
import argparse
import os

import transformers

from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging


logging.set_verbosity_info()

_A						      =				logging.get_logger(__name__)


_A						      =				{name: getattr(transformers, name + "Fast") for name in SLOW_TO_FAST_CONVERTERS}



def 		lowercase_    (     A__				,	A__				,	A__				,	A__	)							->							int:
    """simple docstring"""

    if tokenizer_name is not None and tokenizer_name not in TOKENIZER_CLASSES:
        raise ValueError(F'Unrecognized tokenizer name, should be one of {list(TOKENIZER_CLASSES.keys()	)}.'	)

    if tokenizer_name is None:
        snake_case				  =      TOKENIZER_CLASSES
    else:
        snake_case				  =      {tokenizer_name: getattr(__a				,	tokenizer_name + "Fast"	)}

    logger.info(F'Loading tokenizer classes: {tokenizer_names}'	)

    for tokenizer_name in tokenizer_names:
        snake_case				  =      TOKENIZER_CLASSES[tokenizer_name]

        snake_case				  =      True
        if checkpoint_name is None:
            snake_case				  =      list(tokenizer_class.max_model_input_sizes.keys()	)
        else:
            snake_case				  =      [checkpoint_name]

        logger.info(F'For tokenizer {tokenizer_class.__class__.__name__} loading checkpoints: {checkpoint_names}'	)

        for checkpoint in checkpoint_names:
            logger.info(F'Loading {tokenizer_class.__class__.__name__} {checkpoint}'	)

            # Load tokenizer
            snake_case				  =      tokenizer_class.from_pretrained(__a				,	force_download=__a	)

            # Save fast tokenizer
            logger.info(F'Save fast tokenizer to {dump_path} with prefix {checkpoint} add_prefix {add_prefix}'	)

            # For organization names we create sub-directories
            if "/" in checkpoint:
                snake_case  ,							snake_case				  =      checkpoint.split("/"	)
                snake_case				  =      os.path.join(__a				,	__a	)
            elif add_prefix:
                snake_case				  =      checkpoint
                snake_case				  =      dump_path
            else:
                snake_case				  =      None
                snake_case				  =      dump_path

            logger.info(F'=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}'	)

            if checkpoint in list(tokenizer.pretrained_vocab_files_map.values()	)[0]:
                snake_case				  =      list(tokenizer.pretrained_vocab_files_map.values()	)[0][checkpoint]
                snake_case				  =      file_path.split(__a	)[-1][0]
                if next_char == "/":
                    snake_case				  =      os.path.join(__a				,	__a	)
                    snake_case				  =      None

                logger.info(F'=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}'	)

            snake_case				  =      tokenizer.save_pretrained(
                __a				,	legacy_format=__a				,	filename_prefix=__a	)
            logger.info(F'=> File names {file_names}'	)

            for file_name in file_names:
                if not file_name.endswith("tokenizer.json"	):
                    os.remove(__a	)
                    logger.info(F'=> removing {file_name}'	)


if __name__ == "__main__":
    _A						      =				argparse.ArgumentParser()
    # Required parameters
    parser.add_argument(
        "--dump_path", default=None, type=str, required=True, help="Path to output generated fast tokenizer files."
    )
    parser.add_argument(
        "--tokenizer_name",
        default=None,
        type=str,
        help=(
            f"Optional tokenizer type selected in the list of {list(TOKENIZER_CLASSES.keys())}. If not given, will "
            "download and convert all the checkpoints from AWS."
        ),
    )
    parser.add_argument(
        "--checkpoint_name",
        default=None,
        type=str,
        help="Optional checkpoint name. If not given, will download and convert the canonical checkpoints from AWS.",
    )
    parser.add_argument(
        "--force_download",
        action="store_true",
        help="Re-download checkpoints.",
    )
    _A						      =				parser.parse_args()

    convert_slow_checkpoint_to_fast(args.tokenizer_name, args.checkpoint_name, args.dump_path, args.force_download)



import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin







class   lowerCamelCase	(						A_							,				unittest.TestCase						):
     UpperCAmelCase__       :							str     =	PhobertTokenizer
     UpperCAmelCase__       :							List[Any]     =	False





     def 	UpperCAmelCase(self   :					Union[str, Any]     )		->		List[str]:
         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         snake_case				  =      ["T@@", "i", "I", "R@@", "r", "e@@"]
         snake_case				  =      dict(zip(_A       ,					range(len(_A     )     )     )     )
         snake_case				  =      ["#version: 0.2", "l à</w>"]
         snake_case				  =      {"unk_token": "<unk>"}

         snake_case				  =      os.path.join(self.tmpdirname       ,					VOCAB_FILES_NAMES["vocab_file"]     )
         snake_case				  =      os.path.join(self.tmpdirname       ,					VOCAB_FILES_NAMES["merges_file"]     )

         with open(self.vocab_file       ,					"w"       ,					encoding="utf-8"     ) as fp:
             for token in vocab_tokens:
                 fp.write(f'{token} {vocab_tokens[token]}\n'     )
         with open(self.merges_file       ,					"w"       ,					encoding="utf-8"     ) as fp:
             fp.write("\n".join(_A     )     )





     def 	UpperCAmelCase(self   :					Optional[int]       ,					**_A   :					Optional[int]     )		->		Union[str, Any]:
         kwargs.update(self.special_tokens_map     )
         return PhobertTokenizer.from_pretrained(self.tmpdirname       ,					**_A     )





     def 	UpperCAmelCase(self   :					Tuple       ,					_A   :					Optional[Any]     )		->		str:
         snake_case				  =      "Tôi là VinAI Research"
         snake_case				  =      "T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"
         return input_text, output_text





     def 	UpperCAmelCase(self   :					Any     )		->		Union[str, Any]:
         snake_case				  =      PhobertTokenizer(self.vocab_file       ,					self.merges_file       ,					**self.special_tokens_map     )
         snake_case				  =      "Tôi là VinAI Research"
         snake_case				  =      "T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h".split()
         snake_case				  =      tokenizer.tokenize(_A     )
         print(_A     )
         self.assertListEqual(_A       ,					_A     )

         snake_case				  =      tokens + [tokenizer.unk_token]

         snake_case				  =      [4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(_A     )       ,					_A     )

