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fix training scripts except controlnet not working

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Kohya S
2023-06-22 08:46:53 +09:00
parent 1c09867b3e
commit 5114e8daf1
7 changed files with 14 additions and 9 deletions
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10
fine_tune.py
View File

@@ -42,7 +42,7 @@ def train(args):
# データセットを準備する
if args.dataset_class is None:
blueprint_generator = BlueprintGenerator(ConfigSanitizer(False, True, True))
blueprint_generator = BlueprintGenerator(ConfigSanitizer(False, True, False, True))
if args.dataset_config is not None:
print(f"Load dataset config from {args.dataset_config}")
user_config = config_util.load_user_config(args.dataset_config)
@@ -260,7 +260,9 @@ def train(args):
accelerator.print(f" num batches per epoch / 1epochのバッチ数: {len(train_dataloader)}")
accelerator.print(f" num epochs / epoch数: {num_train_epochs}")
accelerator.print(f" batch size per device / バッチサイズ: {args.train_batch_size}")
accelerator.print(f" total train batch size (with parallel & distributed & accumulation) / 総バッチサイズ（並列学習、勾配合計含む）: {total_batch_size}")
accelerator.print(
f" total train batch size (with parallel & distributed & accumulation) / 総バッチサイズ（並列学習、勾配合計含む）: {total_batch_size}"
)
accelerator.print(f" gradient accumulation steps / 勾配を合計するステップ数 = {args.gradient_accumulation_steps}")
accelerator.print(f" total optimization steps / 学習ステップ数: {args.max_train_steps}")
@@ -395,7 +397,9 @@ def train(args):
current_loss = loss.detach().item() # 平均なのでbatch sizeは関係ないはず
if args.logging_dir is not None:
logs = {"loss": current_loss, "lr": float(lr_scheduler.get_last_lr()[0])}
if args.optimizer_type.lower().startswith("DAdapt".lower()) or args.optimizer_type.lower() == "Prodigy": # tracking d*lr value
if (
args.optimizer_type.lower().startswith("DAdapt".lower()) or args.optimizer_type.lower() == "Prodigy"
): # tracking d*lr value
logs["lr/d*lr"] = (
lr_scheduler.optimizers[0].param_groups[0]["d"] * lr_scheduler.optimizers[0].param_groups[0]["lr"]
)

3
library/config_util.py
View File

@@ -584,6 +584,7 @@ if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--support_dreambooth", action="store_true")
parser.add_argument("--support_finetuning", action="store_true")
parser.add_argument("--support_controlnet", action="store_true")
parser.add_argument("--support_dropout", action="store_true")
parser.add_argument("dataset_config")
config_args, remain = parser.parse_known_args()
@@ -602,7 +603,7 @@ if __name__ == "__main__":
print("\n[user_config]")
print(user_config)
sanitizer = ConfigSanitizer(config_args.support_dreambooth, config_args.support_finetuning, config_args.support_dropout)
sanitizer = ConfigSanitizer(config_args.support_dreambooth, config_args.support_finetuning, config_args.support_controlnet, config_args.support_dropout)
sanitized_user_config = sanitizer.sanitize_user_config(user_config)
print("\n[sanitized_user_config]")

2
requirements.txt
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@@ -14,7 +14,7 @@ altair==4.2.2
easygui==0.98.3
toml==0.10.2
voluptuous==0.13.1
huggingface-hub==0.13.3
huggingface-hub==0.14.1
# for BLIP captioning
# requests==2.28.2
# timm==0.6.12

2
train_db.py
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@@ -45,7 +45,7 @@ def train(args):
# データセットを準備する
if args.dataset_class is None:
blueprint_generator = BlueprintGenerator(ConfigSanitizer(True, False, True))
blueprint_generator = BlueprintGenerator(ConfigSanitizer(True, False, False, True))
if args.dataset_config is not None:
print(f"Load dataset config from {args.dataset_config}")
user_config = config_util.load_user_config(args.dataset_config)

2
train_network.py
View File

@@ -92,7 +92,7 @@ def train(args):
# データセットを準備する
if args.dataset_class is None:
blueprint_generator = BlueprintGenerator(ConfigSanitizer(True, True, True))
blueprint_generator = BlueprintGenerator(ConfigSanitizer(True, True, False, True))
if use_user_config:
print(f"Loading dataset config from {args.dataset_config}")
user_config = config_util.load_user_config(args.dataset_config)

2
train_textual_inversion.py
View File

@@ -151,7 +151,7 @@ def train(args):
# データセットを準備する
if args.dataset_class is None:
blueprint_generator = BlueprintGenerator(ConfigSanitizer(True, True, False))
blueprint_generator = BlueprintGenerator(ConfigSanitizer(True, True, False, False))
if args.dataset_config is not None:
accelerator.print(f"Load dataset config from {args.dataset_config}")
user_config = config_util.load_user_config(args.dataset_config)

2
train_textual_inversion_XTI.py
View File

@@ -189,7 +189,7 @@ def train(args):
print(f"create embeddings for {args.num_vectors_per_token} tokens, for {args.token_string}")
# データセットを準備する
blueprint_generator = BlueprintGenerator(ConfigSanitizer(True, True, False))
blueprint_generator = BlueprintGenerator(ConfigSanitizer(True, True, False, False))
if args.dataset_config is not None:
print(f"Load dataset config from {args.dataset_config}")
user_config = config_util.load_user_config(args.dataset_config)