rename references to dpo dataset prep to pref data (#2258)

src/axolotl/common/datasets.py

@@ -11,7 +11,7 @@
 import axolotl.monkeypatch.data.batch_dataset_fetcher  # pylint: disable=unused-import  # noqa: F401
 from axolotl.cli.args import PreprocessCliArgs, TrainerCliArgs
 from axolotl.utils.data import prepare_dataset
-from axolotl.utils.data.rl import load_prepare_dpo_datasets
+from axolotl.utils.data.rl import load_prepare_preference_datasets
 from axolotl.utils.dict import DictDefault
 from axolotl.utils.models import load_processor, load_tokenizer
 from axolotl.utils.tokenization import check_dataset_labels
@@ -103,9 +103,9 @@ def load_preference_datasets(
     cli_args: Union[PreprocessCliArgs, TrainerCliArgs],
 ) -> TrainDatasetMeta:
     """
-    Loads one or more training or evaluation datasets for DPO training, calling
-    `axolotl.utils.data.rl.load_prepare_dpo_datasets`. Optionally, logs out debug
-    information.
+    Loads one or more training or evaluation datasets for RL training using paired
+    preference data, calling `axolotl.utils.data.rl.load_prepare_preference_datasets`.
+    Optionally, logs out debug information.
 
     Args:
         cfg: Dictionary mapping `axolotl` config keys to values.
@@ -115,7 +115,7 @@ def load_preference_datasets(
         Dataclass with fields for training and evaluation datasets and the computed
         `total_num_steps`.
     """
-    train_dataset, eval_dataset = load_prepare_dpo_datasets(cfg)
+    train_dataset, eval_dataset = load_prepare_preference_datasets(cfg)
     total_num_steps = int(
         math.ceil(len(train_dataset) * cfg.num_epochs / cfg.batch_size)
     )

src/axolotl/utils/data/__init__.py

@@ -5,7 +5,7 @@
     encode_pretraining,
     wrap_pretraining_dataset,
 )
-from axolotl.utils.data.rl import load_prepare_dpo_datasets  # noqa: F401
+from axolotl.utils.data.rl import load_prepare_preference_datasets  # noqa: F401
 from axolotl.utils.data.sft import (  # noqa: F401
     get_dataset_wrapper,
     load_prepare_datasets,

src/axolotl/utils/data/rl.py

@@ -115,7 +115,7 @@ def drop_long_rl_seq(
     raise ValueError("Unknown RL type")
 
 
-def load_prepare_dpo_datasets(cfg):
+def load_prepare_preference_datasets(cfg):
     def load_split(dataset_cfgs, _cfg):
         split_datasets: List[Any] = []
         for i, ds_cfg in enumerate(dataset_cfgs):

tests/test_datasets.py

@@ -17,7 +17,7 @@
 from transformers import AutoTokenizer
 
 from axolotl.utils.data import load_tokenized_prepared_datasets
-from axolotl.utils.data.rl import load_prepare_dpo_datasets
+from axolotl.utils.data.rl import load_prepare_preference_datasets
 from axolotl.utils.dict import DictDefault
 
 
@@ -280,7 +280,7 @@ def test_load_hub_with_dpo(self):
             }
         )
 
-        train_dataset, _ = load_prepare_dpo_datasets(cfg)
+        train_dataset, _ = load_prepare_preference_datasets(cfg)
 
         assert len(train_dataset) == 1800
         assert "conversation" in train_dataset.features
@@ -329,7 +329,7 @@ def test_load_hub_with_revision_with_dpo(self):
             }
         )
 
-        train_dataset, _ = load_prepare_dpo_datasets(cfg)
+        train_dataset, _ = load_prepare_preference_datasets(cfg)
 
         assert len(train_dataset) == 1800
         assert "conversation" in train_dataset.features

tests/test_exact_deduplication.py

@@ -12,7 +12,7 @@
 from transformers import AutoTokenizer
 
 from axolotl.utils.data import prepare_dataset
-from axolotl.utils.data.rl import load_prepare_dpo_datasets
+from axolotl.utils.data.rl import load_prepare_preference_datasets
 from axolotl.utils.data.utils import deduplicate_and_log_datasets
 from axolotl.utils.dict import DictDefault
 from axolotl.utils.models import load_processor, load_tokenizer
@@ -236,7 +236,7 @@ def test_load_with_deduplication(self):
         """Verify that loading with deduplication removes duplicates."""
 
         # Load the dataset using the deduplication setting
-        train_dataset, _ = load_prepare_dpo_datasets(self.cfg)
+        train_dataset, _ = load_prepare_preference_datasets(self.cfg)
 
         # Verify that the dataset has been deduplicated
         assert len(train_dataset) == 1800, "Dataset was not properly deduplicated"
@@ -245,7 +245,7 @@ def test_load_without_deduplication(self):
         """Verify that loading without deduplication retains duplicates."""
         self.cfg.dataset_exact_deduplication = False
         # Load the dataset without deduplication
-        train_dataset, _ = load_prepare_dpo_datasets(self.cfg)
+        train_dataset, _ = load_prepare_preference_datasets(self.cfg)
 
         # Verify that the dataset retains duplicates
         assert (