Fix languages covered by M4Tv2 (#28019)

* correct language assessment  + add tests

* Update src/transformers/models/seamless_m4t_v2/modeling_seamless_m4t_v2.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* make style + simplify and enrich test

---------

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

src/transformers/models/seamless_m4t_v2/modeling_seamless_m4t_v2.py

@@ -4596,7 +4596,11 @@ class SeamlessM4Tv2Model(SeamlessM4Tv2PreTrainedModel):
         if tgt_lang is not None:
             # also accept __xxx__
             tgt_lang = tgt_lang.replace("__", "")
-            for key in ["text_decoder_lang_to_code_id", "t2u_lang_code_to_id", "vocoder_lang_code_to_id"]:
+            if generate_speech:
+                keys_to_check = ["text_decoder_lang_to_code_id", "t2u_lang_code_to_id", "vocoder_lang_code_to_id"]
+            else:
+                keys_to_check = ["text_decoder_lang_to_code_id"]
+            for key in keys_to_check:
                 lang_code_to_id = getattr(self.generation_config, key, None)
                 if lang_code_to_id is None:
                     raise ValueError(

tests/models/seamless_m4t_v2/test_modeling_seamless_m4t_v2.py

@@ -758,7 +758,13 @@ class SeamlessM4Tv2GenerationTest(unittest.TestCase):
         self.tmpdirname = tempfile.mkdtemp()
 
     def update_generation(self, model):
-        lang_code_to_id = {
+        text_lang_code_to_id = {
+            "fra": 4,
+            "eng": 4,
+            "rus": 4,
+        }
+
+        speech_lang_code_to_id = {
             "fra": 4,
             "eng": 4,
         }
@@ -773,9 +779,9 @@ class SeamlessM4Tv2GenerationTest(unittest.TestCase):
 
         generation_config = copy.deepcopy(model.generation_config)
 
-        generation_config.__setattr__("text_decoder_lang_to_code_id", lang_code_to_id)
+        generation_config.__setattr__("text_decoder_lang_to_code_id", text_lang_code_to_id)
-        generation_config.__setattr__("t2u_lang_code_to_id", lang_code_to_id)
+        generation_config.__setattr__("t2u_lang_code_to_id", speech_lang_code_to_id)
-        generation_config.__setattr__("vocoder_lang_code_to_id", lang_code_to_id)
+        generation_config.__setattr__("vocoder_lang_code_to_id", speech_lang_code_to_id)
         generation_config.__setattr__("id_to_text", id_to_text)
         generation_config.__setattr__("char_to_id", char_to_id)
         generation_config.__setattr__("eos_token_id", 0)
@@ -784,13 +790,13 @@ class SeamlessM4Tv2GenerationTest(unittest.TestCase):
 
         model.generation_config = generation_config
 
-    def prepare_text_input(self):
+    def prepare_text_input(self, tgt_lang):
         config, inputs, decoder_input_ids, input_mask, lm_labels = self.text_model_tester.prepare_config_and_inputs()
 
         input_dict = {
             "input_ids": inputs,
             "attention_mask": input_mask,
-            "tgt_lang": "eng",
+            "tgt_lang": tgt_lang,
             "num_beams": 2,
             "do_sample": True,
         }
@@ -837,6 +843,26 @@ class SeamlessM4Tv2GenerationTest(unittest.TestCase):
         output = model.generate(**inputs)
         return output
 
+    def test_generation_languages(self):
+        config, input_text_rus = self.prepare_text_input(tgt_lang="rus")
+
+        model = SeamlessM4Tv2Model(config=config)
+        self.update_generation(model)
+        model.to(torch_device)
+        model.eval()
+
+        # make sure that generating speech, with a language that is only supported for text translation, raises error
+        with self.assertRaises(ValueError):
+            model.generate(**input_text_rus)
+
+        # make sure that generating text only works
+        model.generate(**input_text_rus, generate_speech=False)
+
+        # make sure it works for languages supported by both output modalities
+        config, input_text_eng = self.prepare_text_input(tgt_lang="eng")
+        model.generate(**input_text_eng)
+        model.generate(**input_text_eng, generate_speech=False)
+
     def test_speech_generation(self):
         config, input_speech, input_text = self.prepare_speech_and_text_input()