[seamless_m4t] Skip some tests when speech is not available

src/transformers/testing_utils.py

@@ -130,6 +130,7 @@
     is_seqio_available,
     is_soundfile_available,
     is_spacy_available,
+    is_speech_available,
     is_spqr_available,
     is_sudachi_available,
     is_sudachi_projection_available,
@@ -1476,6 +1477,13 @@ def require_tiktoken(test_case):
     return unittest.skipUnless(is_tiktoken_available(), "test requires TikToken")(test_case)
 
 
+def require_speech(test_case):
+    """
+    Decorator marking a test that requires speech. These tests are skipped when speech isn't available.
+    """
+    return unittest.skipUnless(is_speech_available(), "test requires torchaudio")(test_case)
+
+
 def get_gpu_count():
     """
     Return the number of available gpus (regardless of whether torch, tf or jax is used)

tests/models/seamless_m4t/test_modeling_seamless_m4t.py

@@ -18,7 +18,7 @@
 import unittest
 
 from transformers import SeamlessM4TConfig, is_speech_available, is_torch_available
-from transformers.testing_utils import require_torch, slow, torch_device
+from transformers.testing_utils import require_speech, require_torch, slow, torch_device
 from transformers.trainer_utils import set_seed
 from transformers.utils import cached_property
 
@@ -1028,6 +1028,7 @@ def test_to_swh_text(self):
 
         self.assertListAlmostEqual(expected_wav_slice, output.waveform.squeeze().tolist()[50:60])
 
+    @require_speech
     @slow
     def test_to_rus_speech(self):
         model = SeamlessM4TModel.from_pretrained(self.repo_id).to(torch_device)
@@ -1066,6 +1067,7 @@ def test_text_to_text_model(self):
         }
         self.factory_test_task(SeamlessM4TModel, SeamlessM4TForTextToText, self.input_text, kwargs1, kwargs2)
 
+    @require_speech
     @slow
     def test_speech_to_text_model(self):
         kwargs1 = {"tgt_lang": "eng", "return_intermediate_token_ids": True, "generate_speech": False}
@@ -1077,6 +1079,7 @@ def test_speech_to_text_model(self):
         }
         self.factory_test_task(SeamlessM4TModel, SeamlessM4TForSpeechToText, self.input_audio, kwargs1, kwargs2)
 
+    @require_speech
     @slow
     def test_speech_to_speech_model(self):
         kwargs1 = {"tgt_lang": "eng", "return_intermediate_token_ids": True}

tests/models/seamless_m4t_v2/test_modeling_seamless_m4t_v2.py

@@ -18,7 +18,7 @@
 import unittest
 
 from transformers import SeamlessM4Tv2Config, is_speech_available, is_torch_available
-from transformers.testing_utils import require_torch, slow, torch_device
+from transformers.testing_utils import require_speech, require_torch, slow, torch_device
 from transformers.trainer_utils import set_seed
 from transformers.utils import cached_property
 
@@ -1095,6 +1095,7 @@ def test_to_swh_text(self):
             [-2.001826e-04, 8.580012e-02], [output.waveform.mean().item(), output.waveform.std().item()]
         )
 
+    @require_speech
     @slow
     def test_to_rus_speech(self):
         model = SeamlessM4Tv2Model.from_pretrained(self.repo_id).to(torch_device)
@@ -1139,6 +1140,7 @@ def test_text_to_text_model(self):
         }
         self.factory_test_task(SeamlessM4Tv2Model, SeamlessM4Tv2ForTextToText, self.input_text, kwargs1, kwargs2)
 
+    @require_speech
     @slow
     def test_speech_to_text_model(self):
         kwargs1 = {"tgt_lang": "eng", "return_intermediate_token_ids": True, "generate_speech": False}
@@ -1150,6 +1152,7 @@ def test_speech_to_text_model(self):
         }
         self.factory_test_task(SeamlessM4Tv2Model, SeamlessM4Tv2ForSpeechToText, self.input_audio, kwargs1, kwargs2)
 
+    @require_speech
     @slow
     def test_speech_to_speech_model(self):
         kwargs1 = {"tgt_lang": "eng", "return_intermediate_token_ids": True}