




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


UpperCamelCase								=					logging.get_logger(__name__)

UpperCamelCase								=					{'vocab_file': 'vocab.txt'}

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

UpperCamelCase								=					{
    'openbmb/cpm-ant-10b': 1024,
}



def 							_A       (						lowerCAmelCase_					: Optional[Any]      ):
     """simple docstring"""

     lowerCAmelCase__          =			collections.OrderedDict()
     with open(lowerCAmelCase_       ,    "r"       ,    encoding="utf-8"      ) as reader:
          lowerCAmelCase__          =			reader.readlines()
     for index, token in enumerate(lowerCAmelCase_      ):
          lowerCAmelCase__          =			token.rstrip("\n"      )
          lowerCAmelCase__          =			index
     return vocab





class 			__lowerCamelCase	(   UpperCamelCase__   ):




    """simple docstring"""

    def __init__(	self					:					Optional[int]       ,     SCREAMING_SNAKE_CASE__					:					Optional[Any]       ,     SCREAMING_SNAKE_CASE__					:					Optional[Any]="<unk>"       ,     SCREAMING_SNAKE_CASE__					:					str=200       )				->	Tuple:
         lowerCAmelCase__          =			vocab
         lowerCAmelCase__          =			unk_token
         lowerCAmelCase__          =			max_input_chars_per_word


    def        a				(	self					:					str       ,     SCREAMING_SNAKE_CASE__					:					Tuple       )				->	List[str]:
         lowerCAmelCase__          =			list(SCREAMING_SNAKE_CASE__       )
         if len(SCREAMING_SNAKE_CASE__       ) > self.max_input_chars_per_word:
              return [self.unk_token]

         lowerCAmelCase__          =			0
         lowerCAmelCase__          =			[]
         while start < len(SCREAMING_SNAKE_CASE__       ):
              lowerCAmelCase__          =			len(SCREAMING_SNAKE_CASE__       )
              lowerCAmelCase__          =			None
              while start < end:
                   lowerCAmelCase__          =			"".join(chars[start:end]       )
                   if substr in self.vocab:
                        lowerCAmelCase__          =			substr
                        break
                   end -= 1
              if cur_substr is None:
                   sub_tokens.append(self.unk_token       )
                   start += 1
              else:
                   sub_tokens.append(SCREAMING_SNAKE_CASE__       )
                   lowerCAmelCase__          =			end

         return sub_tokens






class 			__lowerCamelCase	(   UpperCamelCase__   ):




    """simple docstring"""

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


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

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

         lowerCAmelCase__          =			collections.OrderedDict(sorted(self.encoder.items()       ,     key=lambda SCREAMING_SNAKE_CASE__       : x[1]       )       )
         lowerCAmelCase__          =			{v: k for k, v in self.encoder.items()}

         lowerCAmelCase__          =			WordpieceTokenizer(vocab=self.encoder       ,     unk_token=self.unk_token       )


    @property
    def        a				(	self					:					str       )				->	Any:
         return self.encoder[self.bod_token]


    @property
    def        a				(	self					:					List[Any]       )				->	Tuple:
         return self.encoder[self.eod_token]


    @property
    def        a				(	self					:					Optional[int]       )				->	Union[str, Any]:
         return self.encoder["\n"]


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


    def        a				(	self					:					Union[str, Any]       )				->	int:
         return dict(self.encoder       ,     **self.added_tokens_encoder       )


    def        a				(	self					:					List[Any]       ,     SCREAMING_SNAKE_CASE__					:					List[str]       )				->	List[Any]:
         lowerCAmelCase__          =			[]
         for x in jieba.cut(SCREAMING_SNAKE_CASE__       ,     cut_all=SCREAMING_SNAKE_CASE__       ):
              output_tokens.extend(self.wordpiece_tokenizer.tokenize(SCREAMING_SNAKE_CASE__       )       )
         return output_tokens


    def        a				(	self					:					Tuple       ,     SCREAMING_SNAKE_CASE__					:					Any       ,     **SCREAMING_SNAKE_CASE__					:					Optional[int]       )				->	Union[str, Any]:
         lowerCAmelCase__          =			[i for i in token_ids if i >= 0]
         lowerCAmelCase__          =			[
             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(SCREAMING_SNAKE_CASE__       ,     **SCREAMING_SNAKE_CASE__       )


    def        a				(	self					:					int       ,     SCREAMING_SNAKE_CASE__					:					Tuple       )				->	Tuple:
         return token in self.encoder


    def        a				(	self					:					int       ,     SCREAMING_SNAKE_CASE__					:					List[str]       )				->	str:
         return "".join(SCREAMING_SNAKE_CASE__       )


    def        a				(	self					:					List[Any]       ,     SCREAMING_SNAKE_CASE__					:					Dict       )				->	Optional[Any]:
         return self.encoder.get(SCREAMING_SNAKE_CASE__       ,     self.encoder.get(self.unk_token       )       )


    def        a				(	self					:					Union[str, Any]       ,     SCREAMING_SNAKE_CASE__					:					List[Any]       )				->	List[str]:
         return self.decoder.get(SCREAMING_SNAKE_CASE__       ,     self.unk_token       )


    def        a				(	self					:					Optional[Any]       ,     SCREAMING_SNAKE_CASE__					:					str       ,     SCREAMING_SNAKE_CASE__					:					Optional[str] = None       )				->	Tuple[str]:
         if os.path.isdir(SCREAMING_SNAKE_CASE__       ):
              lowerCAmelCase__          =			os.path.join(
                  SCREAMING_SNAKE_CASE__       ,     (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]       )
         else:
              lowerCAmelCase__          =			(filename_prefix + "-" if filename_prefix else "") + save_directory
         lowerCAmelCase__          =			0
         if " " in self.encoder:
              lowerCAmelCase__          =			self.encoder[" "]
              del self.encoder[" "]
         if "\n" in self.encoder:
              lowerCAmelCase__          =			self.encoder["\n"]
              del self.encoder["\n"]
         lowerCAmelCase__          =			collections.OrderedDict(sorted(self.encoder.items()       ,     key=lambda SCREAMING_SNAKE_CASE__       : x[1]       )       )
         with open(SCREAMING_SNAKE_CASE__       ,     "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!"       )
                        lowerCAmelCase__          =			token_index
                   writer.write(token + "\n"       )
                   index += 1
         return (vocab_file,)


    def        a				(	self					:					Optional[int]       ,     SCREAMING_SNAKE_CASE__					:					List[int]       ,     SCREAMING_SNAKE_CASE__					:					List[int] = 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        a				(	self					:					Union[str, Any]       ,     SCREAMING_SNAKE_CASE__					:					List[int]       ,     SCREAMING_SNAKE_CASE__					:					Optional[List[int]] = None       ,     SCREAMING_SNAKE_CASE__					:					bool = False       )				->	List[int]:

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

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






import time
from contextlib import contextmanager
from pathlib import Path

import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder


UpperCamelCase								=					'__DUMMY_TRANSFORMERS_USER__'
UpperCamelCase								=					'Dummy User'
UpperCamelCase								=					'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'

UpperCamelCase								=					'https://hub-ci.huggingface.co'
UpperCamelCase								=					CI_HUB_ENDPOINT + '/datasets/{repo_id}/resolve/{revision}/{path}'
UpperCamelCase								=					CI_HUB_ENDPOINT + '/{repo_id}/resolve/{revision}/{filename}'
UpperCamelCase								=					Path('~/.huggingface/hub_ci_token').expanduser()



@pytest.fixture
def 							_A       (						lowerCAmelCase_					: Dict      ):
     """simple docstring"""

     monkeypatch.setattr(
         "huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE"       ,    lowerCAmelCase_      )



@pytest.fixture
def 							_A       (						lowerCAmelCase_					: int      ):
     """simple docstring"""

     monkeypatch.setattr("datasets.config.HF_ENDPOINT"       ,    lowerCAmelCase_      )
     monkeypatch.setattr("datasets.config.HUB_DATASETS_URL"       ,    lowerCAmelCase_      )



@pytest.fixture
def 							_A       (						lowerCAmelCase_					: str      ):
     """simple docstring"""

     monkeypatch.setattr("huggingface_hub.hf_api.HfFolder.path_token"       ,    lowerCAmelCase_      )



@pytest.fixture
def 							_A       (						lowerCAmelCase_					: int       ,    lowerCAmelCase_					: List[Any]      ):
     """simple docstring"""

     HfFolder.save_token(lowerCAmelCase_      )
     yield
     HfFolder.delete_token()



@pytest.fixture(scope="session"      )
def 							_A       (						):
     """simple docstring"""

     return HfApi(endpoint=lowerCAmelCase_      )



@pytest.fixture(scope="session"      )
def 							_A       (						lowerCAmelCase_					: HfApi      ):
     """simple docstring"""

     lowerCAmelCase__          =			HfFolder.get_token()
     HfFolder.save_token(lowerCAmelCase_      )
     yield CI_HUB_USER_TOKEN
     if previous_token is not None:
          HfFolder.save_token(lowerCAmelCase_      )



@pytest.fixture
def 							_A       (						lowerCAmelCase_					: Tuple      ):
     """simple docstring"""

     def _cleanup_repo(lowerCAmelCase_					: Optional[Any]      ):
          hf_api.delete_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"      )

     return _cleanup_repo



@pytest.fixture
def 							_A       (						lowerCAmelCase_					: Union[str, Any]      ):
     """simple docstring"""

     @contextmanager
     def _temporary_repo(lowerCAmelCase_					: str      ):
          try:
               yield repo_id
          finally:
               cleanup_repo(lowerCAmelCase_      )

     return _temporary_repo



@pytest.fixture(scope="session"      )
def 							_A       (						lowerCAmelCase_					: HfApi       ,    lowerCAmelCase_					: Union[str, Any]       ,    lowerCAmelCase_					: Any      ):
     """simple docstring"""

     lowerCAmelCase__          =			F'repo_txt_data-{int(time.time() * 1_0E3      )}'
     lowerCAmelCase__          =			F'{CI_HUB_USER}/{repo_name}'
     hf_api.create_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"       ,    private=lowerCAmelCase_      )
     hf_api.upload_file(
         token=lowerCAmelCase_       ,    path_or_fileobj=str(lowerCAmelCase_      )       ,    path_in_repo="data/text_data.txt"       ,    repo_id=lowerCAmelCase_       ,    repo_type="dataset"       ,    )
     yield repo_id
     try:
          hf_api.delete_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"      )
     except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
          pass



@pytest.fixture()
def 							_A       (						lowerCAmelCase_					: Optional[Any]       ,    lowerCAmelCase_					: Optional[Any]       ,    lowerCAmelCase_					: int      ):
     """simple docstring"""

     return hf_private_dataset_repo_txt_data_



@pytest.fixture(scope="session"      )
def 							_A       (						lowerCAmelCase_					: HfApi       ,    lowerCAmelCase_					: Tuple       ,    lowerCAmelCase_					: Tuple      ):
     """simple docstring"""

     lowerCAmelCase__          =			F'repo_zipped_txt_data-{int(time.time() * 1_0E3      )}'
     lowerCAmelCase__          =			F'{CI_HUB_USER}/{repo_name}'
     hf_api.create_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"       ,    private=lowerCAmelCase_      )
     hf_api.upload_file(
         token=lowerCAmelCase_       ,    path_or_fileobj=str(lowerCAmelCase_      )       ,    path_in_repo="data.zip"       ,    repo_id=lowerCAmelCase_       ,    repo_type="dataset"       ,    )
     yield repo_id
     try:
          hf_api.delete_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"      )
     except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
          pass



@pytest.fixture()
def 							_A       (						lowerCAmelCase_					: int       ,    lowerCAmelCase_					: List[str]       ,    lowerCAmelCase_					: Tuple      ):
     """simple docstring"""

     return hf_private_dataset_repo_zipped_txt_data_



@pytest.fixture(scope="session"      )
def 							_A       (						lowerCAmelCase_					: HfApi       ,    lowerCAmelCase_					: List[str]       ,    lowerCAmelCase_					: int      ):
     """simple docstring"""

     lowerCAmelCase__          =			F'repo_zipped_img_data-{int(time.time() * 1_0E3      )}'
     lowerCAmelCase__          =			F'{CI_HUB_USER}/{repo_name}'
     hf_api.create_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"       ,    private=lowerCAmelCase_      )
     hf_api.upload_file(
         token=lowerCAmelCase_       ,    path_or_fileobj=str(lowerCAmelCase_      )       ,    path_in_repo="data.zip"       ,    repo_id=lowerCAmelCase_       ,    repo_type="dataset"       ,    )
     yield repo_id
     try:
          hf_api.delete_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"      )
     except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
          pass






@pytest.fixture()
def 							_A       (						lowerCAmelCase_					: Optional[Any]       ,    lowerCAmelCase_					: Dict       ,    lowerCAmelCase_					: List[str]      ):
     """simple docstring"""

     return hf_private_dataset_repo_zipped_img_data_
