


from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate






@dataclass(frozen=A_		)
class     UpperCAmelCase__       (					A_		):



    """simple docstring"""






    UpperCAmelCase__						:		str      =  field(default="language-modeling"   ,  metadata={"include_in_asdict_even_if_is_default": True}		)

    UpperCAmelCase__						:		ClassVar[Features]      =  Features({"text": Value("string"		)}		)
    UpperCAmelCase__						:		ClassVar[Features]      =  Features({}		)
    UpperCAmelCase__						:		str      =  "text"






    @property
    def _a					(			self    )  ->       Dict[str, str]:
         return {self.text_column: "text"}









import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin







class        snake_case_   (lowerCamelCase_	,						unittest.TestCase      ):
					UpperCAmelCase__					:    Tuple          =			XLMTokenizer
					UpperCAmelCase__					:    List[str]          =			False
					def  lowerCamelCase__(      self   :Any      )					->    Optional[Any]:
												super().setUp()

												# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
												a__             =     [
												    '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>',
												    '<unk>',
												]
												a__             =     dict(zip(__snake_case			,range(len(__snake_case      )      )      )      )
												a__             =     ['l o 123', 'lo w 1456', 'e r</w> 1789', '']

												a__             =     os.path.join(self.tmpdirname			,VOCAB_FILES_NAMES['vocab_file']      )
												a__             =     os.path.join(self.tmpdirname			,VOCAB_FILES_NAMES['merges_file']      )
												with open(self.vocab_file			,'w'      ) as fp:
																			fp.write(json.dumps(__snake_case      )      )
												with open(self.merges_file			,'w'      ) as fp:
																			fp.write('\n'.join(__snake_case      )      )
					def  lowerCamelCase__(      self   :Any			,__snake_case   :int      )					->    Optional[int]:
												a__             =     'lower newer'
												a__             =     'lower newer'
												return input_text, output_text
					def  lowerCamelCase__(      self   :Tuple      )					->    Tuple:
												a__             =     XLMTokenizer(self.vocab_file			,self.merges_file      )

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

												a__             =     tokens + ['<unk>']
												a__             =     [14, 15, 20]
												self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case      )			,__snake_case      )



					@slow
					def  lowerCamelCase__(      self   :List[str]      )					->    Optional[Any]:
												a__             =     XLMTokenizer.from_pretrained('xlm-mlm-en-2048'      )

												a__             =     tokenizer.encode('sequence builders'			,add_special_tokens=__snake_case      )
												a__             =     tokenizer.encode('multi-sequence build'			,add_special_tokens=__snake_case      )

												a__             =     tokenizer.build_inputs_with_special_tokens(__snake_case      )
												a__             =     tokenizer.build_inputs_with_special_tokens(__snake_case			,__snake_case      )

												assert encoded_sentence == [0] + text + [1]
												assert encoded_pair == [0] + text + [1] + text_a + [1]




