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Add save_n_epoch_ratio

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forestsource
2023-01-22 02:57:12 +09:00
parent cae42728ab
commit 5e817e4343
4 changed files with 8 additions and 0 deletions
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2
fine_tune.py
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@@ -200,6 +200,8 @@ def train(args):
# epoch数を計算する
num_update_steps_per_epoch = math.ceil(len(train_dataloader) / args.gradient_accumulation_steps)
num_train_epochs = math.ceil(args.max_train_steps / num_update_steps_per_epoch)
if (args.save_n_epoch_ratio is not None) and (args.save_n_epoch_ratio > 0):
args.save_every_n_epochs = math.floor(num_train_epochs / args.save_n_epoch_ratio) or 1
# 学習する
total_batch_size = args.train_batch_size * accelerator.num_processes * args.gradient_accumulation_steps

2
library/train_util.py
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@@ -1028,6 +1028,8 @@ def add_training_arguments(parser: argparse.ArgumentParser, support_dreambooth:
choices=[None, "float", "fp16", "bf16"], help="precision in saving / 保存時に精度を変更して保存する")
parser.add_argument("--save_every_n_epochs", type=int, default=None,
help="save checkpoint every N epochs / 学習中のモデルを指定エポックごとに保存する")
parser.add_argument("--save_n_epoch_ratio", type=int, default=None,
help="save checkpoint N epoch ratio / 学習中のモデルを指定のエポック割合で保存する")
parser.add_argument("--save_last_n_epochs", type=int, default=None, help="save last N checkpoints / 最大Nエポック保存する")
parser.add_argument("--save_last_n_epochs_state", type=int, default=None, help="save last N checkpoints of state (overrides the value of --save_last_n_epochs)/ 最大Nエポックstateを保存する(--save_last_n_epochsの指定を上書きします)")
parser.add_argument("--save_state", action="store_true",

2
train_db.py
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@@ -176,6 +176,8 @@ def train(args):
# epoch数を計算する
num_update_steps_per_epoch = math.ceil(len(train_dataloader) / args.gradient_accumulation_steps)
num_train_epochs = math.ceil(args.max_train_steps / num_update_steps_per_epoch)
if (args.save_n_epoch_ratio is not None) and (args.save_n_epoch_ratio > 0):
args.save_every_n_epochs = math.floor(num_train_epochs / args.save_n_epoch_ratio) or 1
# 学習する
total_batch_size = args.train_batch_size * accelerator.num_processes * args.gradient_accumulation_steps

2
train_network.py
View File

@@ -192,6 +192,8 @@ def train(args):
# epoch数を計算する
num_update_steps_per_epoch = math.ceil(len(train_dataloader) / args.gradient_accumulation_steps)
num_train_epochs = math.ceil(args.max_train_steps / num_update_steps_per_epoch)
if (args.save_n_epoch_ratio is not None) and (args.save_n_epoch_ratio > 0):
args.save_every_n_epochs = math.floor(num_train_epochs / args.save_n_epoch_ratio) or 1
# 学習する
total_batch_size = args.train_batch_size * accelerator.num_processes * args.gradient_accumulation_steps