Allow passing encoder_ouputs as tuple to EncoderDecoder Models (#16814)

* Add passing encoder_outputs as tuple to existing test

* Add check for tuple

* Add check for tuple also for speech and vision
Co-authored-by: jsnfly <jsnfly@gmx.de>

src/transformers/models/encoder_decoder/modeling_encoder_decoder.py

@@ -22,7 +22,7 @@ from torch import nn
 from torch.nn import CrossEntropyLoss
 
 from ...configuration_utils import PretrainedConfig
-from ...modeling_outputs import Seq2SeqLMOutput
+from ...modeling_outputs import BaseModelOutput, Seq2SeqLMOutput
 from ...modeling_utils import PreTrainedModel
 from ...utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
 from ..auto.configuration_auto import AutoConfig
@@ -494,6 +494,8 @@ class EncoderDecoderModel(PreTrainedModel):
                 return_dict=return_dict,
                 **kwargs_encoder,
             )
+        elif isinstance(encoder_outputs, tuple):
+            encoder_outputs = BaseModelOutput(*encoder_outputs)
 
         encoder_hidden_states = encoder_outputs[0]
 

src/transformers/models/speech_encoder_decoder/modeling_speech_encoder_decoder.py

@@ -22,7 +22,7 @@ from torch import nn
 from torch.nn import CrossEntropyLoss
 
 from ...configuration_utils import PretrainedConfig
-from ...modeling_outputs import Seq2SeqLMOutput
+from ...modeling_outputs import BaseModelOutput, Seq2SeqLMOutput
 from ...modeling_utils import PreTrainedModel
 from ...utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
 from ..auto.configuration_auto import AutoConfig
@@ -514,6 +514,8 @@ class SpeechEncoderDecoderModel(PreTrainedModel):
                 return_dict=return_dict,
                 **kwargs_encoder,
             )
+        elif isinstance(encoder_outputs, tuple):
+            encoder_outputs = BaseModelOutput(*encoder_outputs)
 
         encoder_hidden_states = encoder_outputs[0]
 

src/transformers/models/vision_encoder_decoder/modeling_vision_encoder_decoder.py

@@ -22,7 +22,7 @@ from torch import nn
 from torch.nn import CrossEntropyLoss
 
 from ...configuration_utils import PretrainedConfig
-from ...modeling_outputs import Seq2SeqLMOutput
+from ...modeling_outputs import BaseModelOutput, Seq2SeqLMOutput
 from ...modeling_utils import PreTrainedModel
 from ...utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
 from ..auto.configuration_auto import AutoConfig
@@ -466,6 +466,8 @@ class VisionEncoderDecoderModel(PreTrainedModel):
                 return_dict=return_dict,
                 **kwargs_encoder,
             )
+        elif isinstance(encoder_outputs, tuple):
+            encoder_outputs = BaseModelOutput(*encoder_outputs)
 
         encoder_hidden_states = encoder_outputs[0]
 

tests/encoder_decoder/test_modeling_encoder_decoder.py

@@ -142,6 +142,22 @@ class EncoderDecoderMixin:
             outputs_encoder_decoder["encoder_last_hidden_state"].shape, (input_ids.shape + (config.hidden_size,))
         )
 
+        # Test passing encoder_outputs as tuple.
+        encoder_outputs = (encoder_hidden_states,)
+        outputs_encoder_decoder = enc_dec_model(
+            encoder_outputs=encoder_outputs,
+            decoder_input_ids=decoder_input_ids,
+            attention_mask=attention_mask,
+            decoder_attention_mask=decoder_attention_mask,
+        )
+
+        self.assertEqual(
+            outputs_encoder_decoder["logits"].shape, (decoder_input_ids.shape + (decoder_config.vocab_size,))
+        )
+        self.assertEqual(
+            outputs_encoder_decoder["encoder_last_hidden_state"].shape, (input_ids.shape + (config.hidden_size,))
+        )
+
     def check_encoder_decoder_model_from_pretrained_using_model_paths(
         self,
         config,