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[typo] 'gradient ccumulation' - 'gradient accumulation' #967

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2 changes: 1 addition & 1 deletion train_db.py
Original file line number Diff line number Diff line change
Expand Up @@ -271,7 +271,7 @@ def train(args):
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 ccumulation steps / 勾配を合計するステップ数 = {args.gradient_accumulation_steps}")
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}")

progress_bar = tqdm(range(args.max_train_steps), smoothing=0, disable=not accelerator.is_local_main_process, desc="steps")
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2 changes: 1 addition & 1 deletion train_textual_inversion.py
Original file line number Diff line number Diff line change
Expand Up @@ -490,7 +490,7 @@ def train(self, args):
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 ccumulation steps / 勾配を合計するステップ数 = {args.gradient_accumulation_steps}")
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}")

progress_bar = tqdm(range(args.max_train_steps), smoothing=0, disable=not accelerator.is_local_main_process, desc="steps")
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2 changes: 1 addition & 1 deletion train_textual_inversion_XTI.py
Original file line number Diff line number Diff line change
Expand Up @@ -387,7 +387,7 @@ def train(args):
logger.info(
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}"
)
logger.info(f" gradient ccumulation steps / 勾配を合計するステップ数 = {args.gradient_accumulation_steps}")
logger.info(f" gradient accumulation steps / 勾配を合計するステップ数 = {args.gradient_accumulation_steps}")
logger.info(f" total optimization steps / 学習ステップ数: {args.max_train_steps}")

progress_bar = tqdm(range(args.max_train_steps), smoothing=0, disable=not accelerator.is_local_main_process, desc="steps")
Expand Down