rust_tokenizers 3.1.2

// Copyright 2018 The Open AI Team Authors
// Copyright 2018 The HuggingFace Inc. team.
// Copyright 2019-2020 Guillaume Becquin
// Copyright 2020 Maarten van Gompel
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//     http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

use crate::RobertaVocab;
use crate::preprocessing::vocab::base_vocab::Vocab;
use crate::preprocessing::tokenizer::base_tokenizer::{Tokenizer, Offset, Token, TokenRef, Mask, OffsetSize};
use std::collections::HashMap;
use crate::preprocessing::tokenizer::tokenization_utils::{bpe, split_on_special_tokens, is_whitespace, 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 RobertaTokenizer {
    vocab: Rc<RobertaVocab>,
    bpe_ranks: Rc<BpePairVocab>,
    cache: RefCell<HashMap<String, (Vec<String>, Vec<usize>)>>,
    pattern_lookahead: Regex,
    pattern_tokenization: Regex,
    lower_case: bool,
}

impl RobertaTokenizer {
    pub fn from_file(vocab_path: &str, merges_path: &str, lower_case: bool) -> RobertaTokenizer {
        let vocab = Rc::new(RobertaVocab::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();
        RobertaTokenizer { vocab, bpe_ranks, cache, pattern_lookahead, pattern_tokenization, lower_case }
    }

    pub fn from_existing_vocab_and_merges(vocab: Rc<RobertaVocab>, merges: Rc<BpePairVocab>, lower_case: bool) -> RobertaTokenizer {
        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();
        RobertaTokenizer { vocab, bpe_ranks: merges, cache, pattern_lookahead, pattern_tokenization, lower_case }
    }
}

impl Tokenizer<RobertaVocab> for RobertaTokenizer {
    fn vocab(&self) -> &RobertaVocab {
        self.vocab.as_ref()
    }

    fn tokenize_to_tokens(&self, initial_token: TokenRef) -> Vec<Token> {
        if initial_token.text.len() == 0 {
            return vec!();
        }
        let mut initial_token: Token = initial_token.to_owned();
        if !is_whitespace(&initial_token.text.chars().next().unwrap()) {
            //text should always start with an initial whitespace
            initial_token.text.insert(0, ' ');
            initial_token.reference_offsets.insert(0, 0);
        };
        let mut tokens: Vec<Token> = split_on_special_tokens(initial_token.as_ref(), 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, &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()
    }

    fn build_input_with_special_tokens(&self, tokens_1: Vec<i64>, tokens_2: Option<Vec<i64>>,
                                       offsets_1: Vec<Option<Offset>>, offsets_2: Option<Vec<Option<Offset>>>,
                                       original_offsets_1: Vec<Vec<OffsetSize>>, original_offsets_2: Option<Vec<Vec<OffsetSize>>>,
                                       mask_1: Vec<Mask>, mask_2: Option<Vec<Mask>>) -> (Vec<i64>, Vec<i8>, Vec<i8>, Vec<Option<Offset>>, Vec<Vec<OffsetSize>>, Vec<Mask>) {
        let mut output: Vec<i64> = vec!();
        let mut token_segment_ids: Vec<i8> = vec!();
        let mut special_tokens_mask: Vec<i8> = vec!();
        let mut offsets: Vec<Option<Offset>> = vec!();
        let mut original_offsets: Vec<Vec<OffsetSize>> = vec!();
        let mut mask: Vec<Mask> = vec!();
        special_tokens_mask.push(1);
        special_tokens_mask.extend(vec![0; tokens_1.len()]);
        special_tokens_mask.push(1);
        token_segment_ids.extend(vec![0; tokens_1.len() + 2]);
        output.push(self.vocab.token_to_id(RobertaVocab::cls_value()));
        output.extend(tokens_1);
        output.push(self.vocab.token_to_id(RobertaVocab::sep_value()));
        offsets.push(None);
        offsets.extend(offsets_1);
        offsets.push(None);
        original_offsets.push(vec!());
        original_offsets.extend(original_offsets_1);
        original_offsets.push(vec!());
        mask.push(Mask::Special);
        mask.extend(mask_1);
        mask.push(Mask::Special);
        if let Some(add_tokens) = tokens_2 {
            let length = add_tokens.len();
            special_tokens_mask.push(1);
            special_tokens_mask.extend(vec![0; add_tokens.len()]);
            special_tokens_mask.push(1);
            token_segment_ids.push(0);
            token_segment_ids.extend(vec![1; add_tokens.len() + 1]);
            output.push(self.vocab.token_to_id(RobertaVocab::sep_value()));
            output.extend(add_tokens);
            output.push(self.vocab.token_to_id(RobertaVocab::sep_value()));
            if let Some(add_offsets) = offsets_2 {
                offsets.extend(add_offsets);
            } else {
                offsets.extend(vec![None; length]);
            }
            if let Some(add_original_offsets) = original_offsets_2 {
                original_offsets.extend(add_original_offsets);
            }
            offsets.push(None);
            original_offsets.push(vec!());
            if let Some(mask_2) = mask_2 {
                mask.extend(mask_2)
            } else {
                mask.extend(vec![Mask::None; length]);
            }
            mask.push(Mask::Special);
        }
        (output, token_segment_ids, special_tokens_mask, offsets, original_offsets, mask)
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::RobertaVocab;
    use std::collections::HashMap;
    use crate::preprocessing::tokenizer::base_tokenizer::{TruncationStrategy, TokenizedInput};
    use crate::preprocessing::vocab::base_vocab::swap_key_values;

    fn generate_test_vocab() -> RobertaVocab {
        let values: HashMap<String, i64> = [
            ("t".to_owned(), 0),
            ("h".to_owned(), 1),
            ("a@@".to_owned(), 2),
            ("n".to_owned(), 3),
            ("Ġthe".to_owned(), 4),
            ("Ġ".to_owned(), 5),
            ("<unk>".to_owned(), 6),
            ("o@@".to_owned(), 7),
            ("<s>".to_owned(), 8),
            ("</s>".to_owned(), 9),
            ("<pad>".to_owned(), 10),
            ("<mask>".to_owned(), 11),
            ("Ġear".to_owned(), 12),
            ("th".to_owned(), 13),
        ].iter().cloned().collect();

        let special_values: HashMap<String, i64> = [
            ("<unk>".to_owned(), 6),
            ("<s>".to_owned(), 8),
            ("</s>".to_owned(), 9),
            ("<pad>".to_owned(), 10),
            ("<mask>".to_owned(), 11),
        ].iter().cloned().collect();

        let indices = swap_key_values(&values);
        let special_indices = swap_key_values(&special_values);

        RobertaVocab { values, indices, unknown_value: "<unk>", 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_roberta_tokenizer() {
//        Given
        let vocab = Rc::new(generate_test_vocab());
        let merges = Rc::new(generate_test_merges());
        let roberta_tokenizer: RobertaTokenizer = RobertaTokenizer::from_existing_vocab_and_merges(vocab, merges, true);
        let test_tuples = [
            (
                "The Earth",
                vec!("Ġthe", "Ġear", "th"),
                vec!(Some(Offset { begin: 0, end: 3 }), Some(Offset { begin: 3, end: 7 }), Some(Offset { begin: 7, end: 9 })),
                vec!(vec!(0, 0, 1, 2), vec!(3, 4, 5, 6), vec!(7, 8)),
                vec!(Mask::None, Mask::Begin, Mask::Continuation)
            ),
            (
                "",
                vec!(),
                vec!(),
                vec!(),
                vec!()
            ),
            (
                "✿",
                vec!("Ġ", "â", "ľ", "¿"),
                vec!(Some(Offset { begin: 0, end: 1 }), Some(Offset { begin: 0, end: 1 }), Some(Offset { begin: 0, end: 1 }), Some(Offset { begin: 0, end: 1 })),
                vec!(vec!(0), vec!(0), vec!(0), vec!(0)),
                vec!(Mask::Begin, Mask::Continuation, Mask::Continuation, Mask::Continuation)
            ),
        ];
        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();

//        When & Then
        for (source_text, expected_tokens, expected_offsets, expected_original_offsets, expected_mask) in test_tuples.iter() {
            let (tokens, offsets, original_offsets, mask) = roberta_tokenizer.tokenize_with_offsets(*source_text);
            assert_eq!(tokens, *expected_tokens);
            assert_eq!(offsets, *expected_offsets);
            assert_eq!(original_offsets, *expected_original_offsets);
            assert_eq!(mask, *expected_mask);
        }

        assert_eq!(roberta_tokenizer.tokenize_list(source_texts.clone()), expected_results);
    }

    #[test]
    fn test_roberta_tokenizer_no_lower_casing() {
//        Given
        let vocab = Rc::new(generate_test_vocab());
        let merges = Rc::new(generate_test_merges());
        let roberta_tokenizer: RobertaTokenizer = RobertaTokenizer::from_existing_vocab_and_merges(vocab, merges, false);
        let test_tuples = [
            (
                "The Earth",
                vec!("Ġ", "T", "he", "Ġ", "E", "a", "r", "th"),
                vec!(Some(Offset { begin: 0, end: 1 }), Some(Offset { begin: 0, end: 1 }), Some(Offset { begin: 1, end: 3 }), Some(Offset { begin: 3, end: 4 }), Some(Offset { begin: 4, end: 5 }), Some(Offset { begin: 5, end: 6 }), Some(Offset { begin: 6, end: 7 }), Some(Offset { begin: 7, end: 9 })), //note: first inserted whitespace has offset (0,0), which will map to Option::None in further encoding
                vec!(vec!(0), vec!(0), vec!(1, 2), vec!(3), vec!(4), vec!(5), vec!(6), vec!(7, 8)),
                vec!(Mask::Begin, Mask::Continuation, Mask::Continuation, Mask::Begin, Mask::Continuation, Mask::Continuation, Mask::Continuation, Mask::Continuation)
            ),
            (
                "",
                vec!(),
                vec!(),
                vec!(),
                vec!()
            ),
            (
                "✿",
                vec!("Ġ", "â", "ľ", "¿"),
                vec!(Some(Offset { begin: 0, end: 1 }), Some(Offset { begin: 0, end: 1 }), Some(Offset { begin: 0, end: 1 }), Some(Offset { begin: 0, end: 1 })),
                vec!(vec!(0), vec!(0), vec!(0), vec!(0)),
                vec!(Mask::Begin, Mask::Continuation, Mask::Continuation, Mask::Continuation)
            ),
        ];
        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();

//        When & Then
        for (source_text, expected_tokens, expected_offsets, expected_original_offsets, expected_mask) in test_tuples.iter() {
            let (tokens, offsets, original_offsets, mask) = roberta_tokenizer.tokenize_with_offsets(*source_text);
            assert_eq!(tokens, *expected_tokens);
            assert_eq!(offsets, *expected_offsets);
            assert_eq!(original_offsets, *expected_original_offsets);
            assert_eq!(mask, *expected_mask);
        }

        assert_eq!(roberta_tokenizer.tokenize_list(source_texts.clone()), expected_results);
    }


    #[test]
    fn test_encode() {
//        Given
        let vocab = Rc::new(generate_test_vocab());
        let merges = Rc::new(generate_test_merges());
        let roberta_tokenizer: RobertaTokenizer = RobertaTokenizer::from_existing_vocab_and_merges(vocab, merges, true);
        let truncation_strategy = TruncationStrategy::LongestFirst;
        let test_tuples = [
            (
                "the earth",
                TokenizedInput {
                    token_ids: vec!(8, 4, 12, 13, 9),
                    segment_ids: vec!(0, 0, 0, 0, 0),
                    special_tokens_mask: vec!(1, 0, 0, 0, 1),
                    overflowing_tokens: vec!(),
                    num_truncated_tokens: 0,
                    token_offsets: vec!(None, Some(Offset { begin: 0, end: 3 }), Some(Offset { begin: 3, end: 7 }), Some(Offset { begin: 7, end: 9 }), None),
                    reference_offsets: vec!(vec!(), vec!(0, 0, 1, 2), vec!(3, 4, 5, 6), vec!(7, 8), vec!()),
                    mask: vec!(Mask::Special, Mask::None, Mask::Begin, Mask::Continuation, Mask::Special),
                }
            ),
            (
                "✿",
                TokenizedInput {
                    token_ids: vec!(8, 5, 6, 6, 6, 9),
                    segment_ids: vec!(0, 0, 0, 0, 0, 0),
                    special_tokens_mask: vec!(1, 0, 0, 0, 0, 1),
                    overflowing_tokens: vec!(),
                    num_truncated_tokens: 0,
                    token_offsets: vec!(None, Some(Offset { begin: 0, end: 1 }), Some(Offset { begin: 0, end: 1 }), Some(Offset { begin: 0, end: 1 }), Some(Offset { begin: 0, end: 1 }), None),
                    reference_offsets: vec!(vec!(), vec!(0), vec!(0), vec!(0), vec!(0), vec!()),
                    mask: vec!(Mask::Special, Mask::Begin, Mask::Continuation, Mask::Continuation, Mask::Continuation, Mask::Special),
                }
            ),
            (
                "",
                TokenizedInput {
                    token_ids: vec!(8, 9),
                    segment_ids: vec!(0, 0),
                    special_tokens_mask: vec!(1, 1),
                    overflowing_tokens: vec!(),
                    num_truncated_tokens: 0,
                    token_offsets: vec!(None, None),
                    reference_offsets: vec!(vec!(), vec!()),
                    mask: vec!(Mask::Special, Mask::Special),
                }
            )
        ];
        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();

//        When & Then
        for (source_text, expected_result) in test_tuples.iter() {
            assert_eq!(roberta_tokenizer.encode(source_text, None, 128, &truncation_strategy, 0),
                       *expected_result);
        }
        assert_eq!(roberta_tokenizer.encode_list(source_texts.clone(), 128, &truncation_strategy, 0), expected_results);
    }

    #[test]
    fn test_decode() {
//        Given
        let vocab = Rc::new(generate_test_vocab());
        let merges = Rc::new(generate_test_merges());
        let roberta_tokenizer: RobertaTokenizer = RobertaTokenizer::from_existing_vocab_and_merges(vocab, merges, true);
        let skip_special_tokens = false;
        let clean_up_tokenization_spaces = false;
        let test_tuples = [
            (
                vec!(8, 4, 12, 13, 9),
                "<s> the earth</s>",
            )
        ];
        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();

//        When & Then
        for (source_ids, expected_result) in test_tuples.iter() {
            assert_eq!(roberta_tokenizer.decode(source_ids.clone(), skip_special_tokens, clean_up_tokenization_spaces),
                       *expected_result);
        }
        assert_eq!(Tokenizer::decode_list(&roberta_tokenizer, source_ids.clone(), skip_special_tokens, clean_up_tokenization_spaces), expected_results);
    }
}