
'''simple docstring'''
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union

import torch

from ..utils import BaseOutput


lowerCAmelCase					:    List[Any]           = 'scheduler_config.json'


class 			SCREAMING_SNAKE_CASE__      (     snake_case_):
				lowerCAmelCase_     			=							1
				lowerCAmelCase_     			=							2
				lowerCAmelCase_     			=							3
				lowerCAmelCase_     			=							4
				lowerCAmelCase_     			=							5
				lowerCAmelCase_     			=							6
				lowerCAmelCase_     			=							7
				lowerCAmelCase_     			=							8
				lowerCAmelCase_     			=							9
				lowerCAmelCase_     			=							10
				lowerCAmelCase_     			=							11
				lowerCAmelCase_     			=							12
				lowerCAmelCase_     			=							13
				lowerCAmelCase_     			=							14


@dataclass
class 			SCREAMING_SNAKE_CASE__      (     snake_case_):
				lowerCAmelCase_     			=							42


class 			SCREAMING_SNAKE_CASE__      :
				lowerCAmelCase_     			=							SCHEDULER_CONFIG_NAME
				lowerCAmelCase_     			=							[]
				lowerCAmelCase_     			=							True







				@classmethod
				def 						UpperCAmelCase_    (       cls						,				A_ = None						,				A_ = None						,				A_=False						,				**A_						,				)->		List[Any]:







											'''simple docstring'''






											UpperCamelCase			,	UpperCamelCase			,	UpperCamelCase   			=     cls.load_config(
											    pretrained_model_name_or_path=A_						,				subfolder=A_						,				return_unused_kwargs=A_						,				return_commit_hash=A_						,				**A_						,				)
											return cls.from_config(A_						,				return_unused_kwargs=A_						,				**A_     )







				def 						UpperCAmelCase_    (       self						,				A_						,				A_ = False						,				**A_     )->		Any:







											'''simple docstring'''






											self.save_config(save_directory=A_						,				push_to_hub=A_						,				**A_     )







				@property
				def 						UpperCAmelCase_    (       self     )->		Optional[Any]:







											'''simple docstring'''






											return self._get_compatibles()







				@classmethod
				def 						UpperCAmelCase_    (       cls     )->		Any:







											'''simple docstring'''






											UpperCamelCase   			=     list(set([cls.__name__] + cls._compatibles     )     )
											UpperCamelCase   			=     importlib.import_module(__name__.split('.'     )[0]     )
											UpperCamelCase   			=     [
											    getattr(A_						,				A_     ) for c in compatible_classes_str if hasattr(A_						,				A_     )
											]
											return compatible_classes






'''simple docstring'''
lowerCAmelCase					:    Optional[Any]           = {
    'A': ['B', 'C', 'E'],
    'B': ['A', 'D', 'E'],
    'C': ['A', 'F', 'G'],
    'D': ['B'],
    'E': ['A', 'B', 'D'],
    'F': ['C'],
    'G': ['C'],
}







def 		A_(     A						:		dict		,     A						:		str		,     A						:		Optional[Any]):
							UpperCamelCase   			=     set()
							# keep track of all the paths to be checked
							UpperCamelCase   			=     [[start]]

							# return path if start is goal
							if start == goal:
														return [start]

							# keeps looping until all possible paths have been checked
							while queue:
														# pop the first path from the queue
														UpperCamelCase   			=     queue.pop(0)
														# get the last node from the path
														UpperCamelCase   			=     path[-1]
														if node not in explored:
																					UpperCamelCase   			=     graph[node]
																					# go through all neighbour nodes, construct a new path and
																					# push it into the queue
																					for neighbour in neighbours:
																												UpperCamelCase   			=     list(A)
																												new_path.append(A)
																												queue.append(A)
																												# return path if neighbour is goal
																												if neighbour == goal:
																																			return new_path

            # mark node as explored
																					explored.add(A)

    # in case there's no path between the 2 nodes
							return []







def 		A_(     A						:		dict		,     A						:		str		,     A						:		Tuple):
							if not graph or start not in graph or target not in graph:
														return -1
							if start == target:
														return 0
							UpperCamelCase   			=     [start]
							UpperCamelCase   			=     set(A)
							# Keep tab on distances from `start` node.
							UpperCamelCase   			=     {start: 0, target: -1}
							while queue:
														UpperCamelCase   			=     queue.pop(0)
														if node == target:
																					UpperCamelCase   			=     (
																					    dist[node] if dist[target] == -1 else min(dist[target]		,     dist[node])
																					)
														for adjacent in graph[node]:
																					if adjacent not in visited:
																												visited.add(A)
																												queue.append(A)
																												UpperCamelCase   			=     dist[node] + 1
							return dist[target]


if __name__ == "__main__":
						print(bfs_shortest_path(demo_graph, 'G', 'D'))  # returns ['G', 'C', 'A', 'B', 'D']
						print(bfs_shortest_path_distance(demo_graph, 'G', 'D'))  # returns 4




