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Feat: Enhanced Module Parsing Logic #122

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62 changes: 42 additions & 20 deletions ovis/train/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -91,24 +91,47 @@ def args2dict(args):
elif len(module_name_lr) == 1:
module_name = module_name_lr[0]
else:
raise ValueError
match module_name:
case 'all':
module = model
case 'llm':
module = model.llm
case 'visual_tokenizer':
module = model.visual_tokenizer
case 'visual_tokenizer.head':
module = model.visual_tokenizer.head
case 'visual_tokenizer.vit':
module = model.visual_tokenizer.vit
case 'visual_tokenizer.vit.last_block':
module = model.visual_tokenizer._get_last_block()
case 'vte':
module = model.vte
case _:
raise ValueError(f'Invalid train module name: {module_name}')
raise ValueError(f"Invalid module format: {module_name_lr}")

# 解析模块名称，支持指定LLM的特定层
module_parts = module_name.split('.')
current_module = model

try:
# 逐层查找模块
for part in module_parts:
# 处理数字索引（如layers.31）
if part.isdigit():
part = int(part)
current_module = current_module[part]
else:
current_module = getattr(current_module, part)

module = current_module
rank0_print(f"Selected module: {module_name} (found)")

except AttributeError as e:
# 保留原有匹配模式作为备份
match module_name:
case 'all':
module = model
case 'llm':
module = model.llm
print(module)
case 'visual_tokenizer':
module = model.visual_tokenizer
case 'visual_tokenizer.head':
module = model.visual_tokenizer.head
case 'visual_tokenizer.vit':
module = model.visual_tokenizer.vit
case 'visual_tokenizer.vit.last_block':
module = model.visual_tokenizer._get_last_block()
case 'vte':
module = model.vte
case _:
raise ValueError(f'Invalid train module name: {module_name}, error: {str(e)}')

# 启用该模块的梯度计算
module.requires_grad_(True)
parameters.append({'params': module.parameters(), 'lr': module_lr})

Expand Down Expand Up @@ -152,8 +175,7 @@ def args2dict(args):
trainer = Trainer(
model=model,
args=training_args,
callbacks=[MonitorCallback],
**data_module
callbacks=[MonitorCallback],** data_module
)
rankN_print(BEGIN_LINE)
rankN_print(f'model_accepts_loss_kwargs: {trainer.model_accepts_loss_kwargs}')
Expand Down