[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/utils/common.py

@@ -0,0 +1,88 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import re
+
+import torch
+
+
+def tokenize_by_CJK_char(line: str, do_upper_case=True) -> str:
+    """
+    Tokenize a line of text with CJK char.
+
+    Note: All return characters will be upper case.
+
+    Example:
+      input = "你好世界是 hello world 的中文"
+      output = "你 好 世 界 是 HELLO WORLD 的 中 文"
+
+    Args:
+      line:
+        The input text.
+
+    Return:
+      A new string tokenize by CJK char.
+    """
+    # CJK ranges from nltk/tokenize/util.py (alvations/nltk@79eed6d)
+    CJK_RANGE_PATTERN = (
+        r"([\u1100-\u11ff\u2e80-\ua4cf\ua840-\uD7AF\uF900-\uFAFF\uFE30-\uFE4F\uFF65-\uFFDC\U00020000-\U0002FFFF])"
+    )
+    chars = re.split(CJK_RANGE_PATTERN, line.strip())
+    return " ".join([w.strip().upper() if do_upper_case else w.strip() for w in chars if w.strip()])
+
+
+def de_tokenized_by_CJK_char(line: str, do_lower_case=False) -> str:
+    """
+    Example:
+      input = "你 好 世 界 是 HELLO WORLD 的 中 文"
+      output = "你好世界是 hello world 的中文"
+
+    do_lower_case:
+      input = "SEE YOU!"
+      output = "see you!"
+    """
+    # replace english words in the line with placeholders
+    english_word_pattern = re.compile(r"([A-Z]+(?:[\s'-][A-Z-]+)*)", re.IGNORECASE)
+    english_sents = english_word_pattern.findall(line)
+    for i, sent in enumerate(english_sents):
+        line = line.replace(sent, f"<sent_{i}>")
+
+    words = line.split()
+    # restore english sentences
+    sent_placeholder_pattern = re.compile(r"(<sent_(\d+)>)")
+    for i in range(len(words)):
+        all_matches = sent_placeholder_pattern.findall(words[i])
+        if all_matches:
+            # restore the english word
+            for h, j in all_matches:
+                placeholder_index = int(j)
+                words[i] = words[i].replace(h, english_sents[placeholder_index])
+                if do_lower_case:
+                    words[i] = words[i].lower()
+    return "".join(words)
+
+
+def make_pad_mask(lengths: torch.Tensor, max_len: int = 0) -> torch.Tensor:
+    """Make mask tensor containing indices of padded part.
+
+    See description of make_non_pad_mask.
+
+    Args:
+        lengths (torch.Tensor): Batch of lengths (B,).
+    Returns:
+        torch.Tensor: Mask tensor containing indices of padded part.
+
+    Examples:
+        >>> lengths = [5, 3, 2]
+        >>> make_pad_mask(lengths)
+        masks = [[0, 0, 0, 0 ,0],
+                 [0, 0, 0, 1, 1],
+                 [0, 0, 1, 1, 1]]
+    """
+    batch_size = lengths.size(0)
+    max_len = max_len if max_len > 0 else lengths.max().item()
+    seq_range = torch.arange(0, max_len, dtype=torch.int64, device=lengths.device)
+    seq_range_expand = seq_range.unsqueeze(0).expand(batch_size, max_len)
+    seq_length_expand = lengths.unsqueeze(-1)
+    mask = seq_range_expand >= seq_length_expand
+    return mask