Generate: improve docstrings for custom stopping criteria (#26863)

improve docstrings

src/transformers/generation/stopping_criteria.py

@@ -23,7 +23,8 @@
             [What are input IDs?](../glossary#input-ids)
         scores (`torch.FloatTensor` of shape `(batch_size, config.vocab_size)`):
             Prediction scores of a language modeling head. These can be scores for each vocabulary token before SoftMax
-            or scores for each vocabulary token after SoftMax.
+            or scores for each vocabulary token after SoftMax. If this stopping criteria depends on the `scores` input,
+            make sure you pass `return_dict_in_generate=True, output_scores=True` to `generate`.
         kwargs (`Dict[str, Any]`, *optional*):
             Additional stopping criteria specific kwargs.
 
@@ -34,7 +35,11 @@
 
 
 class StoppingCriteria(ABC):
-    """Abstract base class for all stopping criteria that can be applied during generation."""
+    """Abstract base class for all stopping criteria that can be applied during generation.
+
+    If your stopping criteria depends on the `scores` input, make sure you pass `return_dict_in_generate=True,
+    output_scores=True` to `generate`.
+    """
 
     @add_start_docstrings(STOPPING_CRITERIA_INPUTS_DOCSTRING)
     def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs) -> bool:

src/transformers/generation/utils.py

@@ -1397,7 +1397,9 @@ def generate(
             stopping_criteria (`StoppingCriteriaList`, *optional*):
                 Custom stopping criteria that complement the default stopping criteria built from arguments and a
                 generation config. If a stopping criteria is passed that is already created with the arguments or a
-                generation config an error is thrown. This feature is intended for advanced users.
+                generation config an error is thrown. If your stopping criteria depends on the `scores` input, make
+                sure you pass `return_dict_in_generate=True, output_scores=True` to `generate`. This feature is
+                intended for advanced users.
             prefix_allowed_tokens_fn (`Callable[[int, torch.Tensor], List[int]]`, *optional*):
                 If provided, this function constraints the beam search to allowed tokens only at each step. If not
                 provided no constraint is applied. This function takes 2 arguments: the batch ID `batch_id` and