




'''simple docstring'''







import itertools
from dataclasses import dataclass
from typing import Optional

import pyarrow as pa

import datasets
from datasets.table import table_cast


A			   =datasets.utils.logging.get_logger(__name__)


@dataclass
class       _a  (     datasets.BuilderConfig			):
       __a    :					Dict           = None






class       _a  (     datasets.ArrowBasedBuilder			):
       __a    :					int           = ArrowConfig
       def    A				(     self						:     Union[str, Any]    ):



           '''simple docstring'''

           return datasets.DatasetInfo(features=self.config.features    )
       def    A				(     self						:     str       ,    lowercase						:     Union[str, Any]    ):



           '''simple docstring'''

           if not self.config.data_files:
               raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}"    )
           UpperCAmelCase      	=		dl_manager.download_and_extract(self.config.data_files    )
           if isinstance(_snake_case       ,    (str, list, tuple)    ):
               UpperCAmelCase      	=		data_files
               if isinstance(_snake_case       ,    _snake_case    ):
                   UpperCAmelCase      	=		[files]
               # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
               UpperCAmelCase      	=		[dl_manager.iter_files(_snake_case    ) for file in files]
               return [datasets.SplitGenerator(name=datasets.Split.TRAIN       ,    gen_kwargs={'''files''': files}    )]
           UpperCAmelCase      	=		[]
           for split_name, files in data_files.items():
               if isinstance(_snake_case       ,    _snake_case    ):
                   UpperCAmelCase      	=		[files]
               # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
               UpperCAmelCase      	=		[dl_manager.iter_files(_snake_case    ) for file in files]
               # Infer features is they are stoed in the arrow schema
               if self.info.features is None:
                   for file in itertools.chain.from_iterable(_snake_case    ):
                       with open(_snake_case       ,    '''rb'''    ) as f:
                           UpperCAmelCase      	=		datasets.Features.from_arrow_schema(pa.ipc.open_stream(_snake_case    ).schema    )
                       break
               splits.append(datasets.SplitGenerator(name=_snake_case       ,    gen_kwargs={'''files''': files}    )    )
           return splits
       def    A				(     self						:     Dict       ,    lowercase						:     pa.Table    ):



           '''simple docstring'''

           if self.info.features is not None:
               # more expensive cast to support nested features with keys in a different order
               # allows str <-> int/float or str to Audio for example
               UpperCAmelCase      	=		table_cast(_snake_case       ,    self.info.features.arrow_schema    )
           return pa_table







       def    A				(     self						:     Optional[Any]       ,    lowercase						:     List[str]    ):



           '''simple docstring'''

           for file_idx, file in enumerate(itertools.chain.from_iterable(_snake_case    )    ):
               with open(_snake_case       ,    '''rb'''    ) as f:
                   try:
                       for batch_idx, record_batch in enumerate(pa.ipc.open_stream(_snake_case    )    ):
                           UpperCAmelCase      	=		pa.Table.from_batches([record_batch]    )
                           # Uncomment for debugging (will print the Arrow table size and elements)
                           # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                           # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
                           yield f"{file_idx}_{batch_idx}", self._cast_table(_snake_case    )
                   except ValueError as e:
                       logger.error(f"Failed to read file \'{file}\' with error {type(_snake_case    )}: {e}"    )
                       raise








'''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]




