





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer


__UpperCamelCase:	Any = logging.get_logger(__name__)

__UpperCamelCase:	str = {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

__UpperCamelCase:	Optional[Any] = {
    """vocab_file""": {
        """distilbert-base-uncased""": """https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt""",
        """distilbert-base-uncased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/vocab.txt"""
        ),
        """distilbert-base-cased""": """https://huggingface.co/distilbert-base-cased/resolve/main/vocab.txt""",
        """distilbert-base-cased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/vocab.txt"""
        ),
        """distilbert-base-german-cased""": """https://huggingface.co/distilbert-base-german-cased/resolve/main/vocab.txt""",
        """distilbert-base-multilingual-cased""": (
            """https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/vocab.txt"""
        ),
    },
    """tokenizer_file""": {
        """distilbert-base-uncased""": """https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json""",
        """distilbert-base-uncased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/tokenizer.json"""
        ),
        """distilbert-base-cased""": """https://huggingface.co/distilbert-base-cased/resolve/main/tokenizer.json""",
        """distilbert-base-cased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/tokenizer.json"""
        ),
        """distilbert-base-german-cased""": (
            """https://huggingface.co/distilbert-base-german-cased/resolve/main/tokenizer.json"""
        ),
        """distilbert-base-multilingual-cased""": (
            """https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/tokenizer.json"""
        ),
    },
}

__UpperCamelCase:	Any = {
    """distilbert-base-uncased""": 5_1_2,
    """distilbert-base-uncased-distilled-squad""": 5_1_2,
    """distilbert-base-cased""": 5_1_2,
    """distilbert-base-cased-distilled-squad""": 5_1_2,
    """distilbert-base-german-cased""": 5_1_2,
    """distilbert-base-multilingual-cased""": 5_1_2,
}


__UpperCamelCase:	Tuple = {
    """distilbert-base-uncased""": {"""do_lower_case""": True},
    """distilbert-base-uncased-distilled-squad""": {"""do_lower_case""": True},
    """distilbert-base-cased""": {"""do_lower_case""": False},
    """distilbert-base-cased-distilled-squad""": {"""do_lower_case""": False},
    """distilbert-base-german-cased""": {"""do_lower_case""": False},
    """distilbert-base-multilingual-cased""": {"""do_lower_case""": False},
}


class       __lowerCAmelCase					(       _UpperCamelCase      ):


	'''simple docstring'''





	_A													=				VOCAB_FILES_NAMES
	_A													=				PRETRAINED_VOCAB_FILES_MAP
	_A													=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_A													=				PRETRAINED_INIT_CONFIGURATION
	_A													=				["input_ids", "attention_mask"]
	_A													=				DistilBertTokenizer

	def __init__(						self:						str,					lowerCamelCase_:						int=None,					lowerCamelCase_:						int=None,					lowerCamelCase_:						Optional[Any]=True,					lowerCamelCase_:						Optional[int]="[UNK]",					lowerCamelCase_:						Any="[SEP]",					lowerCamelCase_:						Union[str, Any]="[PAD]",					lowerCamelCase_:						Optional[int]="[CLS]",					lowerCamelCase_:						List[str]="[MASK]",					lowerCamelCase_:						Tuple=True,					lowerCamelCase_:						List[Any]=None,					**lowerCamelCase_:						Optional[Any],					):
			super().__init__(
			    lowerCamelCase_,					tokenizer_file=lowerCamelCase_,					do_lower_case=lowerCamelCase_,					unk_token=lowerCamelCase_,					sep_token=lowerCamelCase_,					pad_token=lowerCamelCase_,					cls_token=lowerCamelCase_,					mask_token=lowerCamelCase_,					tokenize_chinese_chars=lowerCamelCase_,					strip_accents=lowerCamelCase_,					**lowerCamelCase_,					)

			lowercase__					:      List[str]      =		json.loads(self.backend_tokenizer.normalizer.__getstate__()			)
			if (
			    normalizer_state.get('lowercase',					lowerCamelCase_			) != do_lower_case
			    or normalizer_state.get('strip_accents',					lowerCamelCase_			) != strip_accents
			    or normalizer_state.get('handle_chinese_chars',					lowerCamelCase_			) != tokenize_chinese_chars
			):
					lowercase__					:      int      =		getattr(lowerCamelCase_,					normalizer_state.pop('type'			)			)
					lowercase__					:      int      =		do_lower_case
					lowercase__					:      List[Any]      =		strip_accents
					lowercase__					:      Optional[int]      =		tokenize_chinese_chars
					lowercase__					:      int      =		normalizer_class(**lowerCamelCase_			)

			lowercase__					:      Union[str, Any]      =		do_lower_case

	def    snake_case__(						self:						int,					lowerCamelCase_:						List[Any],					lowerCamelCase_:						Optional[int]=None			):
			lowercase__					:      Any      =		[self.cls_token_id] + token_ids_a + [self.sep_token_id]

			if token_ids_a:
					output += token_ids_a + [self.sep_token_id]

			return output

	def    snake_case__(						self:						Union[str, Any],					lowerCamelCase_:						List[int],					lowerCamelCase_:						Optional[List[int]] = None			):
			lowercase__					:      List[Any]      =		[self.sep_token_id]
			lowercase__					:      int      =		[self.cls_token_id]
			if token_ids_a is None:
					return len(cls + token_ids_a + sep			) * [0]
			return len(cls + token_ids_a + sep			) * [0] + len(token_ids_a + sep			) * [1]





	def    snake_case__(						self:						Optional[int],					lowerCamelCase_:						str,					lowerCamelCase_:						Optional[str] = None			):
			lowercase__					:      Tuple      =		self._tokenizer.model.save(lowerCamelCase_,					name=lowerCamelCase_			)
			return tuple(lowerCamelCase_			)









from __future__ import annotations


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : list[float]   ,    _lowercase     : Tuple			)   ->							int:




		'''simple docstring'''
		print(f"""Vertex\tShortest Distance from vertex {src}"""			)
		for i, d in enumerate(_lowercase			):
				print(f"""{i}\t\t{d}"""			)


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : list[dict[str, int]]   ,    _lowercase     : list[float]   ,    _lowercase     : int			)   ->							Any:




		'''simple docstring'''
		for j in range(_lowercase			):
				lowercase__   ,				lowercase__   ,				lowercase__					:      Dict      =		(graph[j][k] for k in ['src', 'dst', 'weight'])
				if distance[u] != float('inf'			) and distance[u] + w < distance[v]:
						return True
		return False


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : list[dict[str, int]]   ,    _lowercase     : int   ,    _lowercase     : int   ,    _lowercase     : int			)   ->							list[float]:




		'''simple docstring'''
		lowercase__					:      Dict      =		[float('inf'			)] * vertex_count
		lowercase__					:      Dict      =		0.0

		for _ in range(vertex_count - 1			):
				for j in range(_lowercase			):
						lowercase__   ,				lowercase__   ,				lowercase__					:      int      =		(graph[j][k] for k in ['src', 'dst', 'weight'])

						if distance[u] != float('inf'			) and distance[u] + w < distance[v]:
								lowercase__					:      str      =		distance[u] + w

		lowercase__					:      str      =		check_negative_cycle(_lowercase   ,    _lowercase   ,    _lowercase			)
		if negative_cycle_exists:
				raise Exception('Negative cycle found'			)

		return distance


if __name__ == "__main__":
			import doctest

			doctest.testmod()

			__UpperCamelCase:	Optional[int] = int(input("""Enter number of vertices: """).strip())
			__UpperCamelCase:	Union[str, Any] = int(input("""Enter number of edges: """).strip())

			__UpperCamelCase:	list[dict[str, int]] = [{} for _ in range(E)]

			for i in range(E):
						print("""Edge """, i + 1)
						__UpperCamelCase,	__UpperCamelCase,	__UpperCamelCase:	List[str] = (
						    int(x)
						    for x in input("""Enter source, destination, weight: """).strip().split(""" """)
						)
						__UpperCamelCase:	List[Any] = {"""src""": src, """dst""": dest, """weight""": weight}

			__UpperCamelCase:	Optional[int] = int(input("""\nEnter shortest path source:""").strip())
			__UpperCamelCase:	Dict = bellman_ford(graph, V, E, source)
			print_distance(shortest_distance, 0)


