




'''simple docstring'''







import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class       _a  (     __a							,							unittest.TestCase			):
       __a    :					str           = HerbertTokenizer
       __a    :					Optional[Any]           = HerbertTokenizerFast
       __a    :					Any           = True
       def    A				(     self						:     Any    ):



           '''simple docstring'''

           super().setUp()

           # Use a simpler test file without japanese/chinese characters
           with open(f"{get_tests_dir()}/fixtures/sample_text_no_unicode.txt"       ,    encoding='''utf-8'''    ) as f_data:
               UpperCAmelCase      	=		f_data.read().replace('''\n\n'''       ,    '''\n'''    ).strip()

           UpperCAmelCase      	=		[
               '''<s>''',
               '''</s>''',
               '''l''',
               '''o''',
               '''w''',
               '''e''',
               '''r''',
               '''s''',
               '''t''',
               '''i''',
               '''d''',
               '''n''',
               '''w</w>''',
               '''r</w>''',
               '''t</w>''',
               '''lo''',
               '''low''',
               '''er</w>''',
               '''low</w>''',
               '''lowest</w>''',
               '''newer</w>''',
               '''wider</w>''',
               ''',</w>''',
               '''<unk>''',
           ]
           UpperCAmelCase      	=		dict(zip(lowercase       ,    range(len(lowercase    )    )    )    )
           UpperCAmelCase      	=		['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

           UpperCAmelCase      	=		os.path.join(self.tmpdirname       ,    VOCAB_FILES_NAMES['''vocab_file''']    )
           UpperCAmelCase      	=		os.path.join(self.tmpdirname       ,    VOCAB_FILES_NAMES['''merges_file''']    )
           with open(self.vocab_file       ,    '''w'''    ) as fp:
               fp.write(json.dumps(lowercase    )    )
           with open(self.merges_file       ,    '''w'''    ) as fp:
               fp.write('''\n'''.join(lowercase    )    )
       def    A				(     self						:     List[Any]       ,    lowercase						:     Optional[Any]    ):



           '''simple docstring'''

           UpperCAmelCase      	=		'''lower newer'''
           UpperCAmelCase      	=		'''lower newer'''
           return input_text, output_text
       def    A				(     self						:     int    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self.tokenizer_class(vocab_file=self.vocab_file       ,    merges_file=self.merges_file    )

           UpperCAmelCase      	=		'''lower'''
           UpperCAmelCase      	=		['''low''', '''er</w>''']
           UpperCAmelCase      	=		tokenizer.tokenize(lowercase    )
           self.assertListEqual(lowercase       ,    lowercase    )

           UpperCAmelCase      	=		tokens + ['''<unk>''']
           UpperCAmelCase      	=		[16, 17, 23]
           self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase    )       ,    lowercase    )
       def    A				(     self						:     str    ):



           '''simple docstring'''

           if not self.test_rust_tokenizer:
               return

           UpperCAmelCase      	=		self.get_tokenizer()
           UpperCAmelCase      	=		self.get_rust_tokenizer()

           UpperCAmelCase      	=		'''lower,newer'''

           UpperCAmelCase      	=		tokenizer.tokenize(lowercase    )
           UpperCAmelCase      	=		rust_tokenizer.tokenize(lowercase    )
           self.assertListEqual(lowercase       ,    lowercase    )

           UpperCAmelCase      	=		tokenizer.encode(lowercase       ,    add_special_tokens=lowercase    )
           UpperCAmelCase      	=		rust_tokenizer.encode(lowercase       ,    add_special_tokens=lowercase    )
           self.assertListEqual(lowercase       ,    lowercase    )

           UpperCAmelCase      	=		self.get_rust_tokenizer()
           UpperCAmelCase      	=		tokenizer.encode(lowercase    )
           UpperCAmelCase      	=		rust_tokenizer.encode(lowercase    )
           self.assertListEqual(lowercase       ,    lowercase    )







       @slow
       def    A				(     self						:     int    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self.tokenizer_class.from_pretrained('''allegro/herbert-base-cased'''    )

           UpperCAmelCase      	=		tokenizer.encode('''konstruowanie sekwencji'''       ,    add_special_tokens=lowercase    )
           UpperCAmelCase      	=		tokenizer.encode('''konstruowanie wielu sekwencji'''       ,    add_special_tokens=lowercase    )

           UpperCAmelCase      	=		tokenizer.build_inputs_with_special_tokens(lowercase    )
           UpperCAmelCase      	=		tokenizer.build_inputs_with_special_tokens(lowercase       ,    lowercase    )

           assert encoded_sentence == [0] + text + [2]
           assert encoded_pair == [0] + text + [2] + text_a + [2]










'''simple docstring'''







import multiprocessing
import os
from typing import BinaryIO, Optional, Union

from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.csv.csv import Csv
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader


class       _a  (     __a			):
       def __init__(     self						:     Any       ,    lowercase						:     NestedDataStructureLike[PathLike]       ,    lowercase						:     Optional[NamedSplit] = None       ,    lowercase						:     Optional[Features] = None       ,    lowercase						:     str = None       ,    lowercase						:     bool = False       ,    lowercase						:     bool = False       ,    lowercase						:     Optional[int] = None       ,    **lowercase						:     str       ,    ):



           '''simple docstring'''

           super().__init__(
               lowercase       ,    split=lowercase       ,    features=lowercase       ,    cache_dir=lowercase       ,    keep_in_memory=lowercase       ,    streaming=lowercase       ,    num_proc=lowercase       ,    **lowercase       ,    )
           UpperCAmelCase      	=		path_or_paths if isinstance(lowercase       ,    lowercase    ) else {self.split: path_or_paths}
           UpperCAmelCase      	=		Csv(
               cache_dir=lowercase       ,    data_files=lowercase       ,    features=lowercase       ,    **lowercase       ,    )







       def    A				(     self						:     Tuple    ):



           '''simple docstring'''

           if self.streaming:
               UpperCAmelCase      	=		self.builder.as_streaming_dataset(split=self.split    )
           # Build regular (map-style) dataset
           else:
               UpperCAmelCase      	=		None
               UpperCAmelCase      	=		None
               UpperCAmelCase      	=		None
               UpperCAmelCase      	=		None

               self.builder.download_and_prepare(
                   download_config=lowercase       ,    download_mode=lowercase       ,    verification_mode=lowercase       ,    base_path=lowercase       ,    num_proc=self.num_proc       ,    )
               UpperCAmelCase      	=		self.builder.as_dataset(
                   split=self.split       ,    verification_mode=lowercase       ,    in_memory=self.keep_in_memory    )
           return dataset






class       _a  :
       def __init__(     self						:     Optional[int]       ,    lowercase						:     Dataset       ,    lowercase						:     Union[PathLike, BinaryIO]       ,    lowercase						:     Optional[int] = None       ,    lowercase						:     Optional[int] = None       ,    **lowercase						:     int       ,    ):



           '''simple docstring'''

           if num_proc is not None and num_proc <= 0:
               raise ValueError(f"num_proc {num_proc} must be an integer > 0."    )

           UpperCAmelCase      	=		dataset
           UpperCAmelCase      	=		path_or_buf
           UpperCAmelCase      	=		batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
           UpperCAmelCase      	=		num_proc
           UpperCAmelCase      	=		'''utf-8'''
           UpperCAmelCase      	=		to_csv_kwargs
       def    A				(     self						:     Union[str, Any]    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self.to_csv_kwargs.pop('''path_or_buf'''       ,    lowercase    )
           UpperCAmelCase      	=		self.to_csv_kwargs.pop('''header'''       ,    lowercase    )
           UpperCAmelCase      	=		self.to_csv_kwargs.pop('''index'''       ,    lowercase    )

           if isinstance(self.path_or_buf       ,    (str, bytes, os.PathLike)    ):
               with open(self.path_or_buf       ,    '''wb+'''    ) as buffer:
                   UpperCAmelCase      	=		self._write(file_obj=lowercase       ,    header=lowercase       ,    index=lowercase       ,    **self.to_csv_kwargs    )
           else:
               UpperCAmelCase      	=		self._write(file_obj=self.path_or_buf       ,    header=lowercase       ,    index=lowercase       ,    **self.to_csv_kwargs    )
           return written
       def    A				(     self						:     List[str]       ,    lowercase						:     Dict    ):



           '''simple docstring'''

           UpperCAmelCase	,					UpperCAmelCase	,					UpperCAmelCase	,					UpperCAmelCase      	=		args

           UpperCAmelCase      	=		query_table(
               table=self.dataset.data       ,    key=slice(lowercase       ,    offset + self.batch_size    )       ,    indices=self.dataset._indices       ,    )
           UpperCAmelCase      	=		batch.to_pandas().to_csv(
               path_or_buf=lowercase       ,    header=header if (offset == 0) else False       ,    index=lowercase       ,    **lowercase    )
           return csv_str.encode(self.encoding    )







       def    A				(     self						:     List[str]       ,    lowercase						:     BinaryIO       ,    lowercase						:     int       ,    lowercase						:     List[str]       ,    **lowercase						:     List[Any]    ):



           '''simple docstring'''

           UpperCAmelCase      	=		0

           if self.num_proc is None or self.num_proc == 1:
               for offset in logging.tqdm(
                   range(0       ,    len(self.dataset    )       ,    self.batch_size    )       ,    unit='''ba'''       ,    disable=not logging.is_progress_bar_enabled()       ,    desc='''Creating CSV from Arrow format'''       ,    ):
                   UpperCAmelCase      	=		self._batch_csv((offset, header, index, to_csv_kwargs)    )
                   written += file_obj.write(lowercase    )

           else:
               UpperCAmelCase	,					UpperCAmelCase      	=		len(self.dataset    ), self.batch_size
               with multiprocessing.Pool(self.num_proc    ) as pool:
                   for csv_str in logging.tqdm(
                       pool.imap(
                           self._batch_csv       ,    [(offset, header, index, to_csv_kwargs) for offset in range(0       ,    lowercase       ,    lowercase    )]       ,    )       ,    total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size       ,    unit='''ba'''       ,    disable=not logging.is_progress_bar_enabled()       ,    desc='''Creating CSV from Arrow format'''       ,    ):
                       written += file_obj.write(lowercase    )

           return written




