Support for returning past_key_values from the model

trl/models/modeling_value_head.py

@@ -144,6 +144,7 @@ def forward(
         input_ids=None,
         past_key_values=None,
         attention_mask=None,
+        return_past_key_values=False,
         **kwargs,
     ):
         r"""
@@ -159,6 +160,7 @@ def forward(
                 Mask to avoid performing attention on padding token indices. Mask values selected in ``[0, 1]``:
                 - 1 for tokens that are **not masked**,
                 - 0 for tokens that are **masked**.
+            return_past_key_values (bool): A flag indicating if the computed hidden-states should be returned.
             kwargs (`dict`, `optional`):
                 Additional keyword arguments, that are passed to the wrapped model.
         """
@@ -187,7 +189,10 @@ def forward(
         if lm_logits.dtype != torch.float32:
             lm_logits = lm_logits.float()
 
-        return (lm_logits, loss, value)
+        if return_past_key_values:
+            return (lm_logits, loss, value, base_model_output.past_key_values)
+        else:
+            return (lm_logits, loss, value)
 
     def generate(self, *args, **kwargs):
         r"""
@@ -406,6 +411,7 @@ def forward(
         input_ids=None,
         past_key_values=None,
         attention_mask=None,
+        return_past_key_values=False,
         **kwargs,
     ):
         kwargs["past_key_values"] = past_key_values
@@ -429,7 +435,10 @@ def forward(
         if lm_logits.dtype != torch.float32:
             lm_logits = lm_logits.float()
 
-        return (lm_logits, loss, value)
+        if return_past_key_values:
+            return (lm_logits, loss, value, base_model_output.past_key_values)
+        else:
+            return (lm_logits, loss, value)
 
     def generate(self, *args, **kwargs):
         r"""