'''simple docstring'''

import collections
import os
from typing import List, Optional, Tuple

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
  import jieba

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__a:			Dict	       =       logging.get_logger(__name__)

__a:			int	       =       {"""vocab_file""": """vocab.txt"""}

__a:			Dict	       =       {
    """vocab_file""": {
        """openbmb/cpm-ant-10b""": """https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt""",
    },
}

__a:			Dict	       =       {
    """openbmb/cpm-ant-10b""": 10_24,
}
def       __UpperCamelCase	(       UpperCAmelCase					):
 lowercase__    :   Union[str, Any]						= collections.OrderedDict()
 with open(lowerCamelCase__		,					'''r'''		,					encoding='''utf-8'''					) as reader:
  lowercase__    :   Tuple						= reader.readlines()
 for index, token in enumerate(lowerCamelCase__					):
  lowercase__    :   Tuple						= token.rstrip('''\n'''					)
  lowercase__    :   str						= index
 return vocab



class       UpperCAmelCase  (						snake_case_ ):





       '''simple docstring'''



       def __init__(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase="<unk>"     ,       __lowerCAmelCase=200			)  ->  str:
        lowercase__    :   Optional[int]						= vocab
        lowercase__    :   Any						= unk_token
        lowercase__    :   List[str]						= max_input_chars_per_word


       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  str:
        lowercase__    :   Dict						= list(__lowerCAmelCase			)
        if len(__lowerCAmelCase			) > self.max_input_chars_per_word:
         return [self.unk_token]

        lowercase__    :   int						= 0
        lowercase__    :   Optional[Any]						= []
        while start < len(__lowerCAmelCase			):
         lowercase__    :   int						= len(__lowerCAmelCase			)
         lowercase__    :   Optional[int]						= None
         while start < end:
          lowercase__    :   str						= ''''''.join(chars[start:end]			)
          if substr in self.vocab:
           lowercase__    :   Dict						= substr
           break
          end -= 1
         if cur_substr is None:
          sub_tokens.append(self.unk_token			)
          start += 1
         else:
          sub_tokens.append(__lowerCAmelCase			)
          lowercase__    :   Optional[int]						= end

        return sub_tokens



class       UpperCAmelCase  (						snake_case_ ):





       '''simple docstring'''



       SCREAMING_SNAKE_CASE 		=   VOCAB_FILES_NAMES
       SCREAMING_SNAKE_CASE 		=   PRETRAINED_VOCAB_FILES_MAP
       SCREAMING_SNAKE_CASE 		=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       SCREAMING_SNAKE_CASE 		=   ["input_ids", "attention_mask"]
       SCREAMING_SNAKE_CASE 		=   False

       def __init__(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase="<d>"     ,       __lowerCAmelCase="</d>"     ,       __lowerCAmelCase="<s>"     ,       __lowerCAmelCase="</s>"     ,       __lowerCAmelCase="<pad>"     ,       __lowerCAmelCase="<unk>"     ,       __lowerCAmelCase="</n>"     ,       __lowerCAmelCase="</_>"     ,       __lowerCAmelCase="left"     ,       **__lowerCAmelCase     ,       )  ->  List[Any]:
        requires_backends(self     ,       ['''jieba''']			)
        super().__init__(
            bod_token=__lowerCAmelCase     ,       eod_token=__lowerCAmelCase     ,       bos_token=__lowerCAmelCase     ,       eos_token=__lowerCAmelCase     ,       pad_token=__lowerCAmelCase     ,       unk_token=__lowerCAmelCase     ,       line_token=__lowerCAmelCase     ,       space_token=__lowerCAmelCase     ,       padding_side=__lowerCAmelCase     ,       **__lowerCAmelCase     ,       )
        lowercase__    :   Tuple						= bod_token
        lowercase__    :   Dict						= eod_token
        lowercase__    :   Optional[Any]						= load_vocab(__lowerCAmelCase			)
        lowercase__    :   Optional[Any]						= self.encoder[space_token]
        lowercase__    :   List[Any]						= self.encoder[line_token]

        del self.encoder[space_token]
        del self.encoder[line_token]

        lowercase__    :   List[str]						= collections.OrderedDict(sorted(self.encoder.items()     ,       key=lambda __lowerCAmelCase			: x[1]			)			)
        lowercase__    :   Any						= {v: k for k, v in self.encoder.items()}

        lowercase__    :   Any						= WordpieceTokenizer(vocab=self.encoder     ,       unk_token=self.unk_token			)

       @property
       def _lowerCAmelCase(						self			)  ->  Tuple:
        return self.encoder[self.bod_token]

       @property
       def _lowerCAmelCase(						self			)  ->  Optional[int]:
        return self.encoder[self.eod_token]

       @property
       def _lowerCAmelCase(						self			)  ->  Optional[int]:
        return self.encoder["\n"]

       @property
       def _lowerCAmelCase(						self			)  ->  int:
        return len(self.encoder			)

       def _lowerCAmelCase(						self			)  ->  Dict:
        return dict(self.encoder     ,       **self.added_tokens_encoder			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  Optional[int]:
        lowercase__    :   int						= []
        for x in jieba.cut(__lowerCAmelCase     ,       cut_all=__lowerCAmelCase			):
         output_tokens.extend(self.wordpiece_tokenizer.tokenize(__lowerCAmelCase			)			)
        return output_tokens

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase     ,       **__lowerCAmelCase			)  ->  Tuple:
        lowercase__    :   Dict						= [i for i in token_ids if i >= 0]
        lowercase__    :   Tuple						= [
            x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
        ]
        return super()._decode(__lowerCAmelCase     ,       **__lowerCAmelCase			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  Union[str, Any]:
        return token in self.encoder

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  str:
        return "".join(__lowerCAmelCase			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  Dict:
        return self.encoder.get(__lowerCAmelCase     ,       self.encoder.get(self.unk_token			)			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  Optional[Any]:
        return self.decoder.get(__lowerCAmelCase     ,       self.unk_token			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase = None			)  ->  Tuple[str]:
        if os.path.isdir(__lowerCAmelCase			):
         lowercase__    :   int						= os.path.join(
             __lowerCAmelCase     ,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']			)
        else:
         lowercase__    :   Tuple						= (filename_prefix + '''-''' if filename_prefix else '''''') + save_directory
        lowercase__    :   str						= 0
        if " " in self.encoder:
         lowercase__    :   Optional[Any]						= self.encoder[''' ''']
         del self.encoder[" "]
        if "\n" in self.encoder:
         lowercase__    :   Union[str, Any]						= self.encoder['''\n''']
         del self.encoder["\n"]
        lowercase__    :   Any						= collections.OrderedDict(sorted(self.encoder.items()     ,       key=lambda __lowerCAmelCase			: x[1]			)			)
        with open(__lowerCAmelCase     ,       '''w'''     ,       encoding='''utf-8'''			) as writer:
         for token, token_index in self.encoder.items():
          if index != token_index:
           logger.warning(
               F"""Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive."""
               ''' Please check that the vocabulary is not corrupted!'''			)
           lowercase__    :   str						= token_index
          writer.write(token + '''\n'''			)
          index += 1
        return (vocab_file,)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase = None			)  ->  List[int]:
        if token_ids_a is None:
         return [self.bos_token_id] + token_ids_a
        return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a


       def _lowerCAmelCase(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase = None     ,       __lowerCAmelCase = False			)  ->  List[int]:

        if already_has_special_tokens:
         return super().get_special_tokens_mask(
             token_ids_a=__lowerCAmelCase     ,       token_ids_a=__lowerCAmelCase     ,       already_has_special_tokens=__lowerCAmelCase			)

        if token_ids_a is not None:
         return [1] + ([0] * len(__lowerCAmelCase			)) + [1] + ([0] * len(__lowerCAmelCase			))
        return [1] + ([0] * len(__lowerCAmelCase			))


'''simple docstring'''

import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('''dataset_size'''		,					[None, 400 * 2**20, 600 * 2**20]					)
@pytest.mark.parametrize('''input_in_memory_max_size'''		,					['''default''', 0, 100 * 2**20, 900 * 2**20]					)
def       __UpperCamelCase	(       UpperCAmelCase		,					UpperCAmelCase		,					UpperCAmelCase					):
 if input_in_memory_max_size != "default":
  monkeypatch.setattr(datasets.config		,					'''IN_MEMORY_MAX_SIZE'''		,					UpperCAmelCase					)
 lowercase__    :   List[Any]						= datasets.config.IN_MEMORY_MAX_SIZE
 if input_in_memory_max_size == "default":
  assert in_memory_max_size == 0
 else:
  assert in_memory_max_size == input_in_memory_max_size
 if dataset_size and in_memory_max_size:
  lowercase__    :   str						= dataset_size < in_memory_max_size
 else:
  lowercase__    :   Optional[int]						= False
 lowercase__    :   Optional[Any]						= is_small_dataset(UpperCAmelCase					)
 assert result == expected

