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add multiplier, steps range

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Kohya S
2023-08-22 08:17:21 +09:00
parent 9be19ad777
commit 6d5cffaee9
2 changed files with 52 additions and 20 deletions
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48
sdxl_gen_img.py
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@@ -661,21 +661,28 @@ class PipelineLike:
if self.control_nets:
# guided_hints = original_control_net.get_guided_hints(self.control_nets, num_latent_input, batch_size, clip_guide_images)
if self.control_net_enabled:
for control_net in self.control_nets:
for control_net, _ in self.control_nets:
with torch.no_grad():
control_net.set_cond_image(clip_guide_images)
else:
for control_net in self.control_nets:
for control_net, _ in self.control_nets:
control_net.set_cond_image(None)
each_control_net_enabled = [self.control_net_enabled] * len(self.control_nets)
for i, t in enumerate(tqdm(timesteps)):
# expand the latents if we are doing classifier free guidance
latent_model_input = latents.repeat((num_latent_input, 1, 1, 1))
latent_model_input = self.scheduler.scale_model_input(latent_model_input, t)
# # disable control net if ratio is set
# if self.control_nets and self.control_net_enabled:
# pass # TODO
# disable control net if ratio is set
if self.control_nets and self.control_net_enabled:
for j, ((control_net, ratio), enabled) in enumerate(zip(self.control_nets, each_control_net_enabled)):
if not enabled or ratio >= 1.0:
continue
if ratio < i / len(timesteps):
print(f"ControlNet {j} is disabled (ratio={ratio} at {i} / {len(timesteps)})")
control_net.set_cond_image(None)
each_control_net_enabled[j] = False
# predict the noise residual
# TODO Diffusers' ControlNet
@@ -1567,7 +1574,7 @@ def main(args):
upscaler.to(dtype).to(device)
# ControlNetの処理
control_nets: List[ControlNetLLLite] = []
control_nets: List[Tuple[ControlNetLLLite, float]] = []
# if args.control_net_models:
# for i, model in enumerate(args.control_net_models):
# prep_type = None if not args.control_net_preps or len(args.control_net_preps) <= i else args.control_net_preps[i]
@@ -1595,12 +1602,19 @@ def main(args):
break
assert mlp_dim is not None and cond_emb_dim is not None, f"invalid control net: {model_file}"
control_net = ControlNetLLLite(unet, cond_emb_dim, mlp_dim)
multiplier = (
1.0
if not args.control_net_multipliers or len(args.control_net_multipliers) <= i
else args.control_net_multipliers[i]
)
ratio = 1.0 if not args.control_net_ratios or len(args.control_net_ratios) <= i else args.control_net_ratios[i]
control_net = ControlNetLLLite(unet, cond_emb_dim, mlp_dim, multiplier=multiplier)
control_net.apply_to()
control_net.load_state_dict(state_dict)
control_net.to(dtype).to(device)
control_net.set_batch_cond_only(False, False)
control_nets.append(control_net)
control_nets.append((control_net, ratio))
if args.opt_channels_last:
print(f"set optimizing: channels last")
@@ -2623,14 +2637,16 @@ def setup_parser() -> argparse.ArgumentParser:
# parser.add_argument(
# "--control_net_preps", type=str, default=None, nargs="*", help="ControlNet preprocess to use / 使用するControlNetのプリプロセス名"
# )
# parser.add_argument("--control_net_multiplier", type=float, default=None, nargs="*", help="ControlNet multiplier / ControlNetの適用率")
# parser.add_argument(
# "--control_net_ratios",
# type=float,
# default=None,
# nargs="*",
# help="ControlNet guidance ratio for steps / ControlNetでガイドするステップ比率",
# )
parser.add_argument(
"--control_net_multipliers", type=float, default=None, nargs="*", help="ControlNet multiplier / ControlNetの適用率"
)
parser.add_argument(
"--control_net_ratios",
type=float,
default=None,
nargs="*",
help="ControlNet guidance ratio for steps / ControlNetでガイドするステップ比率",
)
# # parser.add_argument(
# "--control_net_image_path", type=str, default=None, nargs="*", help="image for ControlNet guidance / ControlNetでガイドに使う画像"
# )