Pin transformers version <4.47 (#2447)

* pin transformers to <4.47

* update version

CONTRIBUTING.md

@@ -256,3 +256,30 @@ That's how `make test` is implemented (without the `pip install` line)!
 
 You can specify a smaller set of tests to test only the feature
 you're working on.
+
+### Deprecation and Backward Compatibility
+
+Our approach to deprecation and backward compatibility is flexible and based on the feature’s usage and impact. Each deprecation is carefully evaluated, aiming to balance innovation with user needs.
+
+When a feature or component is marked for deprecation, its use will emit a warning message. This warning will include:
+
+- **Transition Guidance**: Instructions on how to migrate to the alternative solution or replacement.
+- **Removal Version**: The target version when the feature will be removed, providing users with a clear timeframe to transition.
+
+Example:
+   
+   ```python
+   warnings.warn(
+       "The `Trainer.foo` method is deprecated and will be removed in version 0.14.0. "
+       "Please use the `Trainer.bar` class instead.",
+       FutureWarning,
+   )
+   ```
+
+The deprecation and removal schedule is based on each feature's usage and impact, with examples at two extremes:
+
+- **Experimental or Low-Use Features**: For a feature that is experimental or has limited usage, backward compatibility may not be maintained between releases. Users should therefore anticipate potential breaking changes from one version to the next.
+
+- **Widely-Used Components**: For a feature with high usage, we aim for a more gradual transition period of approximately **5 months**, generally scheduling deprecation around **5 minor releases** after the initial warning.
+
+These examples represent the two ends of a continuum. The specific timeline for each feature will be determined individually, balancing innovation with user stability needs.

docs/source/judges.mdx

@@ -1,5 +1,11 @@
 # Judges
 
+<Tip warning={true}>
+
+TRL Judges is an experimental API which is subject to change at any time.
+
+</Tip>
+
 TRL provides judges to easily compare two completions.
 
 Make sure to have installed the required dependencies by running:

setup.py

@@ -73,13 +73,13 @@ import os
 from setuptools import find_packages, setup
 
 
-__version__ = "0.12.0.dev0"  # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
+__version__ = "0.12.2"  # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
 
 REQUIRED_PKGS = [
     "accelerate>=0.34.0",
     "datasets>=2.21.0",
     "rich",  # rich shouldn't be a required package for trl, we should remove it from here
-    "transformers>=4.46.0",
+    "transformers<4.47.0",
 ]
 EXTRAS = {
     # Windows support is partially supported with DeepSpeed https://github.com/microsoft/DeepSpeed/tree/master#windows

trl/__init__.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-__version__ = "0.12.0.dev0"
+__version__ = "0.12.2"
 
 from typing import TYPE_CHECKING
 

trl/trainer/bco_trainer.py

@@ -48,6 +48,7 @@ from transformers import (
 from transformers.trainer_callback import TrainerCallback
 from transformers.trainer_utils import EvalLoopOutput, has_length
 from transformers.utils import is_peft_available
+from transformers.utils.deprecation import deprecate_kwarg
 
 from ..data_utils import maybe_apply_chat_template
 from ..models import PreTrainedModelWrapper, create_reference_model
@@ -317,6 +318,7 @@ class BCOTrainer(Trainer):
 
     _tag_names = ["trl", "bco"]
 
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.13.0", raise_if_both_names=True)
     def __init__(
         self,
         model: Union[PreTrainedModel, nn.Module, str] = None,

trl/trainer/cpo_trainer.py

@@ -44,6 +44,7 @@ from transformers import (
 from transformers.trainer_callback import TrainerCallback
 from transformers.trainer_utils import EvalLoopOutput
 from transformers.utils import is_peft_available, is_torch_fx_proxy
+from transformers.utils.deprecation import deprecate_kwarg
 
 from ..data_utils import maybe_apply_chat_template, maybe_extract_prompt
 from .cpo_config import CPOConfig
@@ -103,6 +104,7 @@ class CPOTrainer(Trainer):
 
     _tag_names = ["trl", "cpo"]
 
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.14.0", raise_if_both_names=True)
     def __init__(
         self,
         model: Optional[Union[PreTrainedModel, nn.Module, str]] = None,

trl/trainer/dpo_trainer.py

@@ -213,7 +213,7 @@ class DPOTrainer(Trainer):
         ],
         custom_message="Deprecated positional argument(s) used in DPOTrainer, please use the DPOConfig to set these arguments instead.",
     )
-    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.14.0", raise_if_both_names=True)
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.16.0", raise_if_both_names=True)
     def __init__(
         self,
         model: Optional[Union[PreTrainedModel, nn.Module, str]] = None,

trl/trainer/gkd_trainer.py

@@ -37,6 +37,7 @@ from transformers import (
 from transformers.trainer_callback import TrainerCallback
 from transformers.trainer_utils import EvalPrediction
 from transformers.utils import is_liger_kernel_available, is_peft_available
+from transformers.utils.deprecation import deprecate_kwarg
 
 from ..models import PreTrainedModelWrapper
 from ..models.utils import unwrap_model_for_generation
@@ -61,6 +62,7 @@ if is_wandb_available():
 class GKDTrainer(SFTTrainer):
     _tag_names = ["trl", "gkd"]
 
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.13.0", raise_if_both_names=True)
     def __init__(
         self,
         model: Optional[Union[PreTrainedModel, nn.Module, str]] = None,

trl/trainer/iterative_sft_trainer.py

@@ -33,6 +33,7 @@ from transformers import (
 )
 from transformers.trainer_utils import EvalLoopOutput
 from transformers.utils import is_peft_available
+from transformers.utils.deprecation import deprecate_kwarg
 
 from ..core import PPODecorators
 from .utils import generate_model_card
@@ -80,6 +81,7 @@ class IterativeSFTTrainer(Trainer):
 
     _tag_names = ["trl", "iterative-sft"]
 
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.13.0", raise_if_both_names=True)
     def __init__(
         self,
         model: Optional[PreTrainedModel] = None,

trl/trainer/kto_trainer.py

@@ -47,6 +47,7 @@ from transformers import (
 )
 from transformers.trainer_utils import EvalLoopOutput, has_length
 from transformers.utils import is_peft_available
+from transformers.utils.deprecation import deprecate_kwarg
 
 from ..data_utils import maybe_apply_chat_template, maybe_extract_prompt, maybe_unpair_preference_dataset
 from ..models import PreTrainedModelWrapper, create_reference_model
@@ -312,6 +313,7 @@ class KTOTrainer(Trainer):
 
     _tag_names = ["trl", "kto"]
 
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.14.0", raise_if_both_names=True)
     def __init__(
         self,
         model: Union[PreTrainedModel, nn.Module, str] = None,

trl/trainer/nash_md_trainer.py

@@ -33,6 +33,7 @@ from transformers import (
 from transformers.trainer_utils import EvalPrediction
 from transformers.training_args import OptimizerNames
 from transformers.utils import is_apex_available
+from transformers.utils.deprecation import deprecate_kwarg
 
 from ..data_utils import is_conversational, maybe_apply_chat_template
 from ..models.modeling_base import GeometricMixtureWrapper
@@ -93,6 +94,7 @@ class NashMDTrainer(OnlineDPOTrainer):
 
     _tag_names = ["trl", "nash-md"]
 
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.13.0", raise_if_both_names=True)
     def __init__(
         self,
         model: Union[PreTrainedModel, nn.Module] = None,

trl/trainer/online_dpo_trainer.py

@@ -44,6 +44,7 @@ from transformers import (
 from transformers.trainer_utils import PREFIX_CHECKPOINT_DIR, EvalPrediction, seed_worker
 from transformers.training_args import OptimizerNames
 from transformers.utils import is_peft_available, is_sagemaker_mp_enabled, logging
+from transformers.utils.deprecation import deprecate_kwarg
 
 from ..data_utils import apply_chat_template, is_conversational, maybe_apply_chat_template
 from ..models import create_reference_model
@@ -125,6 +126,7 @@ class OnlineDPOTrainer(Trainer):
 
     _tag_names = ["trl", "online-dpo"]
 
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.14.0", raise_if_both_names=True)
     def __init__(
         self,
         model: Union[PreTrainedModel, nn.Module],

trl/trainer/orpo_trainer.py

@@ -48,6 +48,7 @@ from transformers import (
 from transformers.trainer_callback import TrainerCallback
 from transformers.trainer_utils import EvalLoopOutput
 from transformers.utils import is_peft_available, is_torch_fx_proxy
+from transformers.utils.deprecation import deprecate_kwarg
 
 from ..data_utils import maybe_apply_chat_template, maybe_extract_prompt
 from ..models import PreTrainedModelWrapper
@@ -114,6 +115,7 @@ class ORPOTrainer(Trainer):
 
     _tag_names = ["trl", "orpo"]
 
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.15.0", raise_if_both_names=True)
     def __init__(
         self,
         model: Optional[Union[PreTrainedModel, nn.Module, str]] = None,

trl/trainer/ppo_trainer.py

@@ -44,6 +44,7 @@ from transformers import (
 from transformers.integrations import get_reporting_integration_callbacks
 from transformers.trainer import DEFAULT_CALLBACKS, DEFAULT_PROGRESS_CALLBACK
 from transformers.trainer_callback import CallbackHandler, ExportableState, PrinterCallback
+from transformers.utils.deprecation import deprecate_kwarg
 
 from ..core import masked_mean, masked_whiten
 from ..models.utils import unwrap_model_for_generation
@@ -90,6 +91,7 @@ class PolicyAndValueWrapper(nn.Module):
 class PPOTrainer(Trainer):
     _tag_names = ["trl", "ppo"]
 
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.15.0", raise_if_both_names=True)
     def __init__(
         self,
         config: PPOConfig,

trl/trainer/reward_trainer.py

@@ -39,6 +39,7 @@ from transformers.trainer_callback import TrainerCallback
 from transformers.trainer_pt_utils import nested_detach
 from transformers.trainer_utils import EvalPrediction
 from transformers.utils import is_peft_available
+from transformers.utils.deprecation import deprecate_kwarg
 
 from ..data_utils import maybe_apply_chat_template
 from .reward_config import RewardConfig
@@ -80,6 +81,7 @@ def _tokenize(batch: Dict[str, List[Any]], tokenizer: "PreTrainedTokenizerBase")
 class RewardTrainer(Trainer):
     _tag_names = ["trl", "reward-trainer"]
 
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.15.0", raise_if_both_names=True)
     def __init__(
         self,
         model: Optional[Union[PreTrainedModel, nn.Module]] = None,

trl/trainer/rloo_trainer.py

@@ -44,6 +44,7 @@ from transformers import (
 from transformers.integrations import get_reporting_integration_callbacks
 from transformers.trainer import DEFAULT_CALLBACKS, DEFAULT_PROGRESS_CALLBACK
 from transformers.trainer_callback import CallbackHandler, ExportableState, PrinterCallback
+from transformers.utils.deprecation import deprecate_kwarg
 
 from ..models.utils import unwrap_model_for_generation
 from ..trainer.utils import (
@@ -71,6 +72,7 @@ INVALID_LOGPROB = 1.0
 class RLOOTrainer(Trainer):
     _tag_names = ["trl", "rloo"]
 
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.14.0", raise_if_both_names=True)
     def __init__(
         self,
         config: RLOOConfig,

trl/trainer/sft_trainer.py

@@ -124,7 +124,7 @@ class SFTTrainer(Trainer):
         ],
         custom_message="Deprecated positional argument(s) used in SFTTrainer, please use the SFTConfig to set these arguments instead.",
     )
-    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.14.0", raise_if_both_names=True)
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.16.0", raise_if_both_names=True)
     def __init__(
         self,
         model: Optional[Union[PreTrainedModel, nn.Module, str]] = None,

trl/trainer/xpo_trainer.py

@@ -33,6 +33,7 @@ from transformers import (
 )
 from transformers.trainer_utils import EvalPrediction
 from transformers.training_args import OptimizerNames
+from transformers.utils.deprecation import deprecate_kwarg
 
 from ..data_utils import is_conversational, maybe_apply_chat_template
 from ..models.utils import unwrap_model_for_generation
@@ -92,6 +93,7 @@ class XPOTrainer(OnlineDPOTrainer):
 
     _tag_names = ["trl", "xpo"]
 
+    @deprecate_kwarg("tokenizer", new_name="processing_class", version="0.13.0", raise_if_both_names=True)
     def __init__(
         self,
         model: Union[PreTrainedModel, nn.Module] = None,