VictorMylle/Kohya-ss-sd-scripts
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yushan777
2023-09-24 15:24:29 +01:00
parent a2c0f3644b
commit 51e1b45abd
8 changed files with 8 additions and 23 deletions
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4
sdxl_train.py
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@@ -593,9 +593,7 @@ def train(args):
) )
# 指定ステップごとにモデルを保存 # 指定ステップごとにモデルを保存
if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and \ if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and global_step >= args.save_every_n_steps_after_x:
args.save_every_n_steps_after_x is not None and global_step >= args.save_every_n_steps_after_x:
accelerator.wait_for_everyone() accelerator.wait_for_everyone()
if accelerator.is_main_process: if accelerator.is_main_process:
src_path = src_stable_diffusion_ckpt if save_stable_diffusion_format else src_diffusers_model_path src_path = src_stable_diffusion_ckpt if save_stable_diffusion_format else src_diffusers_model_path

4
sdxl_train_control_net_lllite.py
View File

@@ -485,9 +485,7 @@ def train(args):
# sdxl_train_util.sample_images(accelerator, args, None, global_step, accelerator.device, vae, tokenizer, text_encoder, unet) # sdxl_train_util.sample_images(accelerator, args, None, global_step, accelerator.device, vae, tokenizer, text_encoder, unet)
# 指定ステップごとにモデルを保存 # 指定ステップごとにモデルを保存
if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and \ if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and global_step >= args.save_every_n_steps_after_x:
args.save_every_n_steps_after_x is not None and global_step >= args.save_every_n_steps_after_x:
accelerator.wait_for_everyone() accelerator.wait_for_everyone()
if accelerator.is_main_process: if accelerator.is_main_process:
ckpt_name = train_util.get_step_ckpt_name(args, "." + args.save_model_as, global_step) ckpt_name = train_util.get_step_ckpt_name(args, "." + args.save_model_as, global_step)

4
sdxl_train_control_net_lllite_old.py
View File

@@ -455,9 +455,7 @@ def train(args):
# sdxl_train_util.sample_images(accelerator, args, None, global_step, accelerator.device, vae, tokenizer, text_encoder, unet) # sdxl_train_util.sample_images(accelerator, args, None, global_step, accelerator.device, vae, tokenizer, text_encoder, unet)
# 指定ステップごとにモデルを保存 # 指定ステップごとにモデルを保存
if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and \ if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and global_step >= args.save_every_n_steps_after_x:
args.save_every_n_steps_after_x is not None and global_step >= args.save_every_n_steps_after_x:
accelerator.wait_for_everyone() accelerator.wait_for_everyone()
if accelerator.is_main_process: if accelerator.is_main_process:
ckpt_name = train_util.get_step_ckpt_name(args, "." + args.save_model_as, global_step) ckpt_name = train_util.get_step_ckpt_name(args, "." + args.save_model_as, global_step)

4
train_controlnet.py
View File

@@ -482,9 +482,7 @@ def train(args):
) )
# 指定ステップごとにモデルを保存 # 指定ステップごとにモデルを保存
if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and \ if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and global_step >= args.save_every_n_steps_after_x:
args.save_every_n_steps_after_x is not None and global_step >= args.save_every_n_steps_after_x:
accelerator.wait_for_everyone() accelerator.wait_for_everyone()
if accelerator.is_main_process: if accelerator.is_main_process:
ckpt_name = train_util.get_step_ckpt_name(args, "." + args.save_model_as, global_step) ckpt_name = train_util.get_step_ckpt_name(args, "." + args.save_model_as, global_step)

4
train_db.py
View File

@@ -361,9 +361,7 @@ def train(args):
) )
# 指定ステップごとにモデルを保存 # 指定ステップごとにモデルを保存
if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and \ if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and global_step >= args.save_every_n_steps_after_x:
args.save_every_n_steps_after_x is not None and global_step >= args.save_every_n_steps_after_x:
accelerator.wait_for_everyone() accelerator.wait_for_everyone()
if accelerator.is_main_process: if accelerator.is_main_process:
src_path = src_stable_diffusion_ckpt if save_stable_diffusion_format else src_diffusers_model_path src_path = src_stable_diffusion_ckpt if save_stable_diffusion_format else src_diffusers_model_path

3
train_network.py
View File

@@ -828,8 +828,7 @@ class NetworkTrainer:
self.sample_images(accelerator, args, None, global_step, accelerator.device, vae, tokenizer, text_encoder, unet) self.sample_images(accelerator, args, None, global_step, accelerator.device, vae, tokenizer, text_encoder, unet)
# 指定ステップごとにモデルを保存 # 指定ステップごとにモデルを保存
if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and \ if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and global_step >= args.save_every_n_steps_after_x:
args.save_every_n_steps_after_x is not None and global_step >= args.save_every_n_steps_after_x:
accelerator.wait_for_everyone() accelerator.wait_for_everyone()
if accelerator.is_main_process: if accelerator.is_main_process:

4
train_textual_inversion.py
View File

@@ -622,9 +622,7 @@ class TextualInversionTrainer:
) )
# 指定ステップごとにモデルを保存 # 指定ステップごとにモデルを保存
if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and \ if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and global_step >= args.save_every_n_steps_after_x:
args.save_every_n_steps_after_x is not None and global_step >= args.save_every_n_steps_after_x:
accelerator.wait_for_everyone() accelerator.wait_for_everyone()
if accelerator.is_main_process: if accelerator.is_main_process:
updated_embs_list = [] updated_embs_list = []

4
train_textual_inversion_XTI.py
View File

@@ -499,9 +499,7 @@ def train(args):
# ) # )
# 指定ステップごとにモデルを保存 # 指定ステップごとにモデルを保存
if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and \ if args.save_every_n_steps is not None and global_step % args.save_every_n_steps == 0 and global_step >= args.save_every_n_steps_after_x:
args.save_every_n_steps_after_x is not None and global_step >= args.save_every_n_steps_after_x:
accelerator.wait_for_everyone() accelerator.wait_for_everyone()
if accelerator.is_main_process: if accelerator.is_main_process:
updated_embs = ( updated_embs = (