
|
|
|
|
c['transformer_options'] = transformer_options
|
|
|
|
if 'model_function_wrapper' in model_options:
|
|
output = model_options['model_function_wrapper'](model.apply_model, {"input": input_x, "timestep": timestep_, "c": c, "cond_or_uncond": cond_or_uncond}).chunk(batch_chunks)
|
|
else:
|
|
output = model.apply_model(input_x, timestep_, **c).chunk(batch_chunks)
|
|
del input_x
|
|
|
|
for o in range(batch_chunks):
|
|
if cond_or_uncond[o] == COND:
|
|
out_cond[:,:,area[o][2]:area[o][0] + area[o][2],area[o][3]:area[o][1] + area[o][3]] += output[o] * mult[o]
|
|
out_count[:,:,area[o][2]:area[o][0] + area[o][2],area[o][3]:area[o][1] + area[o][3]] += mult[o]
|
|
else:
|
|
out_uncond[:,:,area[o][2]:area[o][0] + area[o][2],area[o][3]:area[o][1] + area[o][3]] += output[o] * mult[o]
|
|
out_uncond_count[:,:,area[o][2]:area[o][0] + area[o][2],area[o][3]:area[o][1] + area[o][3]] += mult[o]
|
|
del mult
|
|
|
|
out_cond /= out_count
|
|
del out_count
|
|
out_uncond /= out_uncond_count
|
|
del out_uncond_count
|
|
return out_cond, out_uncond
|