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fix to show batch size for each dataset refs #637

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Kohya S
2023-07-23 15:39:56 +09:00
parent 7ae0cde754
commit b1e44e96bc
1 changed files with 5 additions and 3 deletions
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8
sdxl_train.py
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@@ -333,15 +333,17 @@ def train(args):
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
# total_batch_size = args.train_batch_size * accelerator.num_processes * args.gradient_accumulation_steps
accelerator.print("running training / 学習開始")
accelerator.print(f" num examples / サンプル数: {train_dataset_group.num_train_images}")
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}"
f" batch size per device / バッチサイズ: {', '.join([str(d.batch_size) for d in train_dataset_group.datasets])}"
)
# 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}")