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fix multi gpu

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This commit is contained in:
Isotr0py
2023-03-10 18:45:53 +08:00
parent c4a596df9e
commit 7544b38635
4 changed files with 5 additions and 5 deletions
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2
fine_tune.py
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@@ -178,7 +178,7 @@ def train(args):
print(f"override steps. steps for {args.max_train_epochs} epochs is / 指定エポックまでのステップ数: {args.max_train_steps}")
# lr schedulerを用意する
lr_scheduler = train_util.get_scheduler_fix(args, optimizer)
lr_scheduler = train_util.get_scheduler_fix(args, optimizer, accelerator.num_processes)
# 実験的機能：勾配も含めたfp16学習を行う　モデル全体をfp16にする
if args.full_fp16:

4
library/train_util.py
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@@ -1849,7 +1849,7 @@ def get_optimizer(args, trainable_params):
# This code can be removed when newer diffusers version (v0.12.1 or greater) is tested and implemented to sd-scripts
def get_scheduler_fix(args,optimizer: Optimizer):
def get_scheduler_fix(args,optimizer: Optimizer,num_processes:int):
"""
Unified API to get any scheduler from its name.
Args:
@@ -1873,7 +1873,7 @@ def get_scheduler_fix(args,optimizer: Optimizer):
name = args.lr_scheduler
num_warmup_steps = args.lr_warmup_steps
num_training_steps = args.max_train_steps * args.gradient_accumulation_steps
num_training_steps = args.max_train_steps * num_processes * args.gradient_accumulation_steps
num_cycles = args.lr_scheduler_num_cycles
power = args.lr_scheduler_power

2
train_network.py
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@@ -179,7 +179,7 @@ def train(args):
print(f"override steps. steps for {args.max_train_epochs} epochs is / 指定エポックまでのステップ数: {args.max_train_steps}")
# lr schedulerを用意する
lr_scheduler = train_util.get_scheduler_fix(args, optimizer)
lr_scheduler = train_util.get_scheduler_fix(args, optimizer, accelerator.num_processes)
# 実験的機能：勾配も含めたfp16学習を行う　モデル全体をfp16にする
if args.full_fp16:

2
train_textual_inversion.py
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@@ -235,7 +235,7 @@ def train(args):
print(f"override steps. steps for {args.max_train_epochs} epochs is / 指定エポックまでのステップ数: {args.max_train_steps}")
# lr schedulerを用意する
lr_scheduler = train_util.get_scheduler_fix(args, optimizer)
lr_scheduler = train_util.get_scheduler_fix(args, optimizer, accelerator.num_processes)
# acceleratorがなんかよろしくやってくれるらしい
text_encoder, optimizer, train_dataloader, lr_scheduler = accelerator.prepare(