VictorMylle/Kohya-ss-sd-scripts
1
0
Fork 1
mirror of https://github.com/kohya-ss/sd-scripts.git synced 2026-04-06 13:47:06 +00:00
Code Issues Packages Projects Releases Wiki Activity

passing filtered hyperparameters to accelerate

Browse Source
This commit is contained in:
Maatra
2024-04-20 14:11:43 +01:00
parent 71e2c91330
commit 2c9db5d9f2
10 changed files with 23 additions and 9 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
fine_tune.py
View File

@@ -310,7 +310,7 @@ def train(args):
init_kwargs["wandb"] = {"name": args.wandb_run_name}
if args.log_tracker_config is not None:
init_kwargs = toml.load(args.log_tracker_config)
accelerator.init_trackers("finetuning" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs)
accelerator.init_trackers("finetuning" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs)
# For --sample_at_first
train_util.sample_images(accelerator, args, 0, global_step, accelerator.device, vae, tokenizer, text_encoder, unet)

14
library/train_util.py
View File

@@ -3378,6 +3378,20 @@ def add_masked_loss_arguments(parser: argparse.ArgumentParser):
help="apply mask for calculating loss. conditioning_data_dir is required for dataset. / 損失計算時にマスクを適用する。datasetにはconditioning_data_dirが必要",
)
def filter_sensitive_args(args: argparse.Namespace):
sensitive_args = ["wandb_api_key", "huggingface_token"]
sensitive_path_args = [
"pretrained_model_name_or_path",
"vae",
"tokenizer_cache_dir",
"train_data_dir",
"conditioning_data_dir",
"reg_data_dir",
"output_dir",
"logging_dir",
]
filtered_args = {k: v for k, v in vars(args).items() if k not in sensitive_args + sensitive_path_args}
return filtered_args
# verify command line args for training
def verify_command_line_training_args(args: argparse.Namespace):

2
sdxl_train.py
View File

@@ -487,7 +487,7 @@ def train(args):
init_kwargs["wandb"] = {"name": args.wandb_run_name}
if args.log_tracker_config is not None:
init_kwargs = toml.load(args.log_tracker_config)
accelerator.init_trackers("finetuning" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs)
accelerator.init_trackers("finetuning" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs)
# For --sample_at_first
sdxl_train_util.sample_images(

2
sdxl_train_control_net_lllite.py
View File

@@ -353,7 +353,7 @@ def train(args):
if args.log_tracker_config is not None:
init_kwargs = toml.load(args.log_tracker_config)
accelerator.init_trackers(
"lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
"lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs
)
loss_recorder = train_util.LossRecorder()

2
sdxl_train_control_net_lllite_old.py
View File

@@ -324,7 +324,7 @@ def train(args):
if args.log_tracker_config is not None:
init_kwargs = toml.load(args.log_tracker_config)
accelerator.init_trackers(
"lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
"lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs
)
loss_recorder = train_util.LossRecorder()

2
train_controlnet.py
View File

@@ -344,7 +344,7 @@ def train(args):
if args.log_tracker_config is not None:
init_kwargs = toml.load(args.log_tracker_config)
accelerator.init_trackers(
"controlnet_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
"controlnet_train" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs
)
loss_recorder = train_util.LossRecorder()

2
train_db.py
View File

@@ -290,7 +290,7 @@ def train(args):
init_kwargs["wandb"] = {"name": args.wandb_run_name}
if args.log_tracker_config is not None:
init_kwargs = toml.load(args.log_tracker_config)
accelerator.init_trackers("dreambooth" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs)
accelerator.init_trackers("dreambooth" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs)
# For --sample_at_first
train_util.sample_images(accelerator, args, 0, global_step, accelerator.device, vae, tokenizer, text_encoder, unet)

2
train_network.py
View File

@@ -753,7 +753,7 @@ class NetworkTrainer:
if args.log_tracker_config is not None:
init_kwargs = toml.load(args.log_tracker_config)
accelerator.init_trackers(
"network_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
"network_train" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs
)
loss_recorder = train_util.LossRecorder()

2
train_textual_inversion.py
View File

@@ -510,7 +510,7 @@ class TextualInversionTrainer:
if args.log_tracker_config is not None:
init_kwargs = toml.load(args.log_tracker_config)
accelerator.init_trackers(
"textual_inversion" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
"textual_inversion" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs
)
# function for saving/removing

2
train_textual_inversion_XTI.py
View File

@@ -407,7 +407,7 @@ def train(args):
if args.log_tracker_config is not None:
init_kwargs = toml.load(args.log_tracker_config)
accelerator.init_trackers(
"textual_inversion" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
"textual_inversion" if args.log_tracker_name is None else args.log_tracker_name, config=train_util.filter_sensitive_args(args), init_kwargs=init_kwargs
)
# function for saving/removing