'''simple docstring'''





import itertools
from dataclasses import dataclass
from typing import Optional

import pandas as pd
import pyarrow as pa

import datasets
from datasets.table import table_cast




@dataclass
class        __A      ( datasets.BuilderConfig	):
    a__       :						Optional[datasets.Features]          =  None




class        __A      ( datasets.ArrowBasedBuilder	):
    a__       :						str          =  PandasConfig



    def 					_lowercase						(self    :    Any ):
         return datasets.DatasetInfo(features=self.config.features )



    def 					_lowercase						(self    :    str   ,			__a    :    List[str] ):
         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(__a   ,			(str, list, tuple) ):
              UpperCAmelCase_           =   data_files
              if isinstance(__a   ,			__a ):
                   UpperCAmelCase_           =   [files]
              # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
              UpperCAmelCase_           =   [dl_manager.iter_files(__a ) 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(__a   ,			__a ):
                   UpperCAmelCase_           =   [files]
              # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
              UpperCAmelCase_           =   [dl_manager.iter_files(__a ) for file in files]
              splits.append(datasets.SplitGenerator(name=__a   ,			gen_kwargs={"files": files} ) )
         return splits



    def 					_lowercase						(self    :    str   ,			__a    :    pa.Table ):
         if self.config.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(__a   ,			self.config.features.arrow_schema )
         return pa_table






    def 					_lowercase						(self    :    List[str]   ,			__a    :    List[Any] ):
         for i, file in enumerate(itertools.chain.from_iterable(__a ) ):
              with open(__a   ,			"rb" ) as f:
                   UpperCAmelCase_           =   pa.Table.from_pandas(pd.read_pickle(__a ) )
                   yield i, self._cast_table(__a )






import os
import unittest

from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 						lowercase__  (						_UpperCAmelCase     ,       unittest.TestCase  ):
	A__    :   Dict				       =LxmertTokenizer
	A__    :   List[Any]				       =LxmertTokenizerFast
	A__    :   Any				       =True
	A__    :   List[Any]				       =True
	def      A_				(			self							:   Optional[Any]							):
						super().setUp()

						SCREAMING_SNAKE_CASE__													= [
						    '[UNK]',
						    '[CLS]',
						    '[SEP]',
						    'want',
						    '##want',
						    '##ed',
						    'wa',
						    'un',
						    'runn',
						    '##ing',
						    ',',
						    'low',
						    'lowest',
						]
						SCREAMING_SNAKE_CASE__													= os.path.join(self.tmpdirname       ,   VOCAB_FILES_NAMES['vocab_file']							)
						with open(self.vocab_file       ,   'w'       ,   encoding='utf-8'							) as vocab_writer:
											vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]							)							)
	def      A_				(			self							:   int       ,   UpperCAmelCase_							:   int							):
						SCREAMING_SNAKE_CASE__													= 'UNwant\u00E9d,running'
						SCREAMING_SNAKE_CASE__													= 'unwanted, running'
						return input_text, output_text
	def      A_				(			self							:   Optional[Any]							):
						SCREAMING_SNAKE_CASE__													= self.tokenizer_class(self.vocab_file							)

						SCREAMING_SNAKE_CASE__													= tokenizer.tokenize('UNwant\u00E9d,running'							)
						self.assertListEqual(UpperCAmelCase_       ,   ['un', '##want', '##ed', ',', 'runn', '##ing']							)
						self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase_							)       ,   [7, 4, 5, 10, 8, 9]							)





	def      A_				(			self							:   List[str]							):
						if not self.test_rust_tokenizer:
											return

						SCREAMING_SNAKE_CASE__													= self.get_tokenizer()
						SCREAMING_SNAKE_CASE__													= self.get_rust_tokenizer()

						SCREAMING_SNAKE_CASE__													= 'I was born in 92000, and this is falsé.'

						SCREAMING_SNAKE_CASE__													= tokenizer.tokenize(UpperCAmelCase_							)
						SCREAMING_SNAKE_CASE__													= rust_tokenizer.tokenize(UpperCAmelCase_							)
						self.assertListEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)

						SCREAMING_SNAKE_CASE__													= tokenizer.encode(UpperCAmelCase_       ,   add_special_tokens=UpperCAmelCase_							)
						SCREAMING_SNAKE_CASE__													= rust_tokenizer.encode(UpperCAmelCase_       ,   add_special_tokens=UpperCAmelCase_							)
						self.assertListEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)

						SCREAMING_SNAKE_CASE__													= self.get_rust_tokenizer()
						SCREAMING_SNAKE_CASE__													= tokenizer.encode(UpperCAmelCase_							)
						SCREAMING_SNAKE_CASE__													= rust_tokenizer.encode(UpperCAmelCase_							)
						self.assertListEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)





