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[fix]fix deepspeed initialization issue in finetune examples

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This commit is contained in:
luwen.miao 2024-11-18 09:49:31 +00:00
parent 2fdc59c3ce
commit ac2f2c78f7
2 changed files with 6 additions and 8 deletions
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7
finetune/train_cogvideox_image_to_video_lora.py
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@ -1242,11 +1242,11 @@ def main(args):
use_deepspeed_optimizer = (
accelerator.state.deepspeed_plugin is not None
and "optimizer" in accelerator.state.deepspeed_plugin.deepspeed_config
and accelerator.state.deepspeed_plugin.deepspeed_config.get("optimizer", "none").lower() == "none"
)
use_deepspeed_scheduler = (
accelerator.state.deepspeed_plugin is not None
and "scheduler" not in accelerator.state.deepspeed_plugin.deepspeed_config
and accelerator.state.deepspeed_plugin.deepspeed_config.get("scheduler", "none").lower() == "none"
)
optimizer = get_optimizer(args, params_to_optimize, use_deepspeed=use_deepspeed_optimizer)
@ -1357,10 +1357,9 @@ def main(args):
from accelerate.utils import DummyScheduler
lr_scheduler = DummyScheduler(
name=args.lr_scheduler,
optimizer=optimizer,
total_num_steps=args.max_train_steps * accelerator.num_processes,
num_warmup_steps=args.lr_warmup_steps * accelerator.num_processes,
warmup_num_steps=args.lr_warmup_steps * accelerator.num_processes,
)
else:
lr_scheduler = get_scheduler(

7
finetune/train_cogvideox_lora.py
View File

@ -1154,11 +1154,11 @@ def main(args):
use_deepspeed_optimizer = (
accelerator.state.deepspeed_plugin is not None
and "optimizer" in accelerator.state.deepspeed_plugin.deepspeed_config
and accelerator.state.deepspeed_plugin.deepspeed_config.get("optimizer", "none").lower() == "none"
)
use_deepspeed_scheduler = (
accelerator.state.deepspeed_plugin is not None
and "scheduler" not in accelerator.state.deepspeed_plugin.deepspeed_config
and accelerator.state.deepspeed_plugin.deepspeed_config.get("scheduler", "none").lower() == "none"
)
optimizer = get_optimizer(args, params_to_optimize, use_deepspeed=use_deepspeed_optimizer)
@ -1219,10 +1219,9 @@ def main(args):
from accelerate.utils import DummyScheduler
lr_scheduler = DummyScheduler(
name=args.lr_scheduler,
optimizer=optimizer,
total_num_steps=args.max_train_steps * accelerator.num_processes,
num_warmup_steps=args.lr_warmup_steps * accelerator.num_processes,
warmup_num_steps=args.lr_warmup_steps * accelerator.num_processes,
)
else:
lr_scheduler = get_scheduler(