diff --git a/mlx_audio/tts/tests/test_models.py b/mlx_audio/tts/tests/test_models.py index c4bd26104..479218b31 100644 --- a/mlx_audio/tts/tests/test_models.py +++ b/mlx_audio/tts/tests/test_models.py @@ -616,14 +616,14 @@ def _default_config(self): "layer_types": ["full_attention"] * 28, } - @patch("transformers.LlamaTokenizer") + @patch("transformers.AutoTokenizer") def test_init(self, mock_tokenizer): """Test LlamaModel initialization.""" from mlx_audio.tts.models.llama.llama import Model, ModelConfig # Mock the tokenizer instance mock_tokenizer_instance = MagicMock() - mock_tokenizer.return_value = mock_tokenizer_instance + mock_tokenizer.from_pretrained.return_value = mock_tokenizer_instance # Create a minimal config config = ModelConfig(**self._default_config) @@ -634,14 +634,22 @@ def test_init(self, mock_tokenizer): # Check that model was created self.assertIsInstance(model, Model) - @patch("transformers.LlamaTokenizer") + @patch("transformers.AutoTokenizer") def test_generate(self, mock_tokenizer): """Test generate method.""" from mlx_audio.tts.models.llama.llama import Model, ModelConfig # Mock tokenizer instance mock_tokenizer_instance = MagicMock() - mock_tokenizer.return_value = mock_tokenizer_instance + + def mock_tokenize(text, return_tensors=None): + result = MagicMock() + result.input_ids = mx.array([[1, 2, 3, 4]], dtype=mx.int64) + return result + + mock_tokenizer_instance.side_effect = mock_tokenize + mock_tokenizer_instance.__call__ = mock_tokenize + mock_tokenizer.from_pretrained.return_value = mock_tokenizer_instance config = ModelConfig(**self._default_config) model = Model(config) @@ -651,7 +659,7 @@ def test_generate(self, mock_tokenizer): self.assertEqual(input_ids.shape[0], 2) logits = model(input_ids) - self.assertEqual(logits.shape, (2, 9, config.vocab_size)) + self.assertEqual(logits.shape, (2, input_ids.shape[1], config.vocab_size)) # Verify batched input creation with reference audio input_ids, input_mask = model.prepare_input_ids( @@ -660,16 +668,16 @@ def test_generate(self, mock_tokenizer): self.assertEqual(input_ids.shape[0], 2) logits = model(input_ids) - self.assertEqual(logits.shape, (2, 22, config.vocab_size)) + self.assertEqual(logits.shape, (2, input_ids.shape[1], config.vocab_size)) - @patch("transformers.LlamaTokenizer") + @patch("transformers.AutoTokenizer") def test_sanitize(self, mock_tokenizer): """Test sanitize method.""" from mlx_audio.tts.models.llama.llama import Model, ModelConfig # Mock tokenizer instance mock_tokenizer_instance = MagicMock() - mock_tokenizer.return_value = mock_tokenizer_instance + mock_tokenizer.from_pretrained.return_value = mock_tokenizer_instance # Create a config with tie_word_embeddings=True config = ModelConfig( @@ -918,14 +926,14 @@ def _default_config(self): "vocab_size": 134400, } - @patch("transformers.LlamaTokenizer") + @patch("transformers.AutoTokenizer") def test_init(self, mock_tokenizer): """Test initialization.""" from mlx_audio.tts.models.outetts.outetts import Model, ModelConfig # Mock the tokenizer instance mock_tokenizer_instance = MagicMock() - mock_tokenizer.return_value = mock_tokenizer_instance + mock_tokenizer.from_pretrained.return_value = mock_tokenizer_instance # Create a minimal config config = ModelConfig(**self._default_config) @@ -936,14 +944,14 @@ def test_init(self, mock_tokenizer): # Check that model was created self.assertIsInstance(model, Model) - @patch("transformers.LlamaTokenizer") + @patch("transformers.AutoTokenizer") def test_generate(self, mock_tokenizer): """Test generate method.""" from mlx_audio.tts.models.outetts.outetts import Model, ModelConfig # Mock tokenizer instance mock_tokenizer_instance = MagicMock() - mock_tokenizer.return_value = mock_tokenizer_instance + mock_tokenizer.from_pretrained.return_value = mock_tokenizer_instance config = ModelConfig(**self._default_config) model = Model(config) diff --git a/pyproject.toml b/pyproject.toml index 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