





import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin



class    __lowerCAmelCase			(     _a,	unittest.TestCase	):
			lowerCamelCase_	:	Optional[int]			     = BlenderbotSmallTokenizer
			lowerCamelCase_	:	Dict			     = False






			def      lowerCamelCase    (self       )	->  List[str]:


							'''simple docstring'''



							super().setUp()

							snake_case_		:       Optional[int]           =    ['''__start__''', '''adapt''', '''act''', '''ap@@''', '''te''', '''__end__''', '''__unk__''']
							snake_case_		:       str           =    dict(zip(__magic_name__   ,				range(len(__magic_name__       )       )       )       )

							snake_case_		:       Tuple           =    ['''#version: 0.2''', '''a p''', '''t e</w>''', '''ap t</w>''', '''a d''', '''ad apt</w>''', '''a c''', '''ac t</w>''', '''''']
							snake_case_		:       List[str]           =    {'''unk_token''': '''__unk__''', '''bos_token''': '''__start__''', '''eos_token''': '''__end__'''}

							snake_case_		:       Optional[int]           =    os.path.join(self.tmpdirname   ,				VOCAB_FILES_NAMES['''vocab_file''']       )
							snake_case_		:       Optional[Any]           =    os.path.join(self.tmpdirname   ,				VOCAB_FILES_NAMES['''merges_file''']       )
							with open(self.vocab_file   ,				'''w'''   ,				encoding='''utf-8'''       ) as fp:
											fp.write(json.dumps(__magic_name__       ) + '''\n'''       )
							with open(self.merges_file   ,				'''w'''   ,				encoding='''utf-8'''       ) as fp:
											fp.write('''\n'''.join(__magic_name__       )       )






			def      lowerCamelCase    (self   ,				**__magic_name__       )	->  int:


							'''simple docstring'''



							kwargs.update(self.special_tokens_map       )
							return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname   ,				**__magic_name__       )






			def      lowerCamelCase    (self   ,				__magic_name__       )	->  Optional[Any]:


							'''simple docstring'''



							snake_case_		:       Optional[int]           =    '''adapt act apte'''
							snake_case_		:       int           =    '''adapt act apte'''
							return input_text, output_text






			def      lowerCamelCase    (self       )	->  Tuple:


							'''simple docstring'''



							snake_case_		:       Any           =    BlenderbotSmallTokenizer(self.vocab_file   ,				self.merges_file   ,				**self.special_tokens_map       )
							snake_case_		:       List[Any]           =    '''adapt act apte'''
							snake_case_		:       Dict           =    ['''adapt''', '''act''', '''ap@@''', '''te''']
							snake_case_		:       Any           =    tokenizer.tokenize(__magic_name__       )
							self.assertListEqual(__magic_name__   ,				__magic_name__       )

							snake_case_		:       Tuple           =    [tokenizer.bos_token] + tokens + [tokenizer.eos_token]

							snake_case_		:       str           =    [0, 1, 2, 3, 4, 5]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(__magic_name__       )   ,				__magic_name__       )






			def      lowerCamelCase    (self       )	->  int:


							'''simple docstring'''



							snake_case_		:       int           =    BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''       )
							assert tok('''sam'''       ).input_ids == [1384]
							snake_case_		:       int           =    '''I am a small frog.'''
							snake_case_		:       Dict           =    tok([src_text]   ,				padding=__magic_name__   ,				truncation=__magic_name__       )['''input_ids''']
							snake_case_		:       str           =    tok.batch_decode(__magic_name__   ,				skip_special_tokens=__magic_name__   ,				clean_up_tokenization_spaces=__magic_name__       )[0]
							assert src_text != decoded  # I wish it did!
							assert decoded == "i am a small frog ."






			def      lowerCamelCase    (self       )	->  int:


							'''simple docstring'''



							snake_case_		:       str           =    BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''       )
							snake_case_		:       Tuple           =    '''I am a small frog .'''
							snake_case_		:       Optional[Any]           =    '''.'''
							snake_case_		:       int           =    tok(__magic_name__       )['''input_ids''']
							snake_case_		:       Any           =    tok(__magic_name__       )['''input_ids''']

							assert encoded[-1] == encoded_dot[0]

"""simple docstring"""




import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class    a_   (  __UpperCamelCase			,		unittest.TestCase      ):
					UpperCamelCase_			:						Optional[int]      =     MgpstrTokenizer
					UpperCamelCase_			:						Optional[int]      =     False
					UpperCamelCase_			:						Tuple      =     {}
					UpperCamelCase_			:						List[str]      =     False




					def     _SCREAMING_SNAKE_CASE    (						self    :  Dict  ):
							super().setUp()

							# fmt: off
							lowerCAmelCase__   = ["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
							# fmt: on
							lowerCAmelCase__   = dict(zip(snake_case__	,    range(len(snake_case__  )  )  )  )

							lowerCAmelCase__   = os.path.join(self.tmpdirname	,    VOCAB_FILES_NAMES["""vocab_file"""]  )
							with open(self.vocab_file	,    """w"""	,    encoding="""utf-8"""  ) as fp:
									fp.write(json.dumps(snake_case__  ) + """\n"""  )




					def     _SCREAMING_SNAKE_CASE    (						self    :  int	,    **snake_case__    :  Tuple  ):
							return MgpstrTokenizer.from_pretrained(self.tmpdirname	,    **snake_case__  )




					def     _SCREAMING_SNAKE_CASE    (						self    :  List[str]	,    snake_case__    :  Dict  ):
							lowerCAmelCase__   = """tester"""
							lowerCAmelCase__   = """tester"""
							return input_text, output_text




					@unittest.skip("""MGP-STR always lower cases letters."""  )
					def     _SCREAMING_SNAKE_CASE    (						self    :  Optional[int]  ):
							pass




					def     _SCREAMING_SNAKE_CASE    (						self    :  Optional[int]  ):
							lowerCAmelCase__   = self.get_tokenizers(do_lower_case=snake_case__  )
							for tokenizer in tokenizers:
									with self.subTest(F"""{tokenizer.__class__.__name__}"""  ):
											lowerCAmelCase__   = """[SPECIAL_TOKEN]"""

											tokenizer.add_special_tokens({"""cls_token""": special_token}  )
											lowerCAmelCase__   = tokenizer.encode([special_token]	,    add_special_tokens=snake_case__  )
											self.assertEqual(len(snake_case__  )	,    1  )

											lowerCAmelCase__   = tokenizer.decode(snake_case__	,    skip_special_tokens=snake_case__  )
											self.assertTrue(special_token not in decoded  )




					def     _SCREAMING_SNAKE_CASE    (						self    :  List[str]  ):
							lowerCAmelCase__   = self.get_tokenizers()
							for tokenizer in tokenizers:
									with self.subTest(F"""{tokenizer.__class__.__name__}"""  ):
											lowerCAmelCase__ ,       lowerCAmelCase__   = self.get_input_output_texts(snake_case__  )

											lowerCAmelCase__   = tokenizer.tokenize(snake_case__  )
											lowerCAmelCase__   = tokenizer.convert_tokens_to_ids(snake_case__  )
											lowerCAmelCase__   = tokenizer.encode(snake_case__	,    add_special_tokens=snake_case__  )
											self.assertListEqual(snake_case__	,    snake_case__  )

											lowerCAmelCase__   = tokenizer.convert_ids_to_tokens(snake_case__  )
											self.assertNotEqual(len(snake_case__  )	,    0  )
											lowerCAmelCase__   = tokenizer.decode(snake_case__  )
											self.assertIsInstance(snake_case__	,    snake_case__  )

											self.assertEqual(text_a.replace(""" """	,    """"""  )	,    snake_case__  )




					@unittest.skip("""MGP-STR tokenizer only handles one sequence."""  )
					def     _SCREAMING_SNAKE_CASE    (						self    :  Optional[Any]  ):
							pass




					@unittest.skip("""inputs cannot be pretokenized in MgpstrTokenizer"""  )
					def     _SCREAMING_SNAKE_CASE    (						self    :  List[Any]  ):
							pass




