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Make a function get_my_scheduler()

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This commit is contained in:
Yuta Hayashibe
2023-10-29 19:45:44 +09:00
parent 2a23713f71
commit 01e00ac1b0
1 changed files with 56 additions and 42 deletions
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98
library/train_util.py
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@@ -4381,6 +4381,59 @@ SCHEDULER_LINEAR_END = 0.0120
SCHEDULER_TIMESTEPS = 1000
SCHEDLER_SCHEDULE = "scaled_linear"
def get_my_scheduler(
*,
sample_sampler: str,
v_parameterization: bool,
):
sched_init_args = {}
if sample_sampler == "ddim":
scheduler_cls = DDIMScheduler
elif sample_sampler == "ddpm": # ddpmはおかしくなるのでoptionから外してある
scheduler_cls = DDPMScheduler
elif sample_sampler == "pndm":
scheduler_cls = PNDMScheduler
elif sample_sampler == "lms" or sample_sampler == "k_lms":
scheduler_cls = LMSDiscreteScheduler
elif sample_sampler == "euler" or sample_sampler == "k_euler":
scheduler_cls = EulerDiscreteScheduler
elif sample_sampler == "euler_a" or sample_sampler == "k_euler_a":
scheduler_cls = EulerAncestralDiscreteScheduler
elif sample_sampler == "dpmsolver" or sample_sampler == "dpmsolver++":
scheduler_cls = DPMSolverMultistepScheduler
sched_init_args["algorithm_type"] = sample_sampler
elif sample_sampler == "dpmsingle":
scheduler_cls = DPMSolverSinglestepScheduler
elif sample_sampler == "heun":
scheduler_cls = HeunDiscreteScheduler
elif sample_sampler == "dpm_2" or sample_sampler == "k_dpm_2":
scheduler_cls = KDPM2DiscreteScheduler
elif sample_sampler == "dpm_2_a" or sample_sampler == "k_dpm_2_a":
scheduler_cls = KDPM2AncestralDiscreteScheduler
else:
scheduler_cls = DDIMScheduler
if v_parameterization:
sched_init_args["prediction_type"] = "v_prediction"
scheduler = scheduler_cls(
num_train_timesteps=SCHEDULER_TIMESTEPS,
beta_start=SCHEDULER_LINEAR_START,
beta_end=SCHEDULER_LINEAR_END,
beta_schedule=SCHEDLER_SCHEDULE,
**sched_init_args,
)
# clip_sample=Trueにする
if (
hasattr(scheduler.config, "clip_sample")
and scheduler.config.clip_sample is False
):
# print("set clip_sample to True")
scheduler.config.clip_sample = True
return scheduler
def sample_images(*args, **kwargs):
return sample_images_common(StableDiffusionLongPromptWeightingPipeline, *args, **kwargs)
@@ -4438,50 +4491,11 @@ def sample_images_common(
with open(args.sample_prompts, "r", encoding="utf-8") as f:
prompts = json.load(f)
# schedulerを用意する
sched_init_args = {}
if args.sample_sampler == "ddim":
scheduler_cls = DDIMScheduler
elif args.sample_sampler == "ddpm": # ddpmはおかしくなるのでoptionから外してある
scheduler_cls = DDPMScheduler
elif args.sample_sampler == "pndm":
scheduler_cls = PNDMScheduler
elif args.sample_sampler == "lms" or args.sample_sampler == "k_lms":
scheduler_cls = LMSDiscreteScheduler
elif args.sample_sampler == "euler" or args.sample_sampler == "k_euler":
scheduler_cls = EulerDiscreteScheduler
elif args.sample_sampler == "euler_a" or args.sample_sampler == "k_euler_a":
scheduler_cls = EulerAncestralDiscreteScheduler
elif args.sample_sampler == "dpmsolver" or args.sample_sampler == "dpmsolver++":
scheduler_cls = DPMSolverMultistepScheduler
sched_init_args["algorithm_type"] = args.sample_sampler
elif args.sample_sampler == "dpmsingle":
scheduler_cls = DPMSolverSinglestepScheduler
elif args.sample_sampler == "heun":
scheduler_cls = HeunDiscreteScheduler
elif args.sample_sampler == "dpm_2" or args.sample_sampler == "k_dpm_2":
scheduler_cls = KDPM2DiscreteScheduler
elif args.sample_sampler == "dpm_2_a" or args.sample_sampler == "k_dpm_2_a":
scheduler_cls = KDPM2AncestralDiscreteScheduler
else:
scheduler_cls = DDIMScheduler
if args.v_parameterization:
sched_init_args["prediction_type"] = "v_prediction"
scheduler = scheduler_cls(
num_train_timesteps=SCHEDULER_TIMESTEPS,
beta_start=SCHEDULER_LINEAR_START,
beta_end=SCHEDULER_LINEAR_END,
beta_schedule=SCHEDLER_SCHEDULE,
**sched_init_args,
scheduler = get_my_scheduler(
sample_sampler=args.scheduler,
v_parameterization=args.v_parameterization,
)
# clip_sample=Trueにする
if hasattr(scheduler.config, "clip_sample") and scheduler.config.clip_sample is False:
# print("set clip_sample to True")
scheduler.config.clip_sample = True
pipeline = pipe_class(
text_encoder=text_encoder,
vae=vae,