





import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 	UpperCamelCase__				(   lowerCAmelCase_							,   unittest.TestCase     ):



					'''simple docstring'''

					__snake_case					:			Tuple				=    RobertaTokenizer
					__snake_case					:			Dict				=    RobertaTokenizerFast
					__snake_case					:			Dict				=    True
					__snake_case					:			Optional[int]				=    {"cls_token": "<s>"}






					def        SCREAMING_SNAKE_CASE__						(							self		:					Optional[int] )  ->	List[Any]:




											'''simple docstring'''


											super().setUp()

											# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
											SCREAMING_SNAKE_CASE	=		[
											    """l""",
											    """o""",
											    """w""",
											    """e""",
											    """r""",
											    """s""",
											    """t""",
											    """i""",
											    """d""",
											    """n""",
											    """\u0120""",
											    """\u0120l""",
											    """\u0120n""",
											    """\u0120lo""",
											    """\u0120low""",
											    """er""",
											    """\u0120lowest""",
											    """\u0120newer""",
											    """\u0120wider""",
											    """<unk>""",
											]
											SCREAMING_SNAKE_CASE	=		dict(zip(lowerCamelCase__		,range(len(lowerCamelCase__ ) ) ) )
											SCREAMING_SNAKE_CASE	=		["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
											SCREAMING_SNAKE_CASE	=		{"""unk_token""": """<unk>"""}

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






					def        SCREAMING_SNAKE_CASE__						(							self		:					Optional[Any]		,**lowerCamelCase__		:					int )  ->	str:




											'''simple docstring'''


											kwargs.update(self.special_tokens_map )
											return self.tokenizer_class.from_pretrained(self.tmpdirname		,**lowerCamelCase__ )






					def        SCREAMING_SNAKE_CASE__						(							self		:					Dict		,**lowerCamelCase__		:					Optional[Any] )  ->	Dict:




											'''simple docstring'''


											kwargs.update(self.special_tokens_map )
											return RobertaTokenizerFast.from_pretrained(self.tmpdirname		,**lowerCamelCase__ )






					def        SCREAMING_SNAKE_CASE__						(							self		:					Optional[int]		,lowerCamelCase__		:					Any )  ->	Union[str, Any]:




											'''simple docstring'''


											SCREAMING_SNAKE_CASE	=		"""lower newer"""
											SCREAMING_SNAKE_CASE	=		"""lower newer"""
											return input_text, output_text






					def        SCREAMING_SNAKE_CASE__						(							self		:					Optional[Any] )  ->	Tuple:




											'''simple docstring'''


											SCREAMING_SNAKE_CASE	=		self.tokenizer_class(self.vocab_file		,self.merges_file		,**self.special_tokens_map )
											SCREAMING_SNAKE_CASE	=		"""lower newer"""
											SCREAMING_SNAKE_CASE	=		["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
											SCREAMING_SNAKE_CASE	=		tokenizer.tokenize(lowerCamelCase__ )  # , add_prefix_space=True)
											self.assertListEqual(lowerCamelCase__		,lowerCamelCase__ )

											SCREAMING_SNAKE_CASE	=		tokens + [tokenizer.unk_token]
											SCREAMING_SNAKE_CASE	=		[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase__ )		,lowerCamelCase__ )






					def        SCREAMING_SNAKE_CASE__						(							self		:					List[Any] )  ->	Dict:




											'''simple docstring'''


											SCREAMING_SNAKE_CASE	=		self.get_tokenizer()

											self.assertListEqual(tokenizer.encode("""Hello world!"""		,add_special_tokens=lowerCamelCase__ )		,[0, 31414, 232, 328, 2] )
											self.assertListEqual(
											    tokenizer.encode("""Hello world! cécé herlolip 418"""		,add_special_tokens=lowerCamelCase__ )		,[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]		,)






					@slow
					def        SCREAMING_SNAKE_CASE__						(							self		:					Optional[int] )  ->	Optional[Any]:




											'''simple docstring'''


											SCREAMING_SNAKE_CASE	=		self.tokenizer_class.from_pretrained("""roberta-base""" )

											SCREAMING_SNAKE_CASE	=		tokenizer.encode("""sequence builders"""		,add_special_tokens=lowerCamelCase__ )
											SCREAMING_SNAKE_CASE	=		tokenizer.encode("""multi-sequence build"""		,add_special_tokens=lowerCamelCase__ )

											SCREAMING_SNAKE_CASE	=		tokenizer.encode(
											    """sequence builders"""		,add_special_tokens=lowerCamelCase__		,add_prefix_space=lowerCamelCase__ )
											SCREAMING_SNAKE_CASE	=		tokenizer.encode(
											    """sequence builders"""		,"""multi-sequence build"""		,add_special_tokens=lowerCamelCase__		,add_prefix_space=lowerCamelCase__ )

											SCREAMING_SNAKE_CASE	=		tokenizer.build_inputs_with_special_tokens(lowerCamelCase__ )
											SCREAMING_SNAKE_CASE	=		tokenizer.build_inputs_with_special_tokens(lowerCamelCase__		,lowerCamelCase__ )

											assert encoded_sentence == encoded_text_from_decode
											assert encoded_pair == encoded_pair_from_decode






					def        SCREAMING_SNAKE_CASE__						(							self		:					Union[str, Any] )  ->	List[str]:




											'''simple docstring'''


											SCREAMING_SNAKE_CASE	=		self.get_tokenizer()

											SCREAMING_SNAKE_CASE	=		"""Encode this sequence."""
											SCREAMING_SNAKE_CASE	=		tokenizer.byte_encoder[""" """.encode("""utf-8""" )[0]]

											# Testing encoder arguments
											SCREAMING_SNAKE_CASE	=		tokenizer.encode(lowerCamelCase__		,add_special_tokens=lowerCamelCase__		,add_prefix_space=lowerCamelCase__ )
											SCREAMING_SNAKE_CASE	=		tokenizer.convert_ids_to_tokens(encoded[0] )[0]
											self.assertNotEqual(lowerCamelCase__		,lowerCamelCase__ )

											SCREAMING_SNAKE_CASE	=		tokenizer.encode(lowerCamelCase__		,add_special_tokens=lowerCamelCase__		,add_prefix_space=lowerCamelCase__ )
											SCREAMING_SNAKE_CASE	=		tokenizer.convert_ids_to_tokens(encoded[0] )[0]
											self.assertEqual(lowerCamelCase__		,lowerCamelCase__ )

											tokenizer.add_special_tokens({"""bos_token""": """<s>"""} )
											SCREAMING_SNAKE_CASE	=		tokenizer.encode(lowerCamelCase__		,add_special_tokens=lowerCamelCase__ )
											SCREAMING_SNAKE_CASE	=		tokenizer.convert_ids_to_tokens(encoded[1] )[0]
											self.assertNotEqual(lowerCamelCase__		,lowerCamelCase__ )

											# Testing spaces after special tokens
											SCREAMING_SNAKE_CASE	=		"""<mask>"""
											tokenizer.add_special_tokens(
											    {"""mask_token""": AddedToken(lowerCamelCase__		,lstrip=lowerCamelCase__		,rstrip=lowerCamelCase__ )} )  # mask token has a left space
											SCREAMING_SNAKE_CASE	=		tokenizer.convert_tokens_to_ids(lowerCamelCase__ )

											SCREAMING_SNAKE_CASE	=		"""Encode <mask> sequence"""
											SCREAMING_SNAKE_CASE	=		"""Encode <mask>sequence"""

											SCREAMING_SNAKE_CASE	=		tokenizer.encode(lowerCamelCase__ )
											SCREAMING_SNAKE_CASE	=		encoded.index(lowerCamelCase__ )
											SCREAMING_SNAKE_CASE	=		tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1] )[0]
											self.assertEqual(lowerCamelCase__		,lowerCamelCase__ )

											SCREAMING_SNAKE_CASE	=		tokenizer.encode(lowerCamelCase__ )
											SCREAMING_SNAKE_CASE	=		encoded.index(lowerCamelCase__ )
											SCREAMING_SNAKE_CASE	=		tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1] )[0]
											self.assertNotEqual(lowerCamelCase__		,lowerCamelCase__ )






					def        SCREAMING_SNAKE_CASE__						(							self		:					List[Any] )  ->	Union[str, Any]:




											'''simple docstring'''


											pass






					def        SCREAMING_SNAKE_CASE__						(							self		:					int )  ->	Optional[int]:




											'''simple docstring'''


											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})""" ):
																							SCREAMING_SNAKE_CASE	=		self.rust_tokenizer_class.from_pretrained(lowerCamelCase__		,**lowerCamelCase__ )
																							SCREAMING_SNAKE_CASE	=		self.tokenizer_class.from_pretrained(lowerCamelCase__		,**lowerCamelCase__ )
																							SCREAMING_SNAKE_CASE	=		"""A, <mask> AllenNLP sentence."""
																							SCREAMING_SNAKE_CASE	=		tokenizer_r.encode_plus(lowerCamelCase__		,add_special_tokens=lowerCamelCase__		,return_token_type_ids=lowerCamelCase__ )
																							SCREAMING_SNAKE_CASE	=		tokenizer_p.encode_plus(lowerCamelCase__		,add_special_tokens=lowerCamelCase__		,return_token_type_ids=lowerCamelCase__ )

																							# token_type_ids should put 0 everywhere
																							self.assertEqual(sum(tokens_r["""token_type_ids"""] )		,sum(tokens_p["""token_type_ids"""] ) )

																							# attention_mask should put 1 everywhere, so sum over length should be 1
																							self.assertEqual(
																							    sum(tokens_r["""attention_mask"""] ) / len(tokens_r["""attention_mask"""] )		,sum(tokens_p["""attention_mask"""] ) / len(tokens_p["""attention_mask"""] )		,)

																							SCREAMING_SNAKE_CASE	=		tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""] )
																							SCREAMING_SNAKE_CASE	=		tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""] )

																							# Rust correctly handles the space before the mask while python doesnt
																							self.assertSequenceEqual(tokens_p["""input_ids"""]		,[0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2] )
																							self.assertSequenceEqual(tokens_r["""input_ids"""]		,[0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2] )

																							self.assertSequenceEqual(
																							    lowerCamelCase__		,["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""] )
																							self.assertSequenceEqual(
																							    lowerCamelCase__		,["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""] )






					def        SCREAMING_SNAKE_CASE__						(							self		:					Optional[int] )  ->	Optional[Any]:




											'''simple docstring'''


											for trim_offsets, add_prefix_space in itertools.product([True, False]		,repeat=2 ):
																	SCREAMING_SNAKE_CASE	=		self.rust_tokenizer_class.from_pretrained(
																	    self.tmpdirname		,use_fast=lowerCamelCase__		,add_prefix_space=lowerCamelCase__		,trim_offsets=lowerCamelCase__ )

																	SCREAMING_SNAKE_CASE	=		json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__() )
																	SCREAMING_SNAKE_CASE	=		json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__() )

																	self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]		,lowerCamelCase__ )

																	self.assertEqual(post_processor_state["""add_prefix_space"""]		,lowerCamelCase__ )
																	self.assertEqual(post_processor_state["""trim_offsets"""]		,lowerCamelCase__ )






					def        SCREAMING_SNAKE_CASE__						(							self		:					Union[str, Any] )  ->	List[str]:




											'''simple docstring'''


											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})""" ):
																							SCREAMING_SNAKE_CASE	=		"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
																							SCREAMING_SNAKE_CASE	=		F"""{text_of_1_token} {text_of_1_token}"""

																							SCREAMING_SNAKE_CASE	=		self.rust_tokenizer_class.from_pretrained(
																							    lowerCamelCase__		,use_fast=lowerCamelCase__		,add_prefix_space=lowerCamelCase__		,trim_offsets=lowerCamelCase__ )
																							SCREAMING_SNAKE_CASE	=		tokenizer_r(lowerCamelCase__		,return_offsets_mapping=lowerCamelCase__		,add_special_tokens=lowerCamelCase__ )
																							self.assertEqual(encoding.offset_mapping[0]		,(0, len(lowerCamelCase__ )) )
																							self.assertEqual(
																							    encoding.offset_mapping[1]		,(len(lowerCamelCase__ ) + 1, len(lowerCamelCase__ ) + 1 + len(lowerCamelCase__ ))		,)

																							SCREAMING_SNAKE_CASE	=		self.rust_tokenizer_class.from_pretrained(
																							    lowerCamelCase__		,use_fast=lowerCamelCase__		,add_prefix_space=lowerCamelCase__		,trim_offsets=lowerCamelCase__ )
																							SCREAMING_SNAKE_CASE	=		tokenizer_r(lowerCamelCase__		,return_offsets_mapping=lowerCamelCase__		,add_special_tokens=lowerCamelCase__ )
																							self.assertEqual(encoding.offset_mapping[0]		,(0, len(lowerCamelCase__ )) )
																							self.assertEqual(
																							    encoding.offset_mapping[1]		,(len(lowerCamelCase__ ) + 1, len(lowerCamelCase__ ) + 1 + len(lowerCamelCase__ ))		,)

																							SCREAMING_SNAKE_CASE	=		self.rust_tokenizer_class.from_pretrained(
																							    lowerCamelCase__		,use_fast=lowerCamelCase__		,add_prefix_space=lowerCamelCase__		,trim_offsets=lowerCamelCase__ )
																							SCREAMING_SNAKE_CASE	=		tokenizer_r(lowerCamelCase__		,return_offsets_mapping=lowerCamelCase__		,add_special_tokens=lowerCamelCase__ )
																							self.assertEqual(encoding.offset_mapping[0]		,(0, len(lowerCamelCase__ )) )
																							self.assertEqual(
																							    encoding.offset_mapping[1]		,(len(lowerCamelCase__ ), len(lowerCamelCase__ ) + 1 + len(lowerCamelCase__ ))		,)

																							SCREAMING_SNAKE_CASE	=		self.rust_tokenizer_class.from_pretrained(
																							    lowerCamelCase__		,use_fast=lowerCamelCase__		,add_prefix_space=lowerCamelCase__		,trim_offsets=lowerCamelCase__ )
																							SCREAMING_SNAKE_CASE	=		tokenizer_r(lowerCamelCase__		,return_offsets_mapping=lowerCamelCase__		,add_special_tokens=lowerCamelCase__ )
																							self.assertEqual(encoding.offset_mapping[0]		,(0, len(lowerCamelCase__ )) )
																							self.assertEqual(
																							    encoding.offset_mapping[1]		,(len(lowerCamelCase__ ), len(lowerCamelCase__ ) + 1 + len(lowerCamelCase__ ))		,)

																							SCREAMING_SNAKE_CASE	=		F""" {text}"""

																							# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
																							#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
																							# )
																							# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
																							# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
																							# self.assertEqual(
																							#     encoding.offset_mapping[1],
																							#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
																							# )

																							SCREAMING_SNAKE_CASE	=		self.rust_tokenizer_class.from_pretrained(
																							    lowerCamelCase__		,use_fast=lowerCamelCase__		,add_prefix_space=lowerCamelCase__		,trim_offsets=lowerCamelCase__ )
																							SCREAMING_SNAKE_CASE	=		tokenizer_r(lowerCamelCase__		,return_offsets_mapping=lowerCamelCase__		,add_special_tokens=lowerCamelCase__ )
																							self.assertEqual(encoding.offset_mapping[0]		,(1, 1 + len(lowerCamelCase__ )) )
																							self.assertEqual(
																							    encoding.offset_mapping[1]		,(1 + len(lowerCamelCase__ ) + 1, 1 + len(lowerCamelCase__ ) + 1 + len(lowerCamelCase__ ))		,)

																							SCREAMING_SNAKE_CASE	=		self.rust_tokenizer_class.from_pretrained(
																							    lowerCamelCase__		,use_fast=lowerCamelCase__		,add_prefix_space=lowerCamelCase__		,trim_offsets=lowerCamelCase__ )
																							SCREAMING_SNAKE_CASE	=		tokenizer_r(lowerCamelCase__		,return_offsets_mapping=lowerCamelCase__		,add_special_tokens=lowerCamelCase__ )
																							self.assertEqual(encoding.offset_mapping[0]		,(0, 1 + len(lowerCamelCase__ )) )
																							self.assertEqual(
																							    encoding.offset_mapping[1]		,(1 + len(lowerCamelCase__ ), 1 + len(lowerCamelCase__ ) + 1 + len(lowerCamelCase__ ))		,)

																							SCREAMING_SNAKE_CASE	=		self.rust_tokenizer_class.from_pretrained(
																							    lowerCamelCase__		,use_fast=lowerCamelCase__		,add_prefix_space=lowerCamelCase__		,trim_offsets=lowerCamelCase__ )
																							SCREAMING_SNAKE_CASE	=		tokenizer_r(lowerCamelCase__		,return_offsets_mapping=lowerCamelCase__		,add_special_tokens=lowerCamelCase__ )
																							self.assertEqual(encoding.offset_mapping[0]		,(0, 1 + len(lowerCamelCase__ )) )
																							self.assertEqual(
																							    encoding.offset_mapping[1]		,(1 + len(lowerCamelCase__ ), 1 + len(lowerCamelCase__ ) + 1 + len(lowerCamelCase__ ))		,)









def      __lowercase     (   _SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE			)				->     float:


      '''simple docstring'''


      _validate_point(_SCREAMING_SNAKE_CASE			)
      _validate_point(_SCREAMING_SNAKE_CASE			)
      if len(_SCREAMING_SNAKE_CASE			) != len(_SCREAMING_SNAKE_CASE			):
            raise ValueError("""Both points must be in the same n-dimensional space"""			)

      return float(sum(abs(a - b			) for a, b in zip(_SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE			)			)			)



def      __lowercase     (   _SCREAMING_SNAKE_CASE			)				->     None:


      '''simple docstring'''


      if point:
            if isinstance(_SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE			):
                  for item in point:
                        if not isinstance(_SCREAMING_SNAKE_CASE				,		(int, float)			):
                              SCREAMING_SNAKE_CASE	=		(
                                  """Expected a list of numbers as input, found """
                                  F"""{type(_SCREAMING_SNAKE_CASE			).__name__}"""
                              )
                              raise TypeError(_SCREAMING_SNAKE_CASE			)
            else:
                  SCREAMING_SNAKE_CASE	=		F"""Expected a list of numbers as input, found {type(_SCREAMING_SNAKE_CASE			).__name__}"""
                  raise TypeError(_SCREAMING_SNAKE_CASE			)
      else:
            raise ValueError("""Missing an input"""			)



def      __lowercase     (   _SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE			)				->     float:


      '''simple docstring'''


      _validate_point(_SCREAMING_SNAKE_CASE			)
      _validate_point(_SCREAMING_SNAKE_CASE			)
      if len(_SCREAMING_SNAKE_CASE			) != len(_SCREAMING_SNAKE_CASE			):
            raise ValueError("""Both points must be in the same n-dimensional space"""			)

      return float(sum(abs(x - y			) for x, y in zip(_SCREAMING_SNAKE_CASE				,		_SCREAMING_SNAKE_CASE			)			)			)


if __name__ == "__main__":
      import doctest

      doctest.testmod()


