use crate::Gpt2Vocab;
use crate::preprocessing::vocab::base_vocab::Vocab;
use crate::preprocessing::tokenizer::base_tokenizer::{Tokenizer, Token, TokenRef, Mask};
use std::collections::HashMap;
use crate::preprocessing::tokenizer::tokenization_utils::{bpe, split_on_special_tokens, split_on_regex_with_lookahead, split_on_bpe_pairs, fix_mask};
use std::rc::Rc;
use std::cell::RefCell;
use crate::preprocessing::vocab::bpe_vocab::BpePairVocab;
use regex::Regex;
use crate::preprocessing::tokenizer::constants::UNICODE_TO_BYTES;
use std::iter::Iterator;
use itertools::Itertools;
use crate::tokenization_utils::lowercase;
pub struct Gpt2Tokenizer {
vocab: Rc<Gpt2Vocab>,
bpe_ranks: Rc<BpePairVocab>,
cache: RefCell<HashMap<String, (Vec<String>, Vec<usize>)>>,
pattern_lookahead: Regex,
pattern_tokenization: Regex,
lower_case: bool,
}
impl Gpt2Tokenizer {
pub fn from_file(vocab_path: &str, merges_path: &str, lower_case: bool) -> Gpt2Tokenizer {
let vocab = Rc::new(Gpt2Vocab::from_file(vocab_path));
let bpe_ranks = Rc::new(BpePairVocab::from_file(merges_path));
let cache = RefCell::new(HashMap::new());
let pattern_lookahead = Regex::new(r"\s+\S").unwrap();
let pattern_tokenization = Regex::new(r"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+").unwrap();
Gpt2Tokenizer { vocab, bpe_ranks, cache, pattern_lookahead, pattern_tokenization, lower_case }
}
pub fn from_existing_vocab_and_merges(vocab: Rc<Gpt2Vocab>, merges: Rc<BpePairVocab>, lower_case: bool) -> Gpt2Tokenizer {
let cache = RefCell::new(HashMap::new());
let pattern_lookahead = Regex::new(r"\s+\S").unwrap();
let pattern_tokenization = Regex::new(r"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+").unwrap();
Gpt2Tokenizer { vocab, bpe_ranks: merges, cache, pattern_lookahead, pattern_tokenization, lower_case }
}
}
impl Tokenizer<Gpt2Vocab> for Gpt2Tokenizer {
fn vocab(&self) -> &Gpt2Vocab {
self.vocab.as_ref()
}
fn tokenize_to_tokens(&self, initial_token: TokenRef) -> Vec<Token> {
let mut tokens = split_on_special_tokens(initial_token, self.vocab.as_ref())
.into_iter()
.map(|token| token.to_owned())
.collect::<Vec<Token>>();
let mut sub_tokens = Vec::new();
for token in tokens.iter_mut() {
if token.mask != Mask::Special && token.mask != Mask::Unknown {
if self.lower_case {
lowercase(token);
}
for token in split_on_regex_with_lookahead(token.as_ref(), &self.pattern_lookahead, &self.pattern_tokenization) {
sub_tokens.extend(split_on_bpe_pairs(token, bpe, (&self.bpe_ranks).as_ref(), &self.cache, true));
}
} else {
sub_tokens.push(token.clone());
}
}
fix_mask(&mut sub_tokens);
sub_tokens
}
fn convert_tokens_to_string(&self, tokens: Vec<String>) -> String {
let tokens = tokens
.iter()
.join("")
.replace(" ##", "")
.trim()
.chars()
.map(|character| UNICODE_TO_BYTES.get(&character).unwrap().clone())
.collect_vec();
String::from_utf8_lossy(&tokens).to_string()
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::Gpt2Vocab;
use std::collections::HashMap;
use crate::preprocessing::tokenizer::base_tokenizer::{TruncationStrategy, TokenizedInput, Offset};
use crate::preprocessing::vocab::base_vocab::swap_key_values;
fn generate_test_vocab() -> Gpt2Vocab {
let values: HashMap<String, i64> = [
("t".to_owned(), 0),
("h".to_owned(), 1),
("a@@".to_owned(), 2),
("n".to_owned(), 3),
("the".to_owned(), 4),
("Ġ".to_owned(), 5),
("<|endoftext|>".to_owned(), 6),
("o@@".to_owned(), 7),
("Ġear".to_owned(), 8),
("th".to_owned(), 9),
].iter().cloned().collect();
let special_values: HashMap<String, i64> = [
("<|endoftext|>".to_owned(), 6),
].iter().cloned().collect();
let indices = swap_key_values(&values);
let special_indices = swap_key_values(&special_values);
Gpt2Vocab { values, indices, unknown_value: "<|endoftext|>", special_values, special_indices }
}
fn generate_test_merges() -> BpePairVocab {
let values: HashMap<(String, String), i64> = [
(("Ġ".to_owned(), "t".to_owned()), 0),
(("Ġ".to_owned(), "n".to_owned()), 1),
(("e".to_owned(), "e".to_owned()), 2),
(("Ġt".to_owned(), "he".to_owned()), 3),
(("h".to_owned(), "e".to_owned()), 4),
(("t".to_owned(), "h".to_owned()), 5),
(("t".to_owned(), "he".to_owned()), 6),
(("Ġ".to_owned(), "e".to_owned()), 7),
(("Ġe".to_owned(), "a".to_owned()), 8),
(("Ġea".to_owned(), "r".to_owned()), 9),
].iter().cloned().collect();
BpePairVocab { values }
}
#[test]
fn test_gpt2_tokenizer() {
let vocab = Rc::new(generate_test_vocab());
let merges = Rc::new(generate_test_merges());
let gpt2_tokenizer: Gpt2Tokenizer = Gpt2Tokenizer::from_existing_vocab_and_merges(vocab, merges, true);
let test_tuples = [
(
"the Earth",
vec!("the", "Ġear", "th")
),
(
"",
vec!()
),
(
" ",
vec!()
),
(
" t",
vec!("Ġ", "Ġ", "Ġt")
),
(
"t ",
vec!("t")
),
(
" \n ",
vec!()
),
];
let source_texts: Vec<&str> = test_tuples.iter().map(|v| v.0).collect();
let expected_results: Vec<Vec<&str>> = test_tuples.iter().map(|v| v.1.clone()).collect();
for (source_text, expected_result) in test_tuples.iter() {
assert_eq!(gpt2_tokenizer.tokenize(*source_text), *expected_result);
}
assert_eq!(gpt2_tokenizer.tokenize_list(source_texts.clone()), expected_results);
}
#[test]
fn test_gpt2_tokenizer_no_lower_casing() {
let vocab = Rc::new(generate_test_vocab());
let merges = Rc::new(generate_test_merges());
let gpt2_tokenizer: Gpt2Tokenizer = Gpt2Tokenizer::from_existing_vocab_and_merges(vocab, merges, false);
let test_tuples = [
(
"the Earth",
vec!("the", "Ġ", "E", "a", "r", "th")
),
(
"",
vec!()
),
(
" ",
vec!()
),
(
" t",
vec!("Ġ", "Ġ", "Ġt")
),
(
" \n ",
vec!()
),
];
let source_texts: Vec<&str> = test_tuples.iter().map(|v| v.0).collect();
let expected_results: Vec<Vec<&str>> = test_tuples.iter().map(|v| v.1.clone()).collect();
for (source_text, expected_result) in test_tuples.iter() {
assert_eq!(gpt2_tokenizer.tokenize(*source_text), *expected_result);
}
assert_eq!(gpt2_tokenizer.tokenize_list(source_texts.clone()), expected_results);
}
#[test]
fn test_encode() {
let vocab = Rc::new(generate_test_vocab());
let merges = Rc::new(generate_test_merges());
let gpt2_tokenizer: Gpt2Tokenizer = Gpt2Tokenizer::from_existing_vocab_and_merges(vocab, merges, true);
let truncation_strategy = TruncationStrategy::LongestFirst;
let test_tuples = [
(
"the earth",
TokenizedInput {
token_ids: vec!(4, 8, 9),
segment_ids: vec!(0, 0, 0),
special_tokens_mask: vec!(0, 0, 0),
overflowing_tokens: vec!(),
num_truncated_tokens: 0,
token_offsets: vec!(
Some(Offset { begin: 0, end: 3 }), Some(Offset { begin: 3, end: 7 }), Some(Offset { begin: 7, end: 9 })
),
reference_offsets: vec!(vec!(0, 1, 2), vec!(3, 4, 5, 6), vec!(7, 8)),
mask: vec!(Mask::None, Mask::Begin, Mask::Continuation),
}
),
(
" ",
TokenizedInput {
token_ids: vec!(),
segment_ids: vec!(),
special_tokens_mask: vec!(),
overflowing_tokens:
vec!(),
num_truncated_tokens: 0,
token_offsets: vec!(),
reference_offsets: vec!(),
mask: vec!(),
}
),
(
"",
TokenizedInput {
token_ids: vec!(),
segment_ids: vec!(),
special_tokens_mask: vec!(),
overflowing_tokens: vec!(),
num_truncated_tokens: 0,
token_offsets: vec!(),
reference_offsets: vec!(),
mask: vec!(),
}
)
];
let source_texts: Vec<&str> = test_tuples.iter().map(|v| v.0).collect();
let expected_results: Vec<TokenizedInput> = test_tuples.iter().map(|v| v.1.clone()).collect();
for (source_text, expected_result) in test_tuples.iter() {
assert_eq!(gpt2_tokenizer.encode(source_text, None, 128, &truncation_strategy, 0),
*expected_result);
}
assert_eq!(gpt2_tokenizer.encode_list(source_texts.clone(), 128, &truncation_strategy, 0), expected_results);
}
#[test]
fn test_decode() {
let vocab = Rc::new(generate_test_vocab());
let merges = Rc::new(generate_test_merges());
let gpt2_tokenizer: Gpt2Tokenizer = Gpt2Tokenizer::from_existing_vocab_and_merges(vocab, merges, true);
let skip_special_tokens = false;
let clean_up_tokenization_spaces = false;
let test_tuples = [
(
vec!(4, 8, 9),
"the earth",
)
];
let source_ids: Vec<Vec<i64>> = test_tuples.iter().map(|v| v.0.clone()).collect_vec();
let expected_results: Vec<&str> = test_tuples.iter().map(|v| v.1.clone()).collect_vec();
for (source_ids, expected_result) in test_tuples.iter() {
assert_eq!(gpt2_tokenizer.decode(source_ids.clone(), skip_special_tokens, clean_up_tokenization_spaces),
*expected_result);
}
assert_eq!(Tokenizer::decode_list(&gpt2_tokenizer, source_ids.clone(), skip_special_tokens, clean_up_tokenization_spaces), expected_results);
}
}