VictorMylle/Kohya-ss-sd-scripts
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Kohya S
2023-02-03 21:04:03 +09:00
parent 93134cdd15
commit 58a809eaff
2 changed files with 52 additions and 52 deletions
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12
gen_img_diffusers.py
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@@ -1845,12 +1845,12 @@ def main(args):
text_encoder, vae, unet = model_util.load_models_from_stable_diffusion_checkpoint(args.v2, args.ckpt) text_encoder, vae, unet = model_util.load_models_from_stable_diffusion_checkpoint(args.v2, args.ckpt)
else: else:
print("load Diffusers pretrained models") print("load Diffusers pretrained models")
pipe = StableDiffusionPipeline.from_pretrained(args.ckpt, safety_checker=None, torch_dtype=dtype) loading_pipe = StableDiffusionPipeline.from_pretrained(args.ckpt, safety_checker=None, torch_dtype=dtype)
text_encoder = pipe.text_encoder text_encoder = loading_pipe.text_encoder
vae = pipe.vae vae = loading_pipe.vae
unet = pipe.unet unet = loading_pipe.unet
tokenizer = pipe.tokenizer tokenizer = loading_pipe.tokenizer
del pipe del loading_pipe
# VAEを読み込む # VAEを読み込む
if args.vae is not None: if args.vae is not None:

8
train_network.py
View File

@@ -1,3 +1,6 @@
from diffusers.optimization import SchedulerType, TYPE_TO_SCHEDULER_FUNCTION
from torch.optim import Optimizer
from typing import Optional, Union
import importlib import importlib
import argparse import argparse
import gc import gc
@@ -40,9 +43,6 @@ def generate_step_logs(args: argparse.Namespace, current_loss, avr_loss, lr_sche
# Which is a newer release of diffusers than currently packaged with sd-scripts # Which is a newer release of diffusers than currently packaged with sd-scripts
# This code can be removed when newer diffusers version (v0.12.1 or greater) is tested and implemented to sd-scripts # This code can be removed when newer diffusers version (v0.12.1 or greater) is tested and implemented to sd-scripts
from typing import Optional, Union
from torch.optim import Optimizer
from diffusers.optimization import SchedulerType, TYPE_TO_SCHEDULER_FUNCTION
def get_scheduler_fix( def get_scheduler_fix(
name: Union[str, SchedulerType], name: Union[str, SchedulerType],
@@ -135,7 +135,7 @@ def train(args):
train_util.debug_dataset(train_dataset) train_util.debug_dataset(train_dataset)
return return
if len(train_dataset) == 0: if len(train_dataset) == 0:
print("No data found. Please verify arguments / 画像がありません。引数指定を確認してください") print("No data found. Please verify arguments (train_data_dir must be the parent of folders with images) / 画像がありません。引数指定を確認してください（train_data_dirには画像があるフォルダではなく、画像があるフォルダの親フォルダを指定する必要があります）")
return return
# acceleratorを準備する # acceleratorを準備する