






'''simple docstring'''







import json
import os
import unittest

from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin

class _lowercase	(				_lowercase				,      unittest.TestCase		):
							a				      =       DebertaTokenizer
							a				      =       True
							a				      =       DebertaTokenizerFast




							def 		lowerCamelCase_				(							self:				List[str]     ):
														super().setUp()

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

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




							def 		lowerCamelCase_				(							self:				int			,							**UpperCamelCase__:				List[Any]     ):
														kwargs.update(self.special_tokens_map     )
														return self.tokenizer_class.from_pretrained(self.tmpdirname			,							**UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				Any			,							UpperCamelCase__:				Optional[int]     ):
														lowerCamelCase__					:	Tuple         =       """lower newer"""
														lowerCamelCase__					:	Any         =       """lower newer"""
														return input_text, output_text




							def 		lowerCamelCase_				(							self:				Optional[int]     ):
														lowerCamelCase__					:	Union[str, Any]         =       self.get_tokenizer()
														lowerCamelCase__					:	int         =       """lower newer"""
														lowerCamelCase__					:	List[Any]         =       ["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
														lowerCamelCase__					:	Any         =       tokenizer.tokenize(UpperCamelCase__     )
														self.assertListEqual(UpperCamelCase__			,							UpperCamelCase__     )

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




							def 		lowerCamelCase_				(							self:				Dict     ):
														lowerCamelCase__					:	List[str]         =       self.get_tokenizer()
														lowerCamelCase__					:	Union[str, Any]         =       tokenizer("""Hello"""			,							"""World"""     )
														lowerCamelCase__					:	Optional[Any]         =       [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1]
														self.assertListEqual(tokd["""token_type_ids"""]			,							UpperCamelCase__     )




							@slow
							def 		lowerCamelCase_				(							self:				Dict     ):
														lowerCamelCase__					:	Union[str, Any]         =       self.tokenizer_class.from_pretrained("""microsoft/deberta-base"""     )

														lowerCamelCase__					:	List[str]         =       tokenizer.encode("""sequence builders"""			,							add_special_tokens=UpperCamelCase__     )
														lowerCamelCase__					:	Optional[int]         =       tokenizer.encode("""multi-sequence build"""			,							add_special_tokens=UpperCamelCase__     )

														lowerCamelCase__					:	str         =       tokenizer.encode(
														    """sequence builders"""			,							add_special_tokens=UpperCamelCase__			,							add_prefix_space=UpperCamelCase__     )
														lowerCamelCase__					:	List[str]         =       tokenizer.encode(
														    """sequence builders"""			,							"""multi-sequence build"""			,							add_special_tokens=UpperCamelCase__			,							add_prefix_space=UpperCamelCase__     )

														lowerCamelCase__					:	Union[str, Any]         =       tokenizer.build_inputs_with_special_tokens(UpperCamelCase__     )
														lowerCamelCase__					:	List[Any]         =       tokenizer.build_inputs_with_special_tokens(UpperCamelCase__			,							UpperCamelCase__     )

														assert encoded_sentence == encoded_text_from_decode
														assert encoded_pair == encoded_pair_from_decode




							@slow
							def 		lowerCamelCase_				(							self:				Tuple     ):
														lowerCamelCase__					:	Tuple         =       [self.tokenizer_class]
														if self.test_rust_tokenizer:
																					tokenizer_classes.append(self.rust_tokenizer_class     )

														for tokenizer_class in tokenizer_classes:
																					lowerCamelCase__					:	Tuple         =       tokenizer_class.from_pretrained("""microsoft/deberta-base"""     )

																					lowerCamelCase__					:	List[str]         =       [
																					    """ALBERT: A Lite BERT for Self-supervised Learning of Language Representations""",
																					    """ALBERT incorporates two parameter reduction techniques""",
																					    """The first one is a factorized embedding parameterization. By decomposing the large vocabulary"""
																					    """ embedding matrix into two small matrices, we separate the size of the hidden layers from the size of"""
																					    """ vocabulary embedding.""",
																					]

																					lowerCamelCase__					:	List[Any]         =       tokenizer(UpperCamelCase__			,							padding=UpperCamelCase__     )
																					lowerCamelCase__					:	int         =       [tokenizer.decode(UpperCamelCase__			,							skip_special_tokens=UpperCamelCase__     ) for seq in encoding["""input_ids"""]]

																					# fmt: off
																					lowerCamelCase__					:	Union[str, Any]         =       {
																					    """input_ids""": [
																					        [1, 2_118, 11_126, 565, 35, 83, 25_191, 163, 18_854, 13, 12_156, 12, 16_101, 25_376, 13_807, 9, 22_205, 27_893, 1_635, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
																					        [1, 2_118, 11_126, 565, 24_536, 80, 43_797, 4_878, 7_373, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
																					        [1, 133, 78, 65, 16, 10, 3_724, 1_538, 33_183, 11_303, 43_797, 1_938, 4, 870, 24_165, 29_105, 5, 739, 32_644, 33_183, 11_303, 36_173, 88, 80, 650, 7_821, 45_940, 6, 52, 2_559, 5, 1_836, 9, 5, 7_397, 13_171, 31, 5, 1_836, 9, 32_644, 33_183, 11_303, 4, 2]
																					    ],
																					    """token_type_ids""": [
																					        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
																					        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
																					        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
																					    ],
																					    """attention_mask""": [
																					        [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
																					        [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
																					        [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
																					    ]
																					}
																					# fmt: on

																					lowerCamelCase__					:	str         =       [
																					    """ALBERT: A Lite BERT for Self-supervised Learning of Language Representations""",
																					    """ALBERT incorporates two parameter reduction techniques""",
																					    """The first one is a factorized embedding parameterization. By decomposing the large vocabulary"""
																					    """ embedding matrix into two small matrices, we separate the size of the hidden layers from the size of"""
																					    """ vocabulary embedding.""",
																					]

																					self.assertDictEqual(encoding.data			,							UpperCamelCase__     )

																					for expected, decoded in zip(UpperCamelCase__			,							UpperCamelCase__     ):
																												self.assertEqual(UpperCamelCase__			,							UpperCamelCase__     )




from __future__ import annotations




def 			UpperCAmelCase__				(			_A      : float	,      _A      : float	,      _A      : float	,      ):





  '''simple docstring'''







  if (stress, tangential_force, area).count(0							) != 1:
    raise ValueError('''You cannot supply more or less than 2 values'''							)
  elif stress < 0:
    raise ValueError('''Stress cannot be negative'''							)
  elif tangential_force < 0:
    raise ValueError('''Tangential Force cannot be negative'''							)
  elif area < 0:
    raise ValueError('''Area cannot be negative'''							)
  elif stress == 0:
    return (
        "stress",
        tangential_force / area,
    )
  elif tangential_force == 0:
    return (
        "tangential_force",
        stress * area,
    )
  else:
    return (
        "area",
        tangential_force / stress,
    )


if __name__ == "__main__":
       import doctest

       doctest.testmod()
