



"""simple docstring"""






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      A__  (    __SCREAMING_SNAKE_CASE    ,						unittest.TestCase				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      XLMTokenizer
	SCREAMING_SNAKE_CASE        =      False

	def 				_SCREAMING_SNAKE_CASE  (	self:						Optional[int])							->			str:

				"""simple docstring"""

				super().setUp()

				# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
				__lowerCAmelCase :    Any				=			[
				    "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>",
				]
				__lowerCAmelCase :    Tuple				=			dict(zip(_SCREAMING_SNAKE_CASE			,     range(len(_SCREAMING_SNAKE_CASE))))
				__lowerCAmelCase :    Optional[Any]				=			["l o 123", "lo w 1456", "e r</w> 1789", ""]

				__lowerCAmelCase :    Dict				=			os.path.join(self.tmpdirname			,     VOCAB_FILES_NAMES["vocab_file"])
				__lowerCAmelCase :    Optional[int]				=			os.path.join(self.tmpdirname			,     VOCAB_FILES_NAMES["merges_file"])
				with open(self.vocab_file			,     "w") as fp:
							fp.write(json.dumps(_SCREAMING_SNAKE_CASE))
				with open(self.merges_file			,     "w") as fp:
							fp.write("\n".join(_SCREAMING_SNAKE_CASE))

	def 				_SCREAMING_SNAKE_CASE  (	self:						Tuple			,     _SCREAMING_SNAKE_CASE:						int)							->			str:

				"""simple docstring"""

				__lowerCAmelCase :    List[Any]				=			"lower newer"
				__lowerCAmelCase :    List[Any]				=			"lower newer"
				return input_text, output_text

	def 				_SCREAMING_SNAKE_CASE  (	self:						Dict)							->			List[str]:

				"""simple docstring"""

				__lowerCAmelCase :    List[str]				=			XLMTokenizer(self.vocab_file			,     self.merges_file)

				__lowerCAmelCase :    Optional[Any]				=			"lower"
				__lowerCAmelCase :    List[Any]				=			["low", "er</w>"]
				__lowerCAmelCase :    int				=			tokenizer.tokenize(_SCREAMING_SNAKE_CASE)
				self.assertListEqual(_SCREAMING_SNAKE_CASE			,     _SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    str				=			tokens + ["<unk>"]
				__lowerCAmelCase :    Tuple				=			[14, 15, 20]
				self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE)			,     _SCREAMING_SNAKE_CASE)







	@slow
	def 				_SCREAMING_SNAKE_CASE  (	self:						Optional[Any])							->			List[str]:

				"""simple docstring"""

				__lowerCAmelCase :    List[Any]				=			XLMTokenizer.from_pretrained("xlm-mlm-en-2048")

				__lowerCAmelCase :    List[Any]				=			tokenizer.encode("sequence builders"			,     add_special_tokens=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase :    Optional[Any]				=			tokenizer.encode("multi-sequence build"			,     add_special_tokens=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    Tuple				=			tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase :    Union[str, Any]				=			tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE			,     _SCREAMING_SNAKE_CASE)

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




"""simple docstring"""






from abc import ABC, abstractmethod
from argparse import ArgumentParser



class      A__  (    __SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	@staticmethod
	@abstractmethod
	def 				_SCREAMING_SNAKE_CASE  (	_SCREAMING_SNAKE_CASE:						ArgumentParser)							->			Optional[int]:

				"""simple docstring"""

				raise NotImplementedError()







	@abstractmethod
	def 				_SCREAMING_SNAKE_CASE  (	self:						Union[str, Any])							->			Dict:

				"""simple docstring"""

				raise NotImplementedError()