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tiny fix about badam

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Former-commit-id: 095fab58d3
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hiyouga
2024-06-25 01:54:53 +08:00
parent dafc9268bc
commit a225b5a70c
17 changed files with 31 additions and 102 deletions
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3
src/llamafactory/train/dpo/trainer.py
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@@ -96,7 +96,8 @@ class CustomDPOTrainer(DPOTrainer):
self.save_model(os.path.join(self.args.output_dir, "pissa_init"))
if finetuning_args.use_badam:
from badam import clip_grad_norm_old_version, BAdamCallback
from badam import BAdamCallback, clip_grad_norm_old_version
self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
self.callback_handler.add_callback(BAdamCallback)

3
src/llamafactory/train/kto/trainer.py
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@@ -91,7 +91,8 @@ class CustomKTOTrainer(KTOTrainer):
self.ref_model.eval()
if finetuning_args.use_badam:
from badam import clip_grad_norm_old_version, BAdamCallback
from badam import BAdamCallback, clip_grad_norm_old_version
self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
self.callback_handler.add_callback(BAdamCallback)

3
src/llamafactory/train/ppo/trainer.py
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@@ -166,7 +166,8 @@ class CustomPPOTrainer(PPOTrainer, Trainer):
self.reward_model = self.accelerator.prepare_model(self.reward_model, evaluation_mode=True)
if finetuning_args.use_badam:
from badam import clip_grad_norm_old_version, BAdamCallback
from badam import BAdamCallback, clip_grad_norm_old_version
self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
self.callback_handler.add_callback(BAdamCallback)

3
src/llamafactory/train/pt/trainer.py
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@@ -48,7 +48,8 @@ class CustomTrainer(Trainer):
self.save_model(os.path.join(self.args.output_dir, "pissa_init"))
if finetuning_args.use_badam:
from badam import clip_grad_norm_old_version, BAdamCallback
from badam import BAdamCallback, clip_grad_norm_old_version
self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
self.callback_handler.add_callback(BAdamCallback)

3
src/llamafactory/train/rm/trainer.py
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@@ -72,7 +72,8 @@ class PairwiseTrainer(Trainer):
self.processor = processor
self.can_return_loss = True # override property to return eval_loss
if finetuning_args.use_badam:
from badam import clip_grad_norm_old_version, BAdamCallback
from badam import BAdamCallback, clip_grad_norm_old_version
self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
self.callback_handler.add_callback(BAdamCallback)

3
src/llamafactory/train/sft/trainer.py
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@@ -56,7 +56,8 @@ class CustomSeq2SeqTrainer(Seq2SeqTrainer):
self.save_model(os.path.join(self.args.output_dir, "pissa_init"))
if finetuning_args.use_badam:
from badam import clip_grad_norm_old_version, BAdamCallback
from badam import BAdamCallback, clip_grad_norm_old_version
self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
self.callback_handler.add_callback(BAdamCallback)

7
src/llamafactory/train/trainer_utils.py
View File

@@ -23,6 +23,7 @@ from typing import TYPE_CHECKING, Callable, Dict, List, Optional, Tuple, Union
import torch
from peft import PeftModel
from transformers import Trainer
from transformers.integrations import is_deepspeed_zero3_enabled
from transformers.optimization import get_scheduler
from transformers.pytorch_utils import ALL_LAYERNORM_LAYERS
from transformers.trainer_pt_utils import get_parameter_names
@@ -372,9 +373,6 @@ def _create_badam_optimizer(
dict(params=decay_params, weight_decay=training_args.weight_decay),
]
from transformers.integrations import is_deepspeed_zero3_enabled
ds_zero3_enabled = is_deepspeed_zero3_enabled()
if finetuning_args.badam_mode == "layer":
from badam import BlockOptimizer
@@ -387,7 +385,7 @@ def _create_badam_optimizer(
start_block=finetuning_args.badam_start_block,
switch_mode=finetuning_args.badam_switch_mode,
verbose=finetuning_args.badam_verbose,
ds_zero3_enabled=ds_zero3_enabled
ds_zero3_enabled=is_deepspeed_zero3_enabled(),
)
logger.info(
f"Using BAdam optimizer with layer-wise update, switch mode is {finetuning_args.badam_switch_mode}, "
@@ -398,7 +396,6 @@ def _create_badam_optimizer(
elif finetuning_args.badam_mode == "ratio":
from badam import BlockOptimizerRatio
assert not ds_zero3_enabled, "BAdam with ratio-based update does not support Deepspeed ZeRO-3 yet, use layer-wise update instead: --badam_mode layer."
assert finetuning_args.badam_update_ratio > 1e-6
optimizer = BlockOptimizerRatio(
param_groups=param_groups,