TF: remove graph mode distinction when processing boolean options (#18102)

src/transformers/modeling_tf_utils.py

@@ -346,8 +346,7 @@ class TFNextSentencePredictionLoss:
 
 def booleans_processing(config, **kwargs):
     """
-    Process the input booleans of each model in order to be sure they are compliant with the execution mode (eager or
-    graph)
+    Process the input booleans of each model.
 
     Args:
         config ([`PretrainedConfig`]):
@@ -360,42 +359,21 @@ def booleans_processing(config, **kwargs):
     """
     final_booleans = {}
 
-    if tf.executing_eagerly():
-        # Pure conv models (such as ConvNext) do not have `output_attentions`. If the signature has
-        # `output_attentions`, it will be present here in `kwargs`, even if unset (in that case, as `None`)
-        if "output_attentions" in kwargs:
-            final_booleans["output_attentions"] = (
-                kwargs["output_attentions"] if kwargs["output_attentions"] is not None else config.output_attentions
-            )
-        final_booleans["output_hidden_states"] = (
-            kwargs["output_hidden_states"]
-            if kwargs["output_hidden_states"] is not None
-            else config.output_hidden_states
-        )
-        final_booleans["return_dict"] = (
-            kwargs["return_dict"] if kwargs["return_dict"] is not None else config.return_dict
+    # Pure conv models (such as ConvNext) do not have `output_attentions`. If the signature has
+    # `output_attentions`, it will be present here in `kwargs`, even if unset (in that case, as `None`)
+    if "output_attentions" in kwargs:
+        final_booleans["output_attentions"] = (
+            kwargs["output_attentions"] if kwargs["output_attentions"] is not None else config.output_attentions
         )
+    final_booleans["output_hidden_states"] = (
+        kwargs["output_hidden_states"] if kwargs["output_hidden_states"] is not None else config.output_hidden_states
+    )
+    final_booleans["return_dict"] = kwargs["return_dict"] if kwargs["return_dict"] is not None else config.return_dict
 
-        if "use_cache" in kwargs:
-            final_booleans["use_cache"] = (
-                kwargs["use_cache"] if kwargs["use_cache"] is not None else getattr(config, "use_cache", None)
-            )
-    else:
-        # Pure conv models (such as ConvNext) do not have `output_attentions`. If the signature has
-        # `output_attentions`, it will be present here in `kwargs`, even if unset (in that case, as `None`)
-        if "output_attentions" in kwargs:
-            final_booleans["output_attentions"] = config.output_attentions
-        final_booleans["output_hidden_states"] = config.output_hidden_states
-
-        if kwargs.get("return_dict", None) not in (None, True):
-            tf_logger.warning(
-                "The parameter `return_dict` cannot be set in graph mode and will always be set to `True`."
-            )
-        final_booleans["return_dict"] = True
-
-        if "use_cache" in kwargs:
-            final_booleans["use_cache"] = getattr(config, "use_cache", None)
-
+    if "use_cache" in kwargs:
+        final_booleans["use_cache"] = (
+            kwargs["use_cache"] if kwargs["use_cache"] is not None else getattr(config, "use_cache", None)
+        )
     return final_booleans