
"""simple docstring"""





import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin



class __lowerCAmelCase				(					_lowercase     ,				unittest.TestCase      ):




			"""simple docstring"""







			snake_case	      =				BioGptTokenizer
			snake_case	      =				False




			def      lowerCamelCase__     (				self						:					Dict	)      -> Dict:







								"""simple docstring"""
								super().setUp()

								# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
								A_				 =						[
								    "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_				 =						dict(zip(_snake_case       ,   range(len(_snake_case	)	)	)	)
								A_				 =						["l o 123", "lo w 1456", "e r</w> 1789", ""]

								A_				 =						os.path.join(self.tmpdirname       ,   VOCAB_FILES_NAMES["vocab_file"]	)
								A_				 =						os.path.join(self.tmpdirname       ,   VOCAB_FILES_NAMES["merges_file"]	)
								with open(self.vocab_file       ,   "w"	) as fp:
													fp.write(json.dumps(_snake_case	)	)
								with open(self.merges_file       ,   "w"	) as fp:
													fp.write("\n".join(_snake_case	)	)




			def      lowerCamelCase__     (				self						:					int       ,   _snake_case						:					List[str]	)      -> Union[str, Any]:







								"""simple docstring"""
								A_				 =						"lower newer"
								A_				 =						"lower newer"
								return input_text, output_text




			def      lowerCamelCase__     (				self						:					List[str]	)      -> Optional[int]:







								"""simple docstring"""
								A_				 =						BioGptTokenizer(self.vocab_file       ,   self.merges_file	)

								A_				 =						"lower"
								A_				 =						["low", "er</w>"]
								A_				 =						tokenizer.tokenize(_snake_case	)
								self.assertListEqual(_snake_case       ,   _snake_case	)

								A_				 =						tokens + ["<unk>"]
								A_				 =						[14, 15, 20]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(_snake_case	)       ,   _snake_case	)






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







								"""simple docstring"""
								A_				 =						BioGptTokenizer.from_pretrained("microsoft/biogpt"	)

								A_				 =						tokenizer.encode("sequence builders"       ,   add_special_tokens=_snake_case	)
								A_				 =						tokenizer.encode("multi-sequence build"       ,   add_special_tokens=_snake_case	)

								A_				 =						tokenizer.build_inputs_with_special_tokens(_snake_case	)
								A_				 =						tokenizer.build_inputs_with_special_tokens(_snake_case       ,   _snake_case	)

								self.assertTrue(encoded_sentence == [2] + text	)
								self.assertTrue(encoded_pair == [2] + text + [2] + text_a	)






"""simple docstring"""





from __future__ import annotations

from collections import Counter
from random import random



class __lowerCAmelCase				:




			"""simple docstring"""







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







								"""simple docstring"""
								A_				 =						{}




			def      lowerCamelCase__     (				self						:					List[Any]       ,   _snake_case						:					str	)      -> None:







								"""simple docstring"""
								A_				 =						{}




			def      lowerCamelCase__     (				self						:					Optional[int]       ,   _snake_case						:					str       ,   _snake_case						:					str       ,   _snake_case						:					float	)      -> None:







								"""simple docstring"""
								if nodea not in self.connections:
													self.add_node(_snake_case	)
								if nodea not in self.connections:
													self.add_node(_snake_case	)
								A_				 =						probability




			def      lowerCamelCase__     (				self						:					Tuple	)      -> list[str]:







								"""simple docstring"""
								return list(self.connections	)






			def      lowerCamelCase__     (				self						:					Union[str, Any]       ,   _snake_case						:					str	)      -> str:







								"""simple docstring"""
								A_				 =						0
								A_				 =						random()

								for dest in self.connections[node]:
													current_probability += self.connections[node][dest]
													if current_probability > random_value:
																		return dest
								return ""





def 							A_     (__a				,   __a				,   __a				):

					'''simple docstring'''





					A_				 =						MarkovChainGraphUndirectedUnweighted()

					for nodea, nodea, probability in transitions:
										graph.add_transition_probability(__a				,   __a				,   __a				)

					A_				 =						Counter(graph.get_nodes()				)
					A_				 =						start

					for _ in range(__a				):
										A_				 =						graph.transition(__a				)
										visited[node] += 1

					return visited


if __name__ == "__main__":
		import doctest

		doctest.testmod()




