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fix incorrect loss value for vlms

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Former-commit-id: 30567a1487727473950104718e626ff660f10cbb
This commit is contained in:
hiyouga 2024-10-30 08:56:46 +00:00
parent 1b02915d19
commit 584ce3a105
12 changed files with 48 additions and 22 deletions
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4
requirements.txt
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@ -1,5 +1,5 @@
transformers>=4.41.2,<=4.46.0
datasets>=2.16.0,<=2.21.0
transformers>=4.41.2,<=4.46.1
datasets>=2.16.0,<=3.0.2
accelerate>=0.34.0,<=1.0.1
peft>=0.11.1,<=0.12.0
trl>=0.8.6,<=0.9.6

8
src/llamafactory/__init__.py
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@ -20,17 +20,17 @@ Level:
Dependency graph:
main:
transformers>=4.41.2,<=4.46.0
datasets>=2.16.0,<=2.21.0
transformers>=4.41.2,<=4.46.1
datasets>=2.16.0,<=3.0.2
accelerate>=0.34.0,<=1.0.1
peft>=0.11.1,<=0.12.0
trl>=0.8.6,<=0.9.6
attention:
transformers>=4.42.4 (gemma+fa2)
longlora:
transformers>=4.41.2,<=4.46.0
transformers>=4.41.2,<=4.46.1
packing:
transformers>=4.41.2,<=4.46.0
transformers>=4.41.2,<=4.46.1
Disable version checking: DISABLE_VERSION_CHECK=1
Enable VRAM recording: RECORD_VRAM=1

8
src/llamafactory/extras/misc.py
View File

@ -79,8 +79,8 @@ def check_dependencies() -> None:
if os.environ.get("DISABLE_VERSION_CHECK", "0").lower() in ["true", "1"]:
logger.warning("Version checking has been disabled, may lead to unexpected behaviors.")
else:
require_version("transformers>=4.41.2,<=4.46.0", "To fix: pip install transformers>=4.41.2,<=4.46.0")
require_version("datasets>=2.16.0,<=2.21.0", "To fix: pip install datasets>=2.16.0,<=2.21.0")
require_version("transformers>=4.41.2,<=4.46.1", "To fix: pip install transformers>=4.41.2,<=4.46.1")
require_version("datasets>=2.16.0,<=3.0.2", "To fix: pip install datasets>=2.16.0,<=3.0.2")
require_version("accelerate>=0.34.0,<=1.0.1", "To fix: pip install accelerate>=0.34.0,<=1.0.1")
require_version("peft>=0.11.1,<=0.12.0", "To fix: pip install peft>=0.11.1,<=0.12.0")
require_version("trl>=0.8.6,<=0.9.6", "To fix: pip install trl>=0.8.6,<=0.9.6")
@ -237,7 +237,7 @@ def try_download_model_from_other_hub(model_args: "ModelArguments") -> str:
if use_modelscope():
require_version("modelscope>=1.11.0", "To fix: pip install modelscope>=1.11.0")
from modelscope import snapshot_download
from modelscope import snapshot_download # type: ignore
revision = "master" if model_args.model_revision == "main" else model_args.model_revision
return snapshot_download(
@ -248,7 +248,7 @@ def try_download_model_from_other_hub(model_args: "ModelArguments") -> str:
if use_openmind():
require_version("openmind>=0.8.0", "To fix: pip install openmind>=0.8.0")
from openmind.utils.hub import snapshot_download
from openmind.utils.hub import snapshot_download # type: ignore
return snapshot_download(
model_args.model_name_or_path,

2
src/llamafactory/extras/packages.py
View File

@ -81,7 +81,7 @@ def is_transformers_version_greater_than_4_43():
@lru_cache
def is_transformers_version_equal_to_4_46():
return _get_package_version("transformers") == version.parse("4.46.0")
return version.parse("4.46.0") <= _get_package_version("transformers") <= version.parse("4.46.1")
def is_uvicorn_available():

2
src/llamafactory/model/model_utils/longlora.py
View File

@ -353,7 +353,7 @@ def llama_sdpa_attention_forward(
def _apply_llama_patch() -> None:
require_version("transformers>=4.41.2,<=4.46.0", "To fix: pip install transformers>=4.41.2,<=4.46.0")
require_version("transformers>=4.41.2,<=4.46.1", "To fix: pip install transformers>=4.41.2,<=4.46.1")
LlamaAttention.forward = llama_attention_forward
LlamaFlashAttention2.forward = llama_flash_attention_2_forward
LlamaSdpaAttention.forward = llama_sdpa_attention_forward

2
src/llamafactory/model/model_utils/packing.py
View File

@ -114,7 +114,7 @@ def get_unpad_data(attention_mask: "torch.Tensor") -> Tuple["torch.Tensor", "tor
def _patch_for_block_diag_attn(model_type: str) -> None:
require_version("transformers>=4.41.2,<=4.46.0", "To fix: pip install transformers>=4.41.2,<=4.46.0")
require_version("transformers>=4.41.2,<=4.46.1", "To fix: pip install transformers>=4.41.2,<=4.46.1")
if is_transformers_version_greater_than_4_43():
import transformers.modeling_flash_attention_utils

4
src/llamafactory/train/dpo/trainer.py
View File

@ -101,7 +101,7 @@ class CustomDPOTrainer(DPOTrainer):
self.callback_handler.add_callback(PissaConvertCallback)
if finetuning_args.use_badam:
from badam import BAdamCallback, clip_grad_norm_old_version
from badam import BAdamCallback, clip_grad_norm_old_version # type: ignore
self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
self.add_callback(BAdamCallback)
@ -274,7 +274,7 @@ class CustomDPOTrainer(DPOTrainer):
https://github.com/huggingface/transformers/blob/v4.46.0/src/transformers/trainer.py#L3605
"""
loss = super().compute_loss(model, inputs, return_outputs)
if kwargs.pop("num_items_in_batch", False) and is_transformers_version_equal_to_4_46():
if is_transformers_version_equal_to_4_46() and kwargs.pop("num_items_in_batch", False):
loss /= self.args.gradient_accumulation_steps
return loss

4
src/llamafactory/train/kto/trainer.py
View File

@ -96,7 +96,7 @@ class CustomKTOTrainer(KTOTrainer):
self.add_callback(SaveProcessorCallback(processor))
if finetuning_args.use_badam:
from badam import BAdamCallback, clip_grad_norm_old_version
from badam import BAdamCallback, clip_grad_norm_old_version # type: ignore
self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
self.add_callback(BAdamCallback)
@ -247,7 +247,7 @@ class CustomKTOTrainer(KTOTrainer):
https://github.com/huggingface/transformers/blob/v4.46.0/src/transformers/trainer.py#L3605
"""
loss = super().compute_loss(model, inputs, return_outputs)
if kwargs.pop("num_items_in_batch", False) and is_transformers_version_equal_to_4_46():
if is_transformers_version_equal_to_4_46() and kwargs.pop("num_items_in_batch", False):
loss /= self.args.gradient_accumulation_steps
return loss

2
src/llamafactory/train/ppo/trainer.py
View File

@ -181,7 +181,7 @@ class CustomPPOTrainer(PPOTrainer, Trainer):
self.add_callback(SaveProcessorCallback(processor))
if finetuning_args.use_badam:
from badam import BAdamCallback, clip_grad_norm_old_version
from badam import BAdamCallback, clip_grad_norm_old_version # type: ignore
self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
self.add_callback(BAdamCallback)

15
src/llamafactory/train/pt/trainer.py
View File

@ -19,6 +19,7 @@ from transformers import Trainer
from typing_extensions import override
from ...extras.logging import get_logger
from ...extras.packages import is_transformers_version_equal_to_4_46
from ..callbacks import PissaConvertCallback, SaveProcessorCallback
from ..trainer_utils import create_custom_optimizer, create_custom_scheduler
@ -51,7 +52,7 @@ class CustomTrainer(Trainer):
self.add_callback(PissaConvertCallback)
if finetuning_args.use_badam:
from badam import BAdamCallback, clip_grad_norm_old_version
from badam import BAdamCallback, clip_grad_norm_old_version # type: ignore
self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
self.add_callback(BAdamCallback)
@ -68,3 +69,15 @@ class CustomTrainer(Trainer):
) -> "torch.optim.lr_scheduler.LRScheduler":
create_custom_scheduler(self.args, num_training_steps, optimizer)
return super().create_scheduler(num_training_steps, optimizer)
@override
def compute_loss(self, model, inputs, return_outputs=False, **kwargs):
r"""
Fixes the loss value for transformers 4.46.0.
https://github.com/huggingface/transformers/blob/v4.46.0/src/transformers/trainer.py#L3605
"""
loss = super().compute_loss(model, inputs, return_outputs, **kwargs)
if is_transformers_version_equal_to_4_46() and not getattr(self, "model_accepts_loss_kwargs", False):
loss /= self.args.gradient_accumulation_steps # other model should not scale the loss
return loss

4
src/llamafactory/train/rm/trainer.py
View File

@ -60,7 +60,7 @@ class PairwiseTrainer(Trainer):
self.add_callback(PissaConvertCallback)
if finetuning_args.use_badam:
from badam import BAdamCallback, clip_grad_norm_old_version
from badam import BAdamCallback, clip_grad_norm_old_version # type: ignore
self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
self.add_callback(BAdamCallback)
@ -100,7 +100,7 @@ class PairwiseTrainer(Trainer):
loss = -torch.nn.functional.logsigmoid(chosen_scores.float() - rejected_scores.float()).mean()
if kwargs.pop("num_items_in_batch", False) and is_transformers_version_equal_to_4_46():
if is_transformers_version_equal_to_4_46() and kwargs.pop("num_items_in_batch", False):
loss /= self.args.gradient_accumulation_steps # fixes the loss value for transformers 4.46.0
if return_outputs:

15
src/llamafactory/train/sft/trainer.py
View File

@ -27,6 +27,7 @@ from typing_extensions import override
from ...extras.constants import IGNORE_INDEX
from ...extras.logging import get_logger
from ...extras.packages import is_transformers_version_equal_to_4_46
from ..callbacks import PissaConvertCallback, SaveProcessorCallback
from ..trainer_utils import create_custom_optimizer, create_custom_scheduler
@ -60,7 +61,7 @@ class CustomSeq2SeqTrainer(Seq2SeqTrainer):
self.add_callback(PissaConvertCallback)
if finetuning_args.use_badam:
from badam import BAdamCallback, clip_grad_norm_old_version
from badam import BAdamCallback, clip_grad_norm_old_version # type: ignore
self.accelerator.clip_grad_norm_ = MethodType(clip_grad_norm_old_version, self.accelerator)
self.add_callback(BAdamCallback)
@ -78,6 +79,18 @@ class CustomSeq2SeqTrainer(Seq2SeqTrainer):
create_custom_scheduler(self.args, num_training_steps, optimizer)
return super().create_scheduler(num_training_steps, optimizer)
@override
def compute_loss(self, model, inputs, return_outputs=False, **kwargs):
r"""
Fixes the loss value for transformers 4.46.0.
https://github.com/huggingface/transformers/blob/v4.46.0/src/transformers/trainer.py#L3605
"""
loss = super().compute_loss(model, inputs, return_outputs, **kwargs)
if is_transformers_version_equal_to_4_46() and not getattr(self, "model_accepts_loss_kwargs", False):
loss /= self.args.gradient_accumulation_steps # other model should not scale the loss
return loss
@override
def prediction_step(
self,