




import json
import os
from pathlib import Path

import pytest

from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename


__SCREAMING_SNAKE_CASE 						="""http://www.mocksite.com/file1.txt"""
__SCREAMING_SNAKE_CASE 						="""\"text\": [\"foo\", \"foo\"]"""
__SCREAMING_SNAKE_CASE 						="""6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8"""






class  __magic_name__						:
				'''simple docstring'''







				SCREAMING_SNAKE_CASE__					:							Union[str, Any]	      =					200
				SCREAMING_SNAKE_CASE__					:							Dict	      =					{"Content-Length": "100"}
				SCREAMING_SNAKE_CASE__					:							Union[str, Any]	      =					{}


				def     _A							(							self:   List[str]		,					**_lowerCamelCase:   Optional[int]		):
											return [bytes(_lowerCamelCase		,					'''utf-8'''		)]






def 			a   (*_lowerCAmelCase  ,    **_lowerCAmelCase     ):
							return MockResponse()

@pytest.mark.parametrize('''urls_type'''  ,    [str, list, dict]     )
def 			a   (_lowerCAmelCase  ,    _lowerCAmelCase  ,    _lowerCAmelCase     ):
							import requests

							monkeypatch.setattr(_lowerCAmelCase  ,    '''request'''  ,    _lowerCAmelCase     )

							SCREAMING_SNAKE_CASE_   	=    URL
							if issubclass(_lowerCAmelCase  ,    _lowerCAmelCase     ):
														SCREAMING_SNAKE_CASE_   	=    url
							elif issubclass(_lowerCAmelCase  ,    _lowerCAmelCase     ):
														SCREAMING_SNAKE_CASE_   	=    [url]
							elif issubclass(_lowerCAmelCase  ,    _lowerCAmelCase     ):
														SCREAMING_SNAKE_CASE_   	=    {'''train''': url}
							SCREAMING_SNAKE_CASE_   	=    '''dummy'''
							SCREAMING_SNAKE_CASE_   	=    '''downloads'''
							SCREAMING_SNAKE_CASE_   	=    tmp_path
							SCREAMING_SNAKE_CASE_   	=    DownloadConfig(
							    cache_dir=os.path.join(_lowerCAmelCase  ,    _lowerCAmelCase     )  ,    use_etag=_lowerCAmelCase  ,    )
							SCREAMING_SNAKE_CASE_   	=    DownloadManager(dataset_name=_lowerCAmelCase  ,    download_config=_lowerCAmelCase     )
							SCREAMING_SNAKE_CASE_   	=    dl_manager.download(_lowerCAmelCase     )
							SCREAMING_SNAKE_CASE_   	=    urls
							for downloaded_paths in [downloaded_paths]:
														if isinstance(_lowerCAmelCase  ,    _lowerCAmelCase     ):
																					SCREAMING_SNAKE_CASE_   	=    [downloaded_paths]
																					SCREAMING_SNAKE_CASE_   	=    [urls]
														elif isinstance(_lowerCAmelCase  ,    _lowerCAmelCase     ):
																					assert "train" in downloaded_paths.keys()
																					SCREAMING_SNAKE_CASE_   	=    downloaded_paths.values()
																					SCREAMING_SNAKE_CASE_   	=    urls.values()
														assert downloaded_paths
														for downloaded_path, input_url in zip(_lowerCAmelCase  ,    _lowerCAmelCase     ):
																					assert downloaded_path == dl_manager.downloaded_paths[input_url]
																					SCREAMING_SNAKE_CASE_   	=    Path(_lowerCAmelCase     )
																					SCREAMING_SNAKE_CASE_   	=    downloaded_path.parts
																					assert parts[-1] == HASH
																					assert parts[-2] == cache_subdir
																					assert downloaded_path.exists()
																					SCREAMING_SNAKE_CASE_   	=    downloaded_path.read_text()
																					assert content == CONTENT
																					SCREAMING_SNAKE_CASE_   	=    downloaded_path.with_suffix('''.json'''     )
																					assert metadata_downloaded_path.exists()
																					SCREAMING_SNAKE_CASE_   	=    json.loads(metadata_downloaded_path.read_text()     )
																					assert metadata_content == {"url": URL, "etag": None}

@pytest.mark.parametrize('''paths_type'''  ,    [str, list, dict]     )
def 			a   (_lowerCAmelCase  ,    _lowerCAmelCase  ,    _lowerCAmelCase     ):
							SCREAMING_SNAKE_CASE_   	=    str(_lowerCAmelCase     )
							if issubclass(_lowerCAmelCase  ,    _lowerCAmelCase     ):
														SCREAMING_SNAKE_CASE_   	=    filename
							elif issubclass(_lowerCAmelCase  ,    _lowerCAmelCase     ):
														SCREAMING_SNAKE_CASE_   	=    [filename]
							elif issubclass(_lowerCAmelCase  ,    _lowerCAmelCase     ):
														SCREAMING_SNAKE_CASE_   	=    {'''train''': filename}
							SCREAMING_SNAKE_CASE_   	=    '''dummy'''
							SCREAMING_SNAKE_CASE_   	=    xz_file.parent
							SCREAMING_SNAKE_CASE_   	=    '''extracted'''
							SCREAMING_SNAKE_CASE_   	=    DownloadConfig(
							    cache_dir=_lowerCAmelCase  ,    use_etag=_lowerCAmelCase  ,    )
							SCREAMING_SNAKE_CASE_   	=    DownloadManager(dataset_name=_lowerCAmelCase  ,    download_config=_lowerCAmelCase     )
							SCREAMING_SNAKE_CASE_   	=    dl_manager.extract(_lowerCAmelCase     )
							SCREAMING_SNAKE_CASE_   	=    paths
							for extracted_paths in [extracted_paths]:
														if isinstance(_lowerCAmelCase  ,    _lowerCAmelCase     ):
																					SCREAMING_SNAKE_CASE_   	=    [extracted_paths]
																					SCREAMING_SNAKE_CASE_   	=    [paths]
														elif isinstance(_lowerCAmelCase  ,    _lowerCAmelCase     ):
																					assert "train" in extracted_paths.keys()
																					SCREAMING_SNAKE_CASE_   	=    extracted_paths.values()
																					SCREAMING_SNAKE_CASE_   	=    paths.values()
														assert extracted_paths
														for extracted_path, input_path in zip(_lowerCAmelCase  ,    _lowerCAmelCase     ):
																					assert extracted_path == dl_manager.extracted_paths[input_path]
																					SCREAMING_SNAKE_CASE_   	=    Path(_lowerCAmelCase     )
																					SCREAMING_SNAKE_CASE_   	=    extracted_path.parts
																					assert parts[-1] == hash_url_to_filename(_lowerCAmelCase  ,    etag=_lowerCAmelCase     )
																					assert parts[-2] == extracted_subdir
																					assert extracted_path.exists()
																					SCREAMING_SNAKE_CASE_   	=    extracted_path.read_text()
																					SCREAMING_SNAKE_CASE_   	=    text_file.read_text()
																					assert extracted_file_content == expected_file_content

def 			a   (_lowerCAmelCase  ,    _lowerCAmelCase     ):
							assert path.endswith('''.jsonl'''     )
							for num_items, line in enumerate(_lowerCAmelCase  ,    start=1     ):
														SCREAMING_SNAKE_CASE_   	=    json.loads(line.decode('''utf-8'''     )     )
														assert item.keys() == {"col_1", "col_2", "col_3"}
							assert num_items == 4

@pytest.mark.parametrize('''archive_jsonl'''  ,    ['''tar_jsonl_path''', '''zip_jsonl_path''']     )
def 			a   (_lowerCAmelCase  ,    _lowerCAmelCase     ):
							SCREAMING_SNAKE_CASE_   	=    request.getfixturevalue(_lowerCAmelCase     )
							SCREAMING_SNAKE_CASE_   	=    DownloadManager()
							for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(_lowerCAmelCase     )  ,    start=1     ):
														_test_jsonl(_lowerCAmelCase  ,    _lowerCAmelCase     )
							assert num_jsonl == 2

@pytest.mark.parametrize('''archive_nested_jsonl'''  ,    ['''tar_nested_jsonl_path''', '''zip_nested_jsonl_path''']     )
def 			a   (_lowerCAmelCase  ,    _lowerCAmelCase     ):
							SCREAMING_SNAKE_CASE_   	=    request.getfixturevalue(_lowerCAmelCase     )
							SCREAMING_SNAKE_CASE_   	=    DownloadManager()
							for num_tar, (path, file) in enumerate(dl_manager.iter_archive(_lowerCAmelCase     )  ,    start=1     ):
														for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(_lowerCAmelCase     )  ,    start=1     ):
																					_test_jsonl(_lowerCAmelCase  ,    _lowerCAmelCase     )
							assert num_tar == 1
							assert num_jsonl == 2






def 			a   (_lowerCAmelCase     ):
							SCREAMING_SNAKE_CASE_   	=    DownloadManager()
							for num_file, file in enumerate(dl_manager.iter_files(_lowerCAmelCase     )  ,    start=1     ):
														assert os.path.basename(_lowerCAmelCase     ) == ("test.txt" if num_file == 1 else "train.txt")
							assert num_file == 2








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

import sentencepiece as spm

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


__SCREAMING_SNAKE_CASE 						=logging.get_logger(__name__)


__SCREAMING_SNAKE_CASE 						="""▁"""

__SCREAMING_SNAKE_CASE 						={"""vocab_file""": """spiece.model"""}

__SCREAMING_SNAKE_CASE 						={
    """vocab_file""": {
        """google/reformer-crime-and-punishment""": (
            """https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"""
        )
    }
}

__SCREAMING_SNAKE_CASE 						={
    """google/reformer-crime-and-punishment""": 524_288,
}






class  __magic_name__						(  __UpperCAmelCase):
				'''simple docstring'''







				SCREAMING_SNAKE_CASE__					:							Any	      =					VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE__					:							Union[str, Any]	      =					PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE__					:							Optional[int]	      =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE__					:							Union[str, Any]	      =					["input_ids", "attention_mask"]


				def __init__(							self:   List[Any]		,					_lowerCamelCase:   List[Any]		,					_lowerCamelCase:   List[Any]="</s>"		,					_lowerCamelCase:   str="<unk>"		,					_lowerCamelCase:   Union[str, Any]=[]		,					_lowerCamelCase:   Optional[Dict[str, Any]] = None		,					**_lowerCamelCase:   List[str]		,					):
											SCREAMING_SNAKE_CASE_   	=    {} if sp_model_kwargs is None else sp_model_kwargs

											super().__init__(
											    eos_token=_lowerCamelCase		,					unk_token=_lowerCamelCase		,					additional_special_tokens=_lowerCamelCase		,					sp_model_kwargs=self.sp_model_kwargs		,					**_lowerCamelCase		,					)

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


				@property
				def     _A							(							self:   Optional[int]		):
											return self.sp_model.get_piece_size()


				def     _A							(							self:   int		):
											SCREAMING_SNAKE_CASE_   	=    {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:   Tuple		):
											SCREAMING_SNAKE_CASE_   	=    self.__dict__.copy()
											SCREAMING_SNAKE_CASE_   	=    None
											return state


				def __setstate__(							self:   Dict		,					_lowerCamelCase:   Union[str, Any]		):
											SCREAMING_SNAKE_CASE_   	=    d

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

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


				def     _A							(							self:   Optional[Any]		,					_lowerCamelCase:   str		):
											return self.sp_model.encode(_lowerCamelCase		,					out_type=_lowerCamelCase		)


				def     _A							(							self:   int		,					_lowerCamelCase:   Optional[int]		):
											return self.sp_model.piece_to_id(_lowerCamelCase		)


				def     _A							(							self:   Union[str, Any]		,					_lowerCamelCase:   Tuple		):
											if index < self.sp_model.get_piece_size():
																		SCREAMING_SNAKE_CASE_   	=    self.sp_model.IdToPiece(_lowerCamelCase		)
											return token


				def     _A							(							self:   List[str]		,					_lowerCamelCase:   int		):
											SCREAMING_SNAKE_CASE_   	=    []
											SCREAMING_SNAKE_CASE_   	=    ''''''
											for token in tokens:
																		# make sure that special tokens are not decoded using sentencepiece model
																		if token in self.all_special_tokens:
																									out_string += self.sp_model.decode(_lowerCamelCase		) + token
																									SCREAMING_SNAKE_CASE_   	=    []
																		else:
																									current_sub_tokens.append(_lowerCamelCase		)
											out_string += self.sp_model.decode(_lowerCamelCase		)
											return out_string.strip()





				def     _A							(							self:   Optional[int]		,					_lowerCamelCase:   str		,					_lowerCamelCase:   Optional[str] = None		):
											if not os.path.isdir(_lowerCamelCase		):
																		logger.error(f"Vocabulary path ({save_directory}) should be a directory"		)
																		return
											SCREAMING_SNAKE_CASE_   	=    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:
																									SCREAMING_SNAKE_CASE_   	=    self.sp_model.serialized_model_proto()
																									fi.write(_lowerCamelCase		)

											return (out_vocab_file,)


