fix can_generate (#36570)

* fix can_generate

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix can generate for speecht5 and blip

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix speecht5 tests

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

---------

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
Co-authored-by: Ilyas Moutawwakil <57442720+IlyasMoutawwakil@users.noreply.github.com>

src/transformers/models/blip/modeling_blip.py

@@ -1233,7 +1233,7 @@ class BlipForConditionalGeneration(BlipPreTrainedModel, GenerationMixin):
     """,
     BLIP_START_DOCSTRING,
 )
-class BlipForQuestionAnswering(BlipPreTrainedModel):
+class BlipForQuestionAnswering(BlipPreTrainedModel, GenerationMixin):
     config_class = BlipConfig
     _tied_weights_keys = ["text_decoder.cls.predictions.decoder.bias"]
 

src/transformers/models/speecht5/modeling_speecht5.py

@@ -2631,6 +2631,13 @@ class SpeechT5ForTextToSpeech(SpeechT5PreTrainedModel):
         # Initialize weights and apply final processing
         self.post_init()
 
+    @classmethod
+    def can_generate(cls) -> bool:
+        # Speecht5 has a unique model structure, where the external class (`SpeechT5ForTextToSpeech`) doesn't need to inherit from
+        # `GenerationMixin` (it has a non-standard generation method). This means that the base `can_generate()` will return `False`,
+        # but we need to override it so as to do `GenerationConfig` handling in multiple parts of the codebase.
+        return True
+
     def get_encoder(self):
         return self.speecht5.get_encoder()
 

tests/models/bark/test_modeling_bark.py

@@ -1076,6 +1076,10 @@ class BarkModelIntegrationTests(unittest.TestCase):
         fine_generation_config = BarkFineGenerationConfig(**self.model.generation_config.fine_acoustics_config)
         return fine_generation_config
 
+    def test_model_can_generate(self):
+        # Bark has custom generate without inheriting GenerationMixin. This test could prevent regression.
+        self.assertTrue(self.model.can_generate())
+
     @slow
     def test_generate_semantic(self):
         input_ids = self.inputs

tests/models/speecht5/test_modeling_speecht5.py

@@ -881,6 +881,7 @@ class SpeechT5ForTextToSpeechTester:
 @require_torch
 class SpeechT5ForTextToSpeechTest(ModelTesterMixin, unittest.TestCase):
     all_model_classes = (SpeechT5ForTextToSpeech,) if is_torch_available() else ()
+    all_generative_model_classes = ()
     is_encoder_decoder = True
     test_pruning = False
     test_headmasking = False
@@ -892,6 +893,12 @@ class SpeechT5ForTextToSpeechTest(ModelTesterMixin, unittest.TestCase):
     def test_config(self):
         self.config_tester.run_common_tests()
 
+    def test_model_can_generate(self):
+        config, inputs_dict = self.model_tester.prepare_config_and_inputs()
+        for model_class in self.all_model_classes:
+            model = model_class(config)
+            self.assertTrue(model.can_generate())
+
     def test_save_load_strict(self):
         config, inputs_dict = self.model_tester.prepare_config_and_inputs()
         for model_class in self.all_model_classes: