




from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

__A        =    TypeVar("T")







def 			lowerCamelCase_		(       UpperCamelCase__				:      int      )     ->       int:





				"""simple docstring"""


				return (position - 1) // 2







def 			lowerCamelCase_		(       UpperCamelCase__				:      int      )     ->       int:





				"""simple docstring"""


				return (2 * position) + 1







def 			lowerCamelCase_		(       UpperCamelCase__				:      int      )     ->       int:





				"""simple docstring"""


				return (2 * position) + 2







class     __lowerCAmelCase (       Generic[T] ):

			"""simple docstring"""







			def __init__(      self							)    ->      None:



							'''simple docstring'''
							__lowerCamelCase		       =    []
							__lowerCamelCase		       =    {}
							__lowerCamelCase		       =    0


			def __len__(      self							)    ->      int:



							'''simple docstring'''
							return self.elements


			def __repr__(      self							)    ->      str:



							'''simple docstring'''
							return str(self.heap							)


			def       lowercase_    (      self							)    ->      bool:



							'''simple docstring'''
							# Check if the priority queue is empty
							return self.elements == 0


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__							)    ->      None:



							'''simple docstring'''
							# Add an element with given priority to the queue
							self.heap.append((elem, weight)							)
							__lowerCamelCase		       =    self.elements
							self.elements += 1
							self._bubble_up(lowerCamelCase__							)


			def       lowercase_    (      self							)    ->      T:



							'''simple docstring'''
							# 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(lowerCamelCase__							)
							return elem


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__							)    ->      None:



							'''simple docstring'''
							# Update the weight of the given key
							__lowerCamelCase		       =    self.position_map[elem]
							__lowerCamelCase		       =    (elem, weight)
							if position > 0:
											__lowerCamelCase		       =    get_parent_position(lowerCamelCase__							)
											__lowerCamelCase       ,						__lowerCamelCase		       =    self.heap[parent_position]
											if parent_weight > weight:
															self._bubble_up(lowerCamelCase__							)
											else:
															self._bubble_down(lowerCamelCase__							)
							else:
											self._bubble_down(lowerCamelCase__							)


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      None:



							'''simple docstring'''
							# 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(lowerCamelCase__							)
							__lowerCamelCase       ,						__lowerCamelCase		       =    self.heap[curr_pos]
							__lowerCamelCase       ,						__lowerCamelCase		       =    self.heap[parent_position]
							if parent_weight > weight:
											self._swap_nodes(lowerCamelCase__			,						lowerCamelCase__							)
											return self._bubble_up(lowerCamelCase__							)
							return None


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      None:



							'''simple docstring'''
							# 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(lowerCamelCase__							)
							__lowerCamelCase		       =    get_child_right_position(lowerCamelCase__							)
							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(lowerCamelCase__			,						lowerCamelCase__							)
															return self._bubble_down(lowerCamelCase__							)
							if child_left_position < self.elements:
											__lowerCamelCase       ,						__lowerCamelCase		       =    self.heap[child_left_position]
											if child_left_weight < weight:
															self._swap_nodes(lowerCamelCase__			,						lowerCamelCase__							)
															return self._bubble_down(lowerCamelCase__							)
							else:
											return None
							if child_right_position < self.elements:
											__lowerCamelCase       ,						__lowerCamelCase		       =    self.heap[child_right_position]
											if child_right_weight < weight:
															self._swap_nodes(lowerCamelCase__			,						lowerCamelCase__							)
															return self._bubble_down(lowerCamelCase__							)
							return None






			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__							)    ->      None:



							'''simple docstring'''
							# 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] ):

			"""simple docstring"""







			def __init__(      self							)    ->      None:



							'''simple docstring'''
							__lowerCamelCase		       =    {}
							__lowerCamelCase		       =    0


			def __repr__(      self							)    ->      str:



							'''simple docstring'''
							return str(self.connections							)


			def __len__(      self							)    ->      int:



							'''simple docstring'''
							return self.nodes


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      None:



							'''simple docstring'''
							# Add a node in the graph if it is not in the graph
							if node not in self.connections:
											__lowerCamelCase		       =    {}
											self.nodes += 1






			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__			,						lowerCamelCase__							)    ->      None:



							'''simple docstring'''
							# Add an edge between 2 nodes in the graph
							self.add_node(lowerCamelCase__							)
							self.add_node(lowerCamelCase__							)
							__lowerCamelCase		       =    weight
							__lowerCamelCase		       =    weight







def 			lowerCamelCase_		(       UpperCamelCase__				:      GraphUndirectedWeighted[T] ,     )     ->       tuple[dict[T, int], dict[T, T | None]]:





				"""simple docstring"""


				__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(UpperCamelCase__ ,     UpperCamelCase__      )

				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(UpperCamelCase__ ,     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(UpperCamelCase__ ,     dist[neighbour]      )
																__lowerCamelCase		       =    node
				return dist, parent








import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
					from transformers.pipelines.conversational import Conversation


__A        =    logging.get_logger(__name__)

__A        =    {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

__A        =    {
    "tokenizer_file": {
        "EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json",
    },
}

__A        =    {
    "gpt-neox-20b": 20_48,
}







class     __lowerCAmelCase (       __magic_name__ ):

			"""simple docstring"""







			snake_case_   		=       VOCAB_FILES_NAMES
			snake_case_   		=       PRETRAINED_VOCAB_FILES_MAP
			snake_case_   		=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			snake_case_   		=       ['''input_ids''', '''attention_mask''']


			def __init__(      self			,						lowerCamelCase__=None			,						lowerCamelCase__=None			,						lowerCamelCase__=None			,						lowerCamelCase__="<|endoftext|>"			,						lowerCamelCase__="<|endoftext|>"			,						lowerCamelCase__="<|endoftext|>"			,						lowerCamelCase__=False			,						**lowerCamelCase__			,						)    ->      int:



							'''simple docstring'''
							super().__init__(
							    lowerCamelCase__			,						lowerCamelCase__			,						tokenizer_file=lowerCamelCase__			,						unk_token=lowerCamelCase__			,						bos_token=lowerCamelCase__			,						eos_token=lowerCamelCase__			,						add_prefix_space=lowerCamelCase__			,						**lowerCamelCase__			,						)

							__lowerCamelCase		       =    json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()							)
							if pre_tok_state.get('add_prefix_space'			,						lowerCamelCase__							) != add_prefix_space:
											__lowerCamelCase		       =    getattr(lowerCamelCase__			,						pre_tok_state.pop('type'							)							)
											__lowerCamelCase		       =    add_prefix_space
											__lowerCamelCase		       =    pre_tok_class(**lowerCamelCase__							)

							__lowerCamelCase		       =    add_prefix_space


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__ = None							)    ->      Tuple[str]:



							'''simple docstring'''
							__lowerCamelCase		       =    self._tokenizer.model.save(lowerCamelCase__			,						name=lowerCamelCase__							)
							return tuple(lowerCamelCase__							)






			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      List[int]:



							'''simple docstring'''
							__lowerCamelCase		       =    []
							for is_user, text in conversation.iter_texts():
											input_ids.extend(self.encode(lowerCamelCase__			,						add_special_tokens=lowerCamelCase__							) + [self.eos_token_id]							)

							if len(lowerCamelCase__							) > self.model_max_length:
											__lowerCamelCase		       =    input_ids[-self.model_max_length :]
							return input_ids


