tokenizer.py

# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# 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.
# Modified from https://github.com/openai/whisper/blob/main/whisper/tokenizer.py
import base64
import os

import tiktoken

LANGUAGES = {
    "en": "english",
    "zh": "chinese",
    "de": "german",
    "es": "spanish",
    "ru": "russian",
    "ko": "korean",
    "fr": "french",
    "ja": "japanese",
    "pt": "portuguese",
    "tr": "turkish",
    "pl": "polish",
    "ca": "catalan",
    "nl": "dutch",
    "ar": "arabic",
    "sv": "swedish",
    "it": "italian",
    "id": "indonesian",
    "hi": "hindi",
    "fi": "finnish",
    "vi": "vietnamese",
    "he": "hebrew",
    "uk": "ukrainian",
    "el": "greek",
    "ms": "malay",
    "cs": "czech",
    "ro": "romanian",
    "da": "danish",
    "hu": "hungarian",
    "ta": "tamil",
    "no": "norwegian",
    "th": "thai",
    "ur": "urdu",
    "hr": "croatian",
    "bg": "bulgarian",
    "lt": "lithuanian",
    "la": "latin",
    "mi": "maori",
    "ml": "malayalam",
    "cy": "welsh",
    "sk": "slovak",
    "te": "telugu",
    "fa": "persian",
    "lv": "latvian",
    "bn": "bengali",
    "sr": "serbian",
    "az": "azerbaijani",
    "sl": "slovenian",
    "kn": "kannada",
    "et": "estonian",
    "mk": "macedonian",
    "br": "breton",
    "eu": "basque",
    "is": "icelandic",
    "hy": "armenian",
    "ne": "nepali",
    "mn": "mongolian",
    "bs": "bosnian",
    "kk": "kazakh",
    "sq": "albanian",
    "sw": "swahili",
    "gl": "galician",
    "mr": "marathi",
    "pa": "punjabi",
    "si": "sinhala",
    "km": "khmer",
    "sn": "shona",
    "yo": "yoruba",
    "so": "somali",
    "af": "afrikaans",
    "oc": "occitan",
    "ka": "georgian",
    "be": "belarusian",
    "tg": "tajik",
    "sd": "sindhi",
    "gu": "gujarati",
    "am": "amharic",
    "yi": "yiddish",
    "lo": "lao",
    "uz": "uzbek",
    "fo": "faroese",
    "ht": "haitian creole",
    "ps": "pashto",
    "tk": "turkmen",
    "nn": "nynorsk",
    "mt": "maltese",
    "sa": "sanskrit",
    "lb": "luxembourgish",
    "my": "myanmar",
    "bo": "tibetan",
    "tl": "tagalog",
    "mg": "malagasy",
    "as": "assamese",
    "tt": "tatar",
    "haw": "hawaiian",
    "ln": "lingala",
    "ha": "hausa",
    "ba": "bashkir",
    "jw": "javanese",
    "su": "sundanese",
    "yue": "cantonese",
}


def get_tokenizer(name: str = "multilingual",
                  num_languages: int = 99,
                  tokenizer_dir: str = None):
    if tokenizer_dir is None:
        vocab_path = os.path.join(os.path.dirname(__file__),
                                  f"assets/{name}.tiktoken")
    else:
        vocab_path = os.path.join(tokenizer_dir, f"{name}.tiktoken")
    ranks = {
        base64.b64decode(token): int(rank)
        for token, rank in (line.split() for line in open(vocab_path) if line)
    }
    n_vocab = len(ranks)
    special_tokens = {}

    specials = [
        "<|endoftext|>",
        "<|startoftranscript|>",
        *[f"<|{lang}|>" for lang in list(LANGUAGES.keys())[:num_languages]],
        "<|translate|>",
        "<|transcribe|>",
        "<|startoflm|>",
        "<|startofprev|>",
        "<|nospeech|>",
        "<|notimestamps|>",
        *[f"<|{i * 0.02:.2f}|>" for i in range(1501)],
    ]

    for token in specials:
        special_tokens[token] = n_vocab
        n_vocab += 1

    return tiktoken.Encoding(
        name=os.path.basename(vocab_path),
        explicit_n_vocab=n_vocab,
        pat_str=
        r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+""",
        mergeable_ranks=ranks,
        special_tokens=special_tokens,
    )


if __name__ == "__main__":
    enc = get_tokenizer()
    mytest_str = "<|startofprev|> Nvidia<|startoftranscript|><|en|><|transcribe|>"
    encoding = enc.encode(mytest_str, allowed_special=enc.special_tokens_set)
    mystr = enc.decode([50361, 45, 43021, 50258, 50259, 50359])
    mystr2 = enc.decode([50361, 46284, 50258, 50259, 50359])
    print(encoding, mystr, mystr2)
    print(
        enc.encode("<|startoftranscript|>",
                   allowed_special=enc.special_tokens_set)[0])

    my_zh_str = "好好学习"
    encoding = enc.encode(my_zh_str, allowed_special=enc.special_tokens_set)
    decoding = enc.decode(encoding)
    print(type(decoding))
    print(encoding, decoding)