
import time
from contextlib import contextmanager
from pathlib import Path

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


__snake_case								=  """__DUMMY_TRANSFORMERS_USER__"""
__snake_case								=  """Dummy User"""
__snake_case								=  """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"""

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






@pytest.fixture
def 							_lowercase							(     UpperCamelCase_		)		->		List[str]:
					'''simple docstring'''


					monkeypatch.setattr(
					    'huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE'	,	_UpperCAmelCase		)






@pytest.fixture
def 							_lowercase							(     UpperCamelCase_		)		->		Any:
					'''simple docstring'''


					monkeypatch.setattr('datasets.config.HF_ENDPOINT'	,	_UpperCAmelCase		)
					monkeypatch.setattr('datasets.config.HUB_DATASETS_URL'	,	_UpperCAmelCase		)






@pytest.fixture
def 							_lowercase							(     UpperCamelCase_		)		->		List[str]:
					'''simple docstring'''


					monkeypatch.setattr('huggingface_hub.hf_api.HfFolder.path_token'	,	_UpperCAmelCase		)






@pytest.fixture
def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_		)		->		List[Any]:
					'''simple docstring'''


					HfFolder.save_token(_UpperCAmelCase		)
					yield
					HfFolder.delete_token()






@pytest.fixture(scope='session'		)
def 							_lowercase							(     )		->		List[str]:
					'''simple docstring'''


					return HfApi(endpoint=_UpperCAmelCase		)






@pytest.fixture(scope='session'		)
def 							_lowercase							(     UpperCamelCase_		)		->		Any:
					'''simple docstring'''


					SCREAMING_SNAKE_CASE__													= HfFolder.get_token()
					HfFolder.save_token(_UpperCAmelCase		)
					yield CI_HUB_USER_TOKEN
					if previous_token is not None:
										HfFolder.save_token(_UpperCAmelCase		)






@pytest.fixture
def 							_lowercase							(     UpperCamelCase_		)		->		Tuple:
					'''simple docstring'''


					def _cleanup_repo(UpperCamelCase_		):
										hf_api.delete_repo(_UpperCAmelCase	,	token=_UpperCAmelCase	,	repo_type='dataset'		)

					return _cleanup_repo






@pytest.fixture
def 							_lowercase							(     UpperCamelCase_		)		->		Any:
					'''simple docstring'''


					@contextmanager
					def _temporary_repo(UpperCamelCase_		):
										try:
															yield repo_id
										finally:
															cleanup_repo(_UpperCAmelCase		)

					return _temporary_repo






@pytest.fixture(scope='session'		)
def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)		->		str:
					'''simple docstring'''


					SCREAMING_SNAKE_CASE__													= F'repo_txt_data-{int(time.time() * 10e3		)}'
					SCREAMING_SNAKE_CASE__													= F'{CI_HUB_USER}/{repo_name}'
					hf_api.create_repo(_UpperCAmelCase	,	token=_UpperCAmelCase	,	repo_type='dataset'	,	private=_UpperCAmelCase		)
					hf_api.upload_file(
					    token=_UpperCAmelCase	,	path_or_fileobj=str(_UpperCAmelCase		)	,	path_in_repo='data/text_data.txt'	,	repo_id=_UpperCAmelCase	,	repo_type='dataset'	,	)
					yield repo_id
					try:
										hf_api.delete_repo(_UpperCAmelCase	,	token=_UpperCAmelCase	,	repo_type='dataset'		)
					except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
										pass






@pytest.fixture()
def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)		->		Union[str, Any]:
					'''simple docstring'''


					return hf_private_dataset_repo_txt_data_






@pytest.fixture(scope='session'		)
def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)		->		Tuple:
					'''simple docstring'''


					SCREAMING_SNAKE_CASE__													= F'repo_zipped_txt_data-{int(time.time() * 10e3		)}'
					SCREAMING_SNAKE_CASE__													= F'{CI_HUB_USER}/{repo_name}'
					hf_api.create_repo(_UpperCAmelCase	,	token=_UpperCAmelCase	,	repo_type='dataset'	,	private=_UpperCAmelCase		)
					hf_api.upload_file(
					    token=_UpperCAmelCase	,	path_or_fileobj=str(_UpperCAmelCase		)	,	path_in_repo='data.zip'	,	repo_id=_UpperCAmelCase	,	repo_type='dataset'	,	)
					yield repo_id
					try:
										hf_api.delete_repo(_UpperCAmelCase	,	token=_UpperCAmelCase	,	repo_type='dataset'		)
					except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
										pass






@pytest.fixture()
def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)		->		Dict:
					'''simple docstring'''


					return hf_private_dataset_repo_zipped_txt_data_






@pytest.fixture(scope='session'		)
def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)		->		Dict:
					'''simple docstring'''


					SCREAMING_SNAKE_CASE__													= F'repo_zipped_img_data-{int(time.time() * 10e3		)}'
					SCREAMING_SNAKE_CASE__													= F'{CI_HUB_USER}/{repo_name}'
					hf_api.create_repo(_UpperCAmelCase	,	token=_UpperCAmelCase	,	repo_type='dataset'	,	private=_UpperCAmelCase		)
					hf_api.upload_file(
					    token=_UpperCAmelCase	,	path_or_fileobj=str(_UpperCAmelCase		)	,	path_in_repo='data.zip'	,	repo_id=_UpperCAmelCase	,	repo_type='dataset'	,	)
					yield repo_id
					try:
										hf_api.delete_repo(_UpperCAmelCase	,	token=_UpperCAmelCase	,	repo_type='dataset'		)
					except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
										pass






@pytest.fixture()
def 							_lowercase							(     UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_		)		->		Optional[int]:
					'''simple docstring'''


					return hf_private_dataset_repo_zipped_img_data_






'''simple docstring'''




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
  from .tokenization_pegasus import PegasusTokenizer
else:
  __SCREAMING_SNAKE_CASE       :     Optional[Any]     =  None


__SCREAMING_SNAKE_CASE       :     Dict     =  logging.get_logger(__name__)


__SCREAMING_SNAKE_CASE       :     Union[str, Any]     =  """▁"""

__SCREAMING_SNAKE_CASE       :     str     =  {"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

__SCREAMING_SNAKE_CASE       :     int     =  {
    """vocab_file""": {"""google/pegasus-xsum""": """https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model"""},
    """tokenizer_file""": {
        """google/pegasus-xsum""": """https://huggingface.co/google/pegasus-xsum/resolve/main/tokenizer.json"""
    },
}

__SCREAMING_SNAKE_CASE       :     str     =  {
    """google/pegasus-xsum""": 512,
}

class 	lowerCamelCase_	(snake_case__    ):
      '''simple docstring'''

      __UpperCamelCase:  Optional[int]						=						VOCAB_FILES_NAMES
      __UpperCamelCase:  Dict						=						PRETRAINED_VOCAB_FILES_MAP
      __UpperCamelCase:  List[Any]						=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __UpperCamelCase:  Optional[int]						=						PegasusTokenizer
      __UpperCamelCase:  Optional[Any]						=						["input_ids", "attention_mask"]




      def __init__(       self						:				Dict						,					A						:				List[str]=None						,					A						:				Union[str, Any]=None						,					A						:				Optional[int]="<pad>"						,					A						:				Tuple="</s>"						,					A						:				Union[str, Any]="<unk>"						,					A						:				Union[str, Any]="<mask_2>"						,					A						:				Dict="<mask_1>"						,					A						:				Union[str, Any]=None						,					A						:				int=103						,					**A						:				Optional[Any]						,					):
             _UpperCAmelCase     :  Dict							      =    offset

             if additional_special_tokens is not None:
                    if not isinstance(A						,					A       ):
                           raise TypeError(
                               F"""additional_special_tokens should be of type {type(A       )}, but is"""
                               F""" {type(A       )}"""       )

                    _UpperCAmelCase     :  Optional[int]							      =    (
                        ([mask_token_sent] + additional_special_tokens)
                        if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
                        else additional_special_tokens
                    )
                    # fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
                    additional_special_tokens_extended += [
                        F"""<unk_{i}>""" for i in range(len(A       )						,					self.offset - 1       )
                    ]

                    if len(set(A       )       ) != len(A       ):
                           raise ValueError(
                               "Please make sure that the provided additional_special_tokens do not contain an incorrectly"
                               F""" shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}."""       )
                    _UpperCAmelCase     :  Any							      =    additional_special_tokens_extended
             else:
                    _UpperCAmelCase     :  Dict							      =    [mask_token_sent] if mask_token_sent is not None else []
                    additional_special_tokens += [F"""<unk_{i}>""" for i in range(2						,					self.offset       )]

             super().__init__(
                 A						,					tokenizer_file=A						,					pad_token=A						,					eos_token=A						,					unk_token=A						,					mask_token=A						,					mask_token_sent=A						,					offset=A						,					additional_special_tokens=A						,					**A						,					)
             _UpperCAmelCase     :  Optional[Any]							      =    vocab_file
             _UpperCAmelCase     :  Optional[Any]							      =    False if not self.vocab_file else True




      def      _A	(       self						:				List[str]						,					A						:				Optional[Any]       ):
             _UpperCAmelCase     :  Any							      =    set(self.all_special_ids       )  # call it once instead of inside list comp
             all_special_ids.remove(self.unk_token_id       )  # <unk> is only sometimes special

             if all_special_ids != set(range(len(self.additional_special_tokens       ) + 3       )       ):
                    raise ValueError(
                        "There should be 3 special tokens: mask_token, pad_token, and eos_token +"
                        F""" {len(self.additional_special_tokens       )} additional_special_tokens, but got {all_special_ids}"""       )

             return [1 if x in all_special_ids else 0 for x in seq]




      def      _A	(       self						:				str						,					A						:				List						,					A						:				Optional[List] = None						,					A						:				bool = False       ):
             if already_has_special_tokens:
                    return self._special_token_mask(A       )
             elif token_ids_a is None:
                    return self._special_token_mask(A       ) + [1]
             else:
                    return self._special_token_mask(token_ids_a + token_ids_a       ) + [1]




      def      _A	(       self						:				Optional[int]						,					A						:				Union[str, Any]						,					A						:				int=None       ):
             if token_ids_a is None:
                    return token_ids_a + [self.eos_token_id]
             # We don't expect to process pairs, but leave the pair logic for API consistency
             return token_ids_a + token_ids_a + [self.eos_token_id]





      def      _A	(       self						:				Union[str, Any]						,					A						:				str						,					A						:				Optional[str] = None       ):
             if not self.can_save_slow_tokenizer:
                    raise ValueError(
                        "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
                        "tokenizer."       )

             if not os.path.isdir(A       ):
                    logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""       )
                    return
             _UpperCAmelCase     :  List[Any]							      =    os.path.join(
                 A						,					(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]       )

             if os.path.abspath(self.vocab_file       ) != os.path.abspath(A       ):
                    copyfile(self.vocab_file						,					A       )

             return (out_vocab_file,)

