
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


SCREAMING_SNAKE_CASE__   :			int												=    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__   :			Union[str, Any]												=    {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

SCREAMING_SNAKE_CASE__   :			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"
        ),
    },
}

SCREAMING_SNAKE_CASE__   :			Tuple												=    {
    "distilbert-base-uncased": 512,
    "distilbert-base-uncased-distilled-squad": 512,
    "distilbert-base-cased": 512,
    "distilbert-base-cased-distilled-squad": 512,
    "distilbert-base-german-cased": 512,
    "distilbert-base-multilingual-cased": 512,
}


SCREAMING_SNAKE_CASE__   :			Dict												=    {
    "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__     (	__lowercase			):
		a__       :						Tuple        =		VOCAB_FILES_NAMES
		a__       :						List[Any]        =		PRETRAINED_VOCAB_FILES_MAP
		a__       :						int        =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		a__       :						List[Any]        =		PRETRAINED_INIT_CONFIGURATION
		a__       :						str        =		["""input_ids""", """attention_mask"""]
		a__       :						Optional[int]        =		DistilBertTokenizer






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

						__lowerCamelCase    					=	json.loads(self.backend_tokenizer.normalizer.__getstate__()  )
						if (
						    normalizer_state.get('''lowercase'''							,			SCREAMING_SNAKE_CASE__  ) != do_lower_case
						    or normalizer_state.get('''strip_accents'''							,			SCREAMING_SNAKE_CASE__  ) != strip_accents
						    or normalizer_state.get('''handle_chinese_chars'''							,			SCREAMING_SNAKE_CASE__  ) != tokenize_chinese_chars
						):
										__lowerCamelCase    					=	getattr(SCREAMING_SNAKE_CASE__							,			normalizer_state.pop('''type'''  )  )
										__lowerCamelCase    					=	do_lower_case
										__lowerCamelCase    					=	strip_accents
										__lowerCamelCase    					=	tokenize_chinese_chars
										__lowerCamelCase    					=	normalizer_class(**SCREAMING_SNAKE_CASE__  )

						__lowerCamelCase    					=	do_lower_case






		def  __A       (		self		:							Optional[Any]							,			SCREAMING_SNAKE_CASE__		:							Optional[Any]							,			SCREAMING_SNAKE_CASE__		:							int=None  )     ->							Optional[Any]:
						__lowerCamelCase    					=	[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  __A       (		self		:							Optional[int]							,			SCREAMING_SNAKE_CASE__		:							List[int]							,			SCREAMING_SNAKE_CASE__		:							Optional[List[int]] = None  )     ->							List[int]:
						__lowerCamelCase    					=	[self.sep_token_id]
						__lowerCamelCase    					=	[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  __A       (		self		:							Optional[Any]							,			SCREAMING_SNAKE_CASE__		:							str							,			SCREAMING_SNAKE_CASE__		:							Optional[str] = None  )     ->							Tuple[str]:
						__lowerCamelCase    					=	self._tokenizer.model.save(SCREAMING_SNAKE_CASE__							,			name=SCREAMING_SNAKE_CASE__  )
						return tuple(SCREAMING_SNAKE_CASE__  )





from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

SCREAMING_SNAKE_CASE__   :			List[Any]												=    TypeVar("T")




def  __magic_name__ (   __lowerCAmelCase	:						int							)			->   int:
				return (position - 1) // 2




def  __magic_name__ (   __lowerCAmelCase	:						int							)			->   int:
				return (2 * position) + 1




def  __magic_name__ (   __lowerCAmelCase	:						int							)			->   int:
				return (2 * position) + 2

class    lowerCAmelCase__     (	Generic[T]			):






		def __init__(		self		:							List[str]  )     ->							None:
						__lowerCamelCase    					=	[]
						__lowerCamelCase    					=	{}
						__lowerCamelCase    					=	0






		def __len__(		self		:							Optional[int]  )     ->							int:
						return self.elements






		def __repr__(		self		:							Optional[int]  )     ->							str:
						return str(self.heap  )






		def  __A       (		self		:							Union[str, Any]  )     ->							bool:
						# Check if the priority queue is empty
						return self.elements == 0






		def  __A       (		self		:							str							,			SCREAMING_SNAKE_CASE__		:							T							,			SCREAMING_SNAKE_CASE__		:							int  )     ->							None:
						# Add an element with given priority to the queue
						self.heap.append((elem, weight)  )
						__lowerCamelCase    					=	self.elements
						self.elements += 1
						self._bubble_up(SCREAMING_SNAKE_CASE__  )






		def  __A       (		self		:							Any  )     ->							T:
						# Remove and return the element with lowest weight (highest priority)
						if self.elements > 1:
										self._swap_nodes(0							,			self.elements - 1  )
						__lowerCamelCase					,    __lowerCamelCase    					=	self.heap.pop()
						del self.position_map[elem]
						self.elements -= 1
						if self.elements > 0:
										__lowerCamelCase					,    __lowerCamelCase    					=	self.heap[0]
										self._bubble_down(SCREAMING_SNAKE_CASE__  )
						return elem






		def  __A       (		self		:							Dict							,			SCREAMING_SNAKE_CASE__		:							T							,			SCREAMING_SNAKE_CASE__		:							int  )     ->							None:
						# Update the weight of the given key
						__lowerCamelCase    					=	self.position_map[elem]
						__lowerCamelCase    					=	(elem, weight)
						if position > 0:
										__lowerCamelCase    					=	get_parent_position(SCREAMING_SNAKE_CASE__  )
										__lowerCamelCase					,    __lowerCamelCase    					=	self.heap[parent_position]
										if parent_weight > weight:
														self._bubble_up(SCREAMING_SNAKE_CASE__  )
										else:
														self._bubble_down(SCREAMING_SNAKE_CASE__  )
						else:
										self._bubble_down(SCREAMING_SNAKE_CASE__  )






		def  __A       (		self		:							Optional[int]							,			SCREAMING_SNAKE_CASE__		:							T  )     ->							None:
						# Place a node at the proper position (upward movement) [to be used internally
						# only]
						__lowerCamelCase    					=	self.position_map[elem]
						if curr_pos == 0:
										return None
						__lowerCamelCase    					=	get_parent_position(SCREAMING_SNAKE_CASE__  )
						__lowerCamelCase					,    __lowerCamelCase    					=	self.heap[curr_pos]
						__lowerCamelCase					,    __lowerCamelCase    					=	self.heap[parent_position]
						if parent_weight > weight:
										self._swap_nodes(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  )
										return self._bubble_up(SCREAMING_SNAKE_CASE__  )
						return None






		def  __A       (		self		:							Optional[int]							,			SCREAMING_SNAKE_CASE__		:							T  )     ->							None:
						# Place a node at the proper position (downward movement) [to be used
						# internally only]
						__lowerCamelCase    					=	self.position_map[elem]
						__lowerCamelCase					,    __lowerCamelCase    					=	self.heap[curr_pos]
						__lowerCamelCase    					=	get_child_left_position(SCREAMING_SNAKE_CASE__  )
						__lowerCamelCase    					=	get_child_right_position(SCREAMING_SNAKE_CASE__  )
						if child_left_position < self.elements and child_right_position < self.elements:
										__lowerCamelCase					,    __lowerCamelCase    					=	self.heap[child_left_position]
										__lowerCamelCase					,    __lowerCamelCase    					=	self.heap[child_right_position]
										if child_right_weight < child_left_weight and child_right_weight < weight:
														self._swap_nodes(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  )
														return self._bubble_down(SCREAMING_SNAKE_CASE__  )
						if child_left_position < self.elements:
										__lowerCamelCase					,    __lowerCamelCase    					=	self.heap[child_left_position]
										if child_left_weight < weight:
														self._swap_nodes(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  )
														return self._bubble_down(SCREAMING_SNAKE_CASE__  )
						else:
										return None
						if child_right_position < self.elements:
										__lowerCamelCase					,    __lowerCamelCase    					=	self.heap[child_right_position]
										if child_right_weight < weight:
														self._swap_nodes(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  )
														return self._bubble_down(SCREAMING_SNAKE_CASE__  )
						return None







		def  __A       (		self		:							List[Any]							,			SCREAMING_SNAKE_CASE__		:							int							,			SCREAMING_SNAKE_CASE__		:							int  )     ->							None:
						# Swap the nodes at the given positions
						__lowerCamelCase    					=	self.heap[nodea_pos][0]
						__lowerCamelCase    					=	self.heap[nodea_pos][0]
						__lowerCamelCase					,    __lowerCamelCase    					=	(
						    self.heap[nodea_pos],
						    self.heap[nodea_pos],
						)
						__lowerCamelCase    					=	nodea_pos
						__lowerCamelCase    					=	nodea_pos





class    lowerCAmelCase__     (	Generic[T]			):






		def __init__(		self		:							Tuple  )     ->							None:
						__lowerCamelCase    					=	{}
						__lowerCamelCase    					=	0






		def __repr__(		self		:							Optional[int]  )     ->							str:
						return str(self.connections  )






		def __len__(		self		:							List[str]  )     ->							int:
						return self.nodes






		def  __A       (		self		:							List[str]							,			SCREAMING_SNAKE_CASE__		:							T  )     ->							None:
						# Add a node in the graph if it is not in the graph
						if node not in self.connections:
										__lowerCamelCase    					=	{}
										self.nodes += 1







		def  __A       (		self		:							Dict							,			SCREAMING_SNAKE_CASE__		:							T							,			SCREAMING_SNAKE_CASE__		:							T							,			SCREAMING_SNAKE_CASE__		:							int  )     ->							None:
						# Add an edge between 2 nodes in the graph
						self.add_node(SCREAMING_SNAKE_CASE__  )
						self.add_node(SCREAMING_SNAKE_CASE__  )
						__lowerCamelCase    					=	weight
						__lowerCamelCase    					=	weight





def  __magic_name__ (   __lowerCAmelCase	:						GraphUndirectedWeighted[T]		,  )			->   tuple[dict[T, int], dict[T, T | None]]:
				__lowerCamelCase    					=	{node: maxsize for node in graph.connections}
				__lowerCamelCase    					=	{node: None for node in graph.connections}

				__lowerCamelCase    					=	MinPriorityQueue()
				for node, weight in dist.items():
								priority_queue.push(__lowerCAmelCase		,  __lowerCAmelCase							)

				if priority_queue.is_empty():
								return dist, parent

				# initialization
				__lowerCamelCase    					=	priority_queue.extract_min()
				__lowerCamelCase    					=	0
				for neighbour in graph.connections[node]:
								if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
												__lowerCamelCase    					=	dist[node] + graph.connections[node][neighbour]
												priority_queue.update_key(__lowerCAmelCase		,  dist[neighbour]							)
												__lowerCamelCase    					=	node

    # running prim's algorithm
				while not priority_queue.is_empty():
								__lowerCamelCase    					=	priority_queue.extract_min()
								for neighbour in graph.connections[node]:
												if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
																__lowerCamelCase    					=	dist[node] + graph.connections[node][neighbour]
																priority_queue.update_key(__lowerCAmelCase		,  dist[neighbour]							)
																__lowerCamelCase    					=	node
				return dist, parent



