Add missing FDivergenceType docstring

docs/source/dpo_trainer.md

@@ -295,3 +295,7 @@ dpo_trainer = DPOTrainer(
 ## DataCollatorForPreference
 
 [[autodoc]] trainer.dpo_trainer.DataCollatorForPreference
+
+## FDivergenceType
+
+[[autodoc]] trainer.dpo_trainer.FDivergenceType

trl/trainer/dpo_config.py

@@ -20,12 +20,37 @@
 
 
 class FDivergenceType(Enum):
+    """Types of f-divergence functions for DPO loss regularization.
+
+    Attributes:
+        REVERSE_KL: Reverse KL divergence.
+        JS_DIVERGENCE: Jensen-Shannon divergence.
+        ALPHA_DIVERGENCE: Alpha divergence.
+
+    Examples:
+        ```python
+        >>> from trl.trainer.dpo_config import DPOConfig, FDivergenceType
+
+        >>> config = DPOConfig(
+        ...     f_divergence_type=FDivergenceType.ALPHA_DIVERGENCE,
+        ...     f_alpha_divergence_coef=0.5,  # used only with ALPHA_DIVERGENCE
+        ... )
+        ```
+    """
+
     REVERSE_KL = "reverse_kl"
     JS_DIVERGENCE = "js_divergence"
     ALPHA_DIVERGENCE = "alpha_divergence"
 
 
 class FDivergenceConstants:
+    """Constants for f-divergence types and their parameters.
+
+    Attributes:
+        ALPHA_DIVERGENCE_COEF_KEY (`str`): Key for the alpha divergence coefficient.
+        ALPHA_DIVERGENCE_COEF_DEFAULT (`float`): Default value for the alpha divergence coefficient.
+    """
+
     ALPHA_DIVERGENCE_COEF_KEY = "alpha_divergence_coef"
     ALPHA_DIVERGENCE_COEF_DEFAULT = 1.0
 
@@ -140,7 +165,7 @@ class DPOConfig(TrainingArguments):
             Parameter controlling the deviation from the reference model. Higher β means less deviation from the
             reference model. For the IPO loss (`loss_type="ipo"`), β is the regularization parameter denoted by τ in
             the [paper](https://huggingface.co/papers/2310.12036).
-        f_divergence_type (`str`, *optional*, defaults to `FDivergenceType.REVERSE_KL`):
+        f_divergence_type ([`FDivergenceType`], *optional*, defaults to `FDivergenceType.REVERSE_KL`):
             Type of f-divergence regularization function to compute divergence between policy and reference model.
         f_alpha_divergence_coef (`float`, *optional*, defaults to `1.0`):
             α coefficient in the α-divergence u^-α regularization function for DPO loss.