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Fix learning rate schedulers not correctly calculating the number of total training steps #7

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Fix learning rate schedulers not correctly calculating the number of total training steps #7

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16 changes: 8 additions & 8 deletions sdxl_train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -569,14 +569,6 @@ def fn_recursive_set_mem_eff(module: torch.nn.Module):
_, _, optimizer = train_util.get_optimizer(args, trainable_params=params_to_optimize)


# lr schedulerを用意する
if args.fused_optimizer_groups:
# prepare lr schedulers for each optimizer
lr_schedulers = [train_util.get_scheduler_fix(args, optimizer, accelerator.num_processes) for optimizer in optimizers]
lr_scheduler = lr_schedulers[0] # avoid error in the following code
else:
lr_scheduler = train_util.get_scheduler_fix(args, optimizer, accelerator.num_processes)

# 実験的機能：勾配も含めたfp16/bf16学習を行う　モデル全体をfp16/bf16にする
if args.full_fp16:
assert (
Expand Down Expand Up @@ -657,6 +649,14 @@ def fn_recursive_set_mem_eff(module: torch.nn.Module):
# データセット側にも学習ステップを送信
train_dataset_group.set_max_train_steps(args.max_train_steps)

# lr schedulerを用意する
if args.fused_optimizer_groups:
# prepare lr schedulers for each optimizer
lr_schedulers = [train_util.get_scheduler_fix(args, optimizer, accelerator.num_processes) for optimizer in optimizers]
lr_scheduler = lr_schedulers[0] # avoid error in the following code
else:
lr_scheduler = train_util.get_scheduler_fix(args, optimizer, accelerator.num_processes)

if args.deepspeed:
ds_model = deepspeed_utils.prepare_deepspeed_model(
args,
Expand Down