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//! Text tokenization for TTS
//!
//! Uses SentencePiece BPE tokenization for converting text to tokens
use crate::{Error, Result};
use std::collections::HashMap;
use std::path::Path;
/// Tokenizer configuration
#[derive(Debug, Clone)]
pub struct TokenizerConfig {
/// Path to BPE model
pub model_path: String,
/// Vocabulary size
pub vocab_size: usize,
/// Start of text token ID
pub bos_id: i64,
/// End of text token ID
pub eos_id: i64,
/// Unknown token ID
pub unk_id: i64,
/// Padding token ID
pub pad_id: i64,
}
impl Default for TokenizerConfig {
fn default() -> Self {
Self {
model_path: "models/bpe.model".to_string(),
vocab_size: 6681,
bos_id: 1,
eos_id: 2,
unk_id: 0,
pad_id: 3,
}
}
}
/// Text tokenizer using BPE (Byte Pair Encoding)
#[derive(Debug)]
pub struct TextTokenizer {
/// Configuration
config: TokenizerConfig,
/// Token to ID mapping
token_to_id: HashMap<String, i64>,
/// ID to token mapping
id_to_token: HashMap<i64, String>,
/// Character-level fallback vocabulary
char_vocab: HashMap<char, i64>,
}
impl TextTokenizer {
/// Create new tokenizer with default vocabulary
pub fn new(config: TokenizerConfig) -> Result<Self> {
let mut token_to_id = HashMap::new();
let mut id_to_token = HashMap::new();
let mut char_vocab = HashMap::new();
// Add special tokens
token_to_id.insert("<unk>".to_string(), config.unk_id);
token_to_id.insert("<s>".to_string(), config.bos_id);
token_to_id.insert("</s>".to_string(), config.eos_id);
token_to_id.insert("<pad>".to_string(), config.pad_id);
id_to_token.insert(config.unk_id, "<unk>".to_string());
id_to_token.insert(config.bos_id, "<s>".to_string());
id_to_token.insert(config.eos_id, "</s>".to_string());
id_to_token.insert(config.pad_id, "<pad>".to_string());
// Add basic ASCII characters
let mut next_id = 4i64;
for c in ' '..='~' {
char_vocab.insert(c, next_id);
token_to_id.insert(c.to_string(), next_id);
id_to_token.insert(next_id, c.to_string());
next_id += 1;
}
// Add Chinese character range (simplified approach)
// In production, this would load from the actual BPE model
for code_point in 0x4E00u32..=0x9FFF {
if let Some(c) = char::from_u32(code_point) {
char_vocab.insert(c, next_id);
token_to_id.insert(c.to_string(), next_id);
id_to_token.insert(next_id, c.to_string());
next_id += 1;
if next_id >= config.vocab_size as i64 {
break;
}
}
}
Ok(Self {
config,
token_to_id,
id_to_token,
char_vocab,
})
}
/// Load tokenizer from model file
pub fn load<P: AsRef<Path>>(path: P) -> Result<Self> {
let path = path.as_ref();
if !path.exists() {
return Err(Error::FileNotFound(path.display().to_string()));
}
// In production, this would load the actual SentencePiece model
// For now, create a character-level tokenizer
let config = TokenizerConfig {
model_path: path.display().to_string(),
..Default::default()
};
Self::new(config)
}
/// Encode text to token IDs
pub fn encode(&self, text: &str) -> Result<Vec<i64>> {
let mut tokens = Vec::new();
// Add BOS token
tokens.push(self.config.bos_id);
// Tokenize character by character (simplified)
// In production, this would use BPE merging
for ch in text.chars() {
if let Some(&id) = self.char_vocab.get(&ch) {
tokens.push(id);
} else if let Some(&id) = self.token_to_id.get(&ch.to_string()) {
tokens.push(id);
} else {
// Unknown token
tokens.push(self.config.unk_id);
}
}
// Add EOS token
tokens.push(self.config.eos_id);
Ok(tokens)
}
/// Encode text without special tokens
pub fn encode_without_special(&self, text: &str) -> Result<Vec<i64>> {
let mut tokens = Vec::new();
for ch in text.chars() {
if let Some(&id) = self.char_vocab.get(&ch) {
tokens.push(id);
} else if let Some(&id) = self.token_to_id.get(&ch.to_string()) {
tokens.push(id);
} else {
tokens.push(self.config.unk_id);
}
}
Ok(tokens)
}
/// Decode token IDs to text
pub fn decode(&self, tokens: &[i64]) -> Result<String> {
let mut text = String::new();
for &token_id in tokens {
// Skip special tokens
if token_id == self.config.bos_id
|| token_id == self.config.eos_id
|| token_id == self.config.pad_id
{
continue;
}
if let Some(token) = self.id_to_token.get(&token_id) {
text.push_str(token);
} else {
// Unknown token placeholder
text.push('?');
}
}
Ok(text)
}
/// Get vocabulary size
pub fn vocab_size(&self) -> usize {
self.config.vocab_size
}
/// Get BOS token ID
pub fn bos_id(&self) -> i64 {
self.config.bos_id
}
/// Get EOS token ID
pub fn eos_id(&self) -> i64 {
self.config.eos_id
}
/// Get UNK token ID
pub fn unk_id(&self) -> i64 {
self.config.unk_id
}
/// Get PAD token ID
pub fn pad_id(&self) -> i64 {
self.config.pad_id
}
/// Pad sequences to same length
pub fn pad_sequences(&self, sequences: &[Vec<i64>], max_len: Option<usize>) -> Vec<Vec<i64>> {
let max_length = max_len.unwrap_or_else(|| sequences.iter().map(|s| s.len()).max().unwrap_or(0));
sequences
.iter()
.map(|seq| {
let mut padded = seq.clone();
while padded.len() < max_length {
padded.push(self.config.pad_id);
}
padded.truncate(max_length);
padded
})
.collect()
}
/// Create attention mask (1 for real tokens, 0 for padding)
pub fn create_attention_mask(&self, tokens: &[i64]) -> Vec<i64> {
tokens
.iter()
.map(|&t| if t == self.config.pad_id { 0 } else { 1 })
.collect()
}
/// Batch encode multiple texts
pub fn batch_encode(&self, texts: &[&str]) -> Result<Vec<Vec<i64>>> {
texts.iter().map(|text| self.encode(text)).collect()
}
/// Batch encode and pad
pub fn batch_encode_padded(
&self,
texts: &[&str],
max_len: Option<usize>,
) -> Result<Vec<Vec<i64>>> {
let encoded: Vec<Vec<i64>> = self.batch_encode(texts)?;
Ok(self.pad_sequences(&encoded, max_len))
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_tokenizer_creation() {
let config = TokenizerConfig::default();
let tokenizer = TextTokenizer::new(config).unwrap();
assert!(tokenizer.vocab_size() > 0);
}
#[test]
fn test_encode_decode() {
let config = TokenizerConfig::default();
let tokenizer = TextTokenizer::new(config).unwrap();
let text = "Hello world";
let tokens = tokenizer.encode(text).unwrap();
// Should start with BOS and end with EOS
assert_eq!(tokens[0], tokenizer.bos_id());
assert_eq!(*tokens.last().unwrap(), tokenizer.eos_id());
let decoded = tokenizer.decode(&tokens).unwrap();
assert_eq!(decoded, text);
}
#[test]
fn test_encode_chinese() {
let config = TokenizerConfig::default();
let tokenizer = TextTokenizer::new(config).unwrap();
let text = "你好";
let tokens = tokenizer.encode(text).unwrap();
// Should have BOS + 2 chars + EOS = 4 tokens
assert_eq!(tokens.len(), 4);
}
#[test]
fn test_pad_sequences() {
let config = TokenizerConfig::default();
let tokenizer = TextTokenizer::new(config).unwrap();
let seq1 = vec![1, 2, 3];
let seq2 = vec![1, 2, 3, 4, 5];
let padded = tokenizer.pad_sequences(&[seq1, seq2], None);
assert_eq!(padded[0].len(), 5);
assert_eq!(padded[1].len(), 5);
assert_eq!(padded[0][3], tokenizer.pad_id());
}
#[test]
fn test_attention_mask() {
let config = TokenizerConfig::default();
let tokenizer = TextTokenizer::new(config).unwrap();
let tokens = vec![1, 2, tokenizer.pad_id(), tokenizer.pad_id()];
let mask = tokenizer.create_attention_mask(&tokens);
assert_eq!(mask, vec![1, 1, 0, 0]);
}
}
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