





import os
from pathlib import Path
from unittest.mock import patch

import pytest
import zstandard as zstd

from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
    OfflineModeIsEnabled,
    cached_path,
    fsspec_get,
    fsspec_head,
    ftp_get,
    ftp_head,
    get_from_cache,
    http_get,
    http_head,
)


a__:      Tuple									=		'\\n    Text data.\n    Second line of data.'

a__:      Optional[Any]									=		'file'


@pytest.fixture(scope='''session'''  )
def 	UpperCamelCase__(       UpperCamelCase__			:       Optional[int]  )->Optional[int]:
       A__											=						tmp_path_factory.mktemp('''data'''  ) / (FILE_PATH + '''.zstd''')
       A__											=						bytes(UpperCamelCase__ ,     '''utf-8'''  )
       with zstd.open(UpperCamelCase__ ,     '''wb'''  ) as f:
              f.write(UpperCamelCase__  )
       return path


@pytest.fixture
def 	UpperCamelCase__(       UpperCamelCase__			:       List[Any]  )->Any:
       with open(os.path.join(tmpfs.local_root_dir ,     UpperCamelCase__  ) ,     '''w'''  ) as f:
              f.write(UpperCamelCase__  )
       return FILE_PATH


@pytest.mark.parametrize('''compression_format''' ,     ['''gzip''', '''xz''', '''zstd''']  )
def 	UpperCamelCase__(       UpperCamelCase__			:       Tuple ,     UpperCamelCase__			:       Optional[int] ,     UpperCamelCase__			:       List[Any] ,     UpperCamelCase__			:       Any ,     UpperCamelCase__			:       Union[str, Any] ,     UpperCamelCase__			:       int  )->Any:
       A__											=						{'''gzip''': gz_file, '''xz''': xz_file, '''zstd''': zstd_path}
       A__											=						input_paths[compression_format]
       A__											=						tmp_path / '''cache'''
       A__											=						DownloadConfig(cache_dir=UpperCamelCase__ ,     extract_compressed_file=UpperCamelCase__  )
       A__											=						cached_path(UpperCamelCase__ ,     download_config=UpperCamelCase__  )
       with open(UpperCamelCase__  ) as f:
              A__											=						f.read()
       with open(UpperCamelCase__  ) as f:
              A__											=						f.read()
       assert extracted_file_content == expected_file_content


@pytest.mark.parametrize('''default_extracted''' ,     [True, False]  )
@pytest.mark.parametrize('''default_cache_dir''' ,     [True, False]  )
def 	UpperCamelCase__(       UpperCamelCase__			:       Optional[int] ,     UpperCamelCase__			:       Tuple ,     UpperCamelCase__			:       str ,     UpperCamelCase__			:       Dict ,     UpperCamelCase__			:       int  )->Optional[Any]:
       A__											=						'''custom_cache'''
       A__											=						'''custom_extracted_dir'''
       A__											=						tmp_path / '''custom_extracted_path'''
       if default_extracted:
              A__											=						('''downloads''' if default_cache_dir else custom_cache_dir, '''extracted''')
       else:
              monkeypatch.setattr('''datasets.config.EXTRACTED_DATASETS_DIR''' ,     UpperCamelCase__  )
              monkeypatch.setattr('''datasets.config.EXTRACTED_DATASETS_PATH''' ,     str(UpperCamelCase__  )  )
              A__											=						custom_extracted_path.parts[-2:] if default_cache_dir else (custom_cache_dir, custom_extracted_dir)

       A__											=						xz_file
       A__											=						(
           DownloadConfig(extract_compressed_file=UpperCamelCase__  )
           if default_cache_dir
           else DownloadConfig(cache_dir=tmp_path / custom_cache_dir ,     extract_compressed_file=UpperCamelCase__  )
       )
       A__											=						cached_path(UpperCamelCase__ ,     download_config=UpperCamelCase__  )
       assert Path(UpperCamelCase__  ).parent.parts[-2:] == expected


def 	UpperCamelCase__(       UpperCamelCase__			:       Optional[int]  )->str:
       # absolute path
       A__											=						str(Path(UpperCamelCase__  ).resolve()  )
       assert cached_path(UpperCamelCase__  ) == text_file
       # relative path
       A__											=						str(Path(UpperCamelCase__  ).resolve().relative_to(Path(os.getcwd()  )  )  )
       assert cached_path(UpperCamelCase__  ) == text_file


def 	UpperCamelCase__(       UpperCamelCase__			:       int  )->Optional[Any]:
       # absolute path
       A__											=						str(tmp_path.resolve() / '''__missing_file__.txt'''  )
       with pytest.raises(UpperCamelCase__  ):
              cached_path(UpperCamelCase__  )
       # relative path
       A__											=						'''./__missing_file__.txt'''
       with pytest.raises(UpperCamelCase__  ):
              cached_path(UpperCamelCase__  )


def 	UpperCamelCase__(       UpperCamelCase__			:       Tuple  )->Optional[int]:
       A__											=						get_from_cache(f"tmp://{tmpfs_file}"  )
       with open(UpperCamelCase__  ) as f:
              A__											=						f.read()
       assert output_file_content == FILE_CONTENT


@patch('''datasets.config.HF_DATASETS_OFFLINE''' ,     UpperCamelCase__  )
def 	UpperCamelCase__(       )->List[str]:
       with pytest.raises(UpperCamelCase__  ):
              cached_path('''https://huggingface.co'''  )


@patch('''datasets.config.HF_DATASETS_OFFLINE''' ,     UpperCamelCase__  )
def 	UpperCamelCase__(       UpperCamelCase__			:       Optional[int]  )->Union[str, Any]:
       A__											=						tmp_path_factory.mktemp('''data'''  ) / '''file.html'''
       with pytest.raises(UpperCamelCase__  ):
              http_get('''https://huggingface.co''' ,     temp_file=UpperCamelCase__  )
       with pytest.raises(UpperCamelCase__  ):
              http_head('''https://huggingface.co'''  )


@patch('''datasets.config.HF_DATASETS_OFFLINE''' ,     UpperCamelCase__  )
def 	UpperCamelCase__(       UpperCamelCase__			:       Union[str, Any]  )->Optional[int]:
       A__											=						tmp_path_factory.mktemp('''data'''  ) / '''file.html'''
       with pytest.raises(UpperCamelCase__  ):
              ftp_get('''ftp://huggingface.co''' ,     temp_file=UpperCamelCase__  )
       with pytest.raises(UpperCamelCase__  ):
              ftp_head('''ftp://huggingface.co'''  )


@patch('''datasets.config.HF_DATASETS_OFFLINE''' ,     UpperCamelCase__  )
def 	UpperCamelCase__(       UpperCamelCase__			:       Union[str, Any]  )->int:
       A__											=						tmp_path_factory.mktemp('''data'''  ) / '''file.html'''
       with pytest.raises(UpperCamelCase__  ):
              fsspec_get('''s3://huggingface.co''' ,     temp_file=UpperCamelCase__  )
       with pytest.raises(UpperCamelCase__  ):
              fsspec_head('''s3://huggingface.co'''  )












import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


a__:      Union[str, Any]									=		logging.get_logger(__name__)

a__:      Union[str, Any]									=		{'vocab_file': 'spiece.model'}

a__:      Tuple									=		{
    'vocab_file': {
        'google/bigbird-roberta-base': 'https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model',
        'google/bigbird-roberta-large': (
            'https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model'
        ),
        'google/bigbird-base-trivia-itc': (
            'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model'
        ),
    }
}

a__:      Any									=		{
    'google/bigbird-roberta-base': 4_096,
    'google/bigbird-roberta-large': 4_096,
    'google/bigbird-base-trivia-itc': 4_096,
}




class     SCREAMING_SNAKE_CASE__ (						UpperCamelCase__      ):
 __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							       =	[]



 def __init__(							self,__lowerCamelCase,__lowerCamelCase="<unk>",__lowerCamelCase="<s>",__lowerCamelCase="</s>",__lowerCamelCase="<pad>",__lowerCamelCase="[SEP]",__lowerCamelCase="[MASK]",__lowerCamelCase="[CLS]",__lowerCamelCase = None,**__lowerCamelCase,):
        A__											=						AddedToken(__lowerCamelCase,lstrip=__lowerCamelCase,rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase,__lowerCamelCase ) else bos_token
        A__											=						AddedToken(__lowerCamelCase,lstrip=__lowerCamelCase,rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase,__lowerCamelCase ) else eos_token
        A__											=						AddedToken(__lowerCamelCase,lstrip=__lowerCamelCase,rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase,__lowerCamelCase ) else unk_token
        A__											=						AddedToken(__lowerCamelCase,lstrip=__lowerCamelCase,rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase,__lowerCamelCase ) else pad_token
        A__											=						AddedToken(__lowerCamelCase,lstrip=__lowerCamelCase,rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase,__lowerCamelCase ) else cls_token
        A__											=						AddedToken(__lowerCamelCase,lstrip=__lowerCamelCase,rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase,__lowerCamelCase ) else sep_token

        # Mask token behave like a normal word, i.e. include the space before it
        A__											=						AddedToken(__lowerCamelCase,lstrip=__lowerCamelCase,rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase,__lowerCamelCase ) else mask_token

        A__											=						{} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            bos_token=__lowerCamelCase,eos_token=__lowerCamelCase,unk_token=__lowerCamelCase,pad_token=__lowerCamelCase,sep_token=__lowerCamelCase,mask_token=__lowerCamelCase,cls_token=__lowerCamelCase,sp_model_kwargs=self.sp_model_kwargs,**__lowerCamelCase,)

        A__											=						vocab_file

        A__											=						spm.SentencePieceProcessor(**self.sp_model_kwargs )
        self.sp_model.Load(__lowerCamelCase )



 @property
 def 				UpperCamelCase			(							self ):
        return self.sp_model.get_piece_size()



 def 				UpperCamelCase			(							self ):
        A__											=						{self.convert_ids_to_tokens(__lowerCamelCase ): i for i in range(self.vocab_size )}
        vocab.update(self.added_tokens_encoder )
        return vocab



 def __getstate__(							self ):
        A__											=						self.__dict__.copy()
        A__											=						None
        return state



 def __setstate__(							self,__lowerCamelCase ):
        A__											=						d

        # for backward compatibility
        if not hasattr(self,'''sp_model_kwargs''' ):
               A__											=						{}

        A__											=						spm.SentencePieceProcessor(**self.sp_model_kwargs )
        self.sp_model.Load(self.vocab_file )



 def 				UpperCamelCase			(							self,__lowerCamelCase ):
        return self.sp_model.encode(__lowerCamelCase,out_type=__lowerCamelCase )



 def 				UpperCamelCase			(							self,__lowerCamelCase ):
        return self.sp_model.piece_to_id(__lowerCamelCase )



 def 				UpperCamelCase			(							self,__lowerCamelCase ):
        A__											=						self.sp_model.IdToPiece(__lowerCamelCase )
        return token



 def 				UpperCamelCase			(							self,__lowerCamelCase ):
        A__											=						[]
        A__											=						''''''
        A__											=						False
        for token in tokens:
               # make sure that special tokens are not decoded using sentencepiece model
               if token in self.all_special_tokens:
                      if not prev_is_special:
                             out_string += " "
                      out_string += self.sp_model.decode(__lowerCamelCase ) + token
                      A__											=						True
                      A__											=						[]
               else:
                      current_sub_tokens.append(__lowerCamelCase )
                      A__											=						False
        out_string += self.sp_model.decode(__lowerCamelCase )
        return out_string.strip()



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = False,__lowerCamelCase = None,__lowerCamelCase = True,**__lowerCamelCase,):
        A__											=						kwargs.pop('''use_source_tokenizer''',__lowerCamelCase )

        A__											=						self.convert_ids_to_tokens(__lowerCamelCase,skip_special_tokens=__lowerCamelCase )

        # To avoid mixing byte-level and unicode for byte-level BPT
        # we need to build string separately for added tokens and byte-level tokens
        # cf. https://github.com/huggingface/transformers/issues/1133
        A__											=						[]
        A__											=						[]
        for token in filtered_tokens:
               if skip_special_tokens and token in self.all_special_ids:
                      continue
               if token in self.added_tokens_encoder:
                      if current_sub_text:
                             sub_texts.append(self.convert_tokens_to_string(__lowerCamelCase ) )
                             A__											=						[]
                      sub_texts.append(__lowerCamelCase )
               else:
                      current_sub_text.append(__lowerCamelCase )
        if current_sub_text:
               sub_texts.append(self.convert_tokens_to_string(__lowerCamelCase ) )

        # Mimic the behavior of the Rust tokenizer:
        # No space before [MASK] and [SEP]
        if spaces_between_special_tokens:
               A__											=						re.sub(r''' (\[(MASK|SEP)\])''',r'''\1''',''' '''.join(__lowerCamelCase ) )
        else:
               A__											=						''''''.join(__lowerCamelCase )

        A__											=						(
            clean_up_tokenization_spaces
            if clean_up_tokenization_spaces is not None
            else self.clean_up_tokenization_spaces
        )
        if clean_up_tokenization_spaces:
               A__											=						self.clean_up_tokenization(__lowerCamelCase )
               return clean_text
        else:
               return text



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = None ):
        if not os.path.isdir(__lowerCamelCase ):
               logger.error(f"Vocabulary path ({save_directory}) should be a directory" )
               return
        A__											=						os.path.join(
            __lowerCamelCase,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''] )

        if os.path.abspath(self.vocab_file ) != os.path.abspath(__lowerCamelCase ) and os.path.isfile(self.vocab_file ):
               copyfile(self.vocab_file,__lowerCamelCase )
        elif not os.path.isfile(self.vocab_file ):
               with open(__lowerCamelCase,'''wb''' ) as fi:
                      A__											=						self.sp_model.serialized_model_proto()
                      fi.write(__lowerCamelCase )

        return (out_vocab_file,)



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = None ):
        if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
        A__											=						[self.cls_token_id]
        A__											=						[self.sep_token_id]
        return cls + token_ids_a + sep + token_ids_a + sep



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = None,__lowerCamelCase = False ):
        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 None:
               return [1] + ([0] * len(__lowerCamelCase )) + [1]
        return [1] + ([0] * len(__lowerCamelCase )) + [1] + ([0] * len(__lowerCamelCase )) + [1]




 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = None ):
        A__											=						[self.sep_token_id]
        A__											=						[self.cls_token_id]
        if token_ids_a is None:
               return len(cls + token_ids_a + sep ) * [0]
        return len(cls + token_ids_a + sep ) * [0] + len(token_ids_a + sep ) * [1]





