[Model] Add IndexTTS2 text-to-speech support (#3838)

Signed-off-by: BeatSeat <wendavid552@gmail.com>
Signed-off-by: David <david@podcast.ai>
Signed-off-by: wendavid552 <wendavid552@gmail.com>
Signed-off-by: WenDavid <davidzhangcf@foxmail.com>

vllm_omni/model_executor/models/indextts2/tokenizer.py

@@ -0,0 +1,56 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import os
+
+from transformers import PreTrainedTokenizer
+from vllm.logger import init_logger
+
+from vllm_omni.model_executor.models.indextts2.utils.front import TextTokenizer
+
+logger = init_logger(__name__)
+
+
+class IndexTTS2Tokenizer(PreTrainedTokenizer):
+    @classmethod
+    def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs):
+        vocab_file = kwargs.pop("vocab_file", None)
+        if vocab_file is None:
+            vocab_file = os.path.join(pretrained_model_name_or_path, "bpe.model")
+        logger.info(f"IndexTTS2Tokenizer.from_pretrained: {pretrained_model_name_or_path}")
+        return cls(vocab_file, **kwargs)
+
+    def __init__(self, vocab_file: str, **kwargs):
+        logger.info(f"IndexTTS2Tokenizer.__init__: vocab_file={vocab_file}")
+        self.vocab_file = vocab_file
+        self._tok = TextTokenizer(vocab_file)
+        logger.info("IndexTTS2Tokenizer initialized successfully")
+        super().__init__(**kwargs)
+
+    @property
+    def vocab_size(self):
+        return self._tok.vocab_size
+
+    def get_vocab(self):
+        return self._tok.get_vocab()
+
+    def _tokenize(self, text):
+        return self._tok.tokenize(text)
+
+    def _convert_token_to_id(self, token):
+        return self._tok.convert_tokens_to_ids(token)[0]
+
+    def convert_tokens_to_string(self, tokens):
+        return self._tok.decode(self._tok.convert_tokens_to_ids(tokens))
+
+    def split_segments(
+        self,
+        tokenized: list[str],
+        max_text_tokens_per_segment: int = 120,
+        quick_streaming_tokens: int = 0,
+    ) -> list[list[str]]:
+        return self._tok.split_segments(
+            tokenized,
+            max_text_tokens_per_segment=max_text_tokens_per_segment,
+            quick_streaming_tokens=quick_streaming_tokens,
+        )