



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        snake_case__    (A__ ,     unittest.TestCase		):







						"""simple docstring"""




						__lowerCAmelCase					:int      =					OpenAIGPTTokenizer
						__lowerCAmelCase					:Optional[int]      =					OpenAIGPTTokenizerFast
						__lowerCAmelCase					:List[str]      =					True
						__lowerCAmelCase					:List[str]      =					False

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				str:
									"""simple docstring"""




									super().setUp()

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

									a__       :						Any							=  os.path.join(self.tmpdirname ,       VOCAB_FILES_NAMES["""vocab_file"""]  )
									a__       :						List[str]							=  os.path.join(self.tmpdirname ,       VOCAB_FILES_NAMES["""merges_file"""]  )
									with open(self.vocab_file ,       """w"""  ) as fp:
												fp.write(json.dumps(__lowercase  )  )
									with open(self.merges_file ,       """w"""  ) as fp:
												fp.write("""\n""".join(__lowercase  )  )

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase  ) ->				List[str]:
									"""simple docstring"""




									return "lower newer", "lower newer"

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				int:
									"""simple docstring"""




									a__       :						Dict							=  OpenAIGPTTokenizer(self.vocab_file ,       self.merges_file  )

									a__       :						Tuple							=  """lower"""
									a__       :						Optional[Any]							=  ["""low""", """er</w>"""]
									a__       :						Dict							=  tokenizer.tokenize(__lowercase  )
									self.assertListEqual(__lowercase ,       __lowercase  )

									a__       :						Any							=  tokens + ["""<unk>"""]
									a__       :						Tuple							=  [1_4, 1_5, 2_0]
									self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowercase  ) ,       __lowercase  )

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase=1_5  ) ->				Dict:
									"""simple docstring"""




									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
												with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
															a__       :						Union[str, Any]							=  self.rust_tokenizer_class.from_pretrained(__lowercase ,       **__lowercase  )

															# Simple input
															a__       :						Optional[Any]							=  """This is a simple input"""
															a__       :						Optional[Any]							=  ["""This is a simple input 1""", """This is a simple input 2"""]
															a__       :						Optional[int]							=  ("""This is a simple input""", """This is a pair""")
															a__       :						Union[str, Any]							=  [
															    ("""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(__lowercase ,       tokenizer_r.encode ,       __lowercase ,       max_length=__lowercase ,       padding="""max_length"""  )

															# Simple input
															self.assertRaises(__lowercase ,       tokenizer_r.encode_plus ,       __lowercase ,       max_length=__lowercase ,       padding="""max_length"""  )

															# Simple input
															self.assertRaises(
															    __lowercase ,       tokenizer_r.batch_encode_plus ,       __lowercase ,       max_length=__lowercase ,       padding="""max_length""" ,       )

															# Pair input
															self.assertRaises(__lowercase ,       tokenizer_r.encode ,       __lowercase ,       max_length=__lowercase ,       padding="""max_length"""  )

															# Pair input
															self.assertRaises(__lowercase ,       tokenizer_r.encode_plus ,       __lowercase ,       max_length=__lowercase ,       padding="""max_length"""  )

															# Pair input
															self.assertRaises(
															    __lowercase ,       tokenizer_r.batch_encode_plus ,       __lowercase ,       max_length=__lowercase ,       padding="""max_length""" ,       )

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				str:
									"""simple docstring"""




									pass




@require_ftfy
@require_spacy
@require_tokenizers
class        snake_case__    (A__		):







						"""simple docstring"""




						pass









from __future__ import annotations

def      lowerCAmelCase_					(  _lowercase    :       float						,       _lowercase    :       float						,       _lowercase    :       float						,       )							->	tuple[str, 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()




