






import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 				lowerCAmelCase_	(		__snake_case   ,		unittest.TestCase			):
				_UpperCamelCase					:       List[Any]							       = OpenAIGPTTokenizer
				_UpperCamelCase					:       Optional[Any]							       = OpenAIGPTTokenizerFast
				_UpperCamelCase					:       Tuple							       = True
				_UpperCamelCase					:       Optional[Any]							       = False


				def 						__a					(					self      ):
											super().setUp()

											# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
											_lowercase							:   int 							=   [
											    '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>',
											]
											_lowercase							:   Optional[int] 							=   dict(zip(_lowerCAmelCase ,						range(len(_lowerCAmelCase      )      )      )      )
											_lowercase							:   List[Any] 							=   ['#version: 0.2', 'l o', 'lo w', 'e r</w>', '']

											_lowercase							:   Optional[Any] 							=   os.path.join(self.tmpdirname ,						VOCAB_FILES_NAMES['vocab_file']      )
											_lowercase							:   str 							=   os.path.join(self.tmpdirname ,						VOCAB_FILES_NAMES['merges_file']      )
											with open(self.vocab_file ,						'w'      ) as fp:
																		fp.write(json.dumps(_lowerCAmelCase      )      )
											with open(self.merges_file ,						'w'      ) as fp:
																		fp.write('\n'.join(_lowerCAmelCase      )      )


				def 						__a					(					self ,						_lowerCAmelCase      ):
											return "lower newer", "lower newer"


				def 						__a					(					self      ):
											_lowercase							:   Optional[Any] 							=   OpenAIGPTTokenizer(self.vocab_file ,						self.merges_file      )

											_lowercase							:   Dict 							=   'lower'
											_lowercase							:   List[Any] 							=   ['low', 'er</w>']
											_lowercase							:   Tuple 							=   tokenizer.tokenize(_lowerCAmelCase      )
											self.assertListEqual(_lowerCAmelCase ,						_lowerCAmelCase      )

											_lowercase							:   Any 							=   tokens + ['<unk>']
											_lowercase							:   List[Any] 							=   [1_4, 1_5, 2_0]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase      ) ,						_lowerCAmelCase      )


				def 						__a					(					self ,						_lowerCAmelCase=1_5      ):
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""      ):
																									_lowercase							:   Optional[Any] 							=   self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase ,						**_lowerCAmelCase      )

																									# Simple input
																									_lowercase							:   Any 							=   'This is a simple input'
																									_lowercase							:   Optional[Any] 							=   ['This is a simple input 1', 'This is a simple input 2']
																									_lowercase							:   Optional[Any] 							=   ('This is a simple input', 'This is a pair')
																									_lowercase							:   int 							=   [
																									    ('This is a simple input 1', 'This is a simple input 2'),
																									    ('This is a simple pair 1', 'This is a simple pair 2'),
																									]

																									# Simple input tests
																									self.assertRaises(_lowerCAmelCase ,						tokenizer_r.encode ,						_lowerCAmelCase ,						max_length=_lowerCAmelCase ,						padding='max_length'      )

																									# Simple input
																									self.assertRaises(_lowerCAmelCase ,						tokenizer_r.encode_plus ,						_lowerCAmelCase ,						max_length=_lowerCAmelCase ,						padding='max_length'      )

																									# Simple input
																									self.assertRaises(
																									    _lowerCAmelCase ,						tokenizer_r.batch_encode_plus ,						_lowerCAmelCase ,						max_length=_lowerCAmelCase ,						padding='max_length' ,						)

																									# Pair input
																									self.assertRaises(_lowerCAmelCase ,						tokenizer_r.encode ,						_lowerCAmelCase ,						max_length=_lowerCAmelCase ,						padding='max_length'      )

																									# Pair input
																									self.assertRaises(_lowerCAmelCase ,						tokenizer_r.encode_plus ,						_lowerCAmelCase ,						max_length=_lowerCAmelCase ,						padding='max_length'      )

																									# Pair input
																									self.assertRaises(
																									    _lowerCAmelCase ,						tokenizer_r.batch_encode_plus ,						_lowerCAmelCase ,						max_length=_lowerCAmelCase ,						padding='max_length' ,						)


				def 						__a					(					self      ):
											pass




@require_ftfy
@require_spacy
@require_tokenizers
class 				lowerCAmelCase_	(		__snake_case			):
				pass












import re

from filelock import FileLock


try:
       import nltk

       UpperCamelCase    							=      True
except (ImportError, ModuleNotFoundError):
       UpperCamelCase    							=      False

if NLTK_AVAILABLE:
       with FileLock('.lock') as lock:
              nltk.download('punkt', quiet=True)


def 				__lowerCamelCase     (							__lowerCAmelCase							:					str							)     ->  str:
   re.sub("""<n>"""					,							""""""					,							__lowerCAmelCase							)  # remove pegasus newline char
   assert NLTK_AVAILABLE, "nltk must be installed to separate newlines between sentences. (pip install nltk)"
   return "\n".join(nltk.sent_tokenize(__lowerCAmelCase							)							)



