



'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__lowerCAmelCase									=   logging.get_logger(__name__)

__lowerCAmelCase									=   {
    '''junnyu/roformer_chinese_small''': '''https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json''',
    '''junnyu/roformer_chinese_base''': '''https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json''',
    '''junnyu/roformer_chinese_char_small''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json'''
    ),
    '''junnyu/roformer_chinese_char_base''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_discriminator''': (
        '''https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_generator''': (
        '''https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json'''
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}

class 	__magic_name__						(    _UpperCamelCase   ):
							lowerCAmelCase       :    str   				=					'roformer'







							def __init__(							self					:       Tuple	,_UpperCAmelCase					:       str=50000	,_UpperCAmelCase					:       Union[str, Any]=None	,_UpperCAmelCase					:       List[str]=768	,_UpperCAmelCase					:       int=12	,_UpperCAmelCase					:       int=12	,_UpperCAmelCase					:       Any=3072	,_UpperCAmelCase					:       Optional[Any]="gelu"	,_UpperCAmelCase					:       List[Any]=0.1	,_UpperCAmelCase					:       List[Any]=0.1	,_UpperCAmelCase					:       int=1536	,_UpperCAmelCase					:       Union[str, Any]=2	,_UpperCAmelCase					:       Dict=0.02	,_UpperCAmelCase					:       Dict=1E-12	,_UpperCAmelCase					:       int=0	,_UpperCAmelCase					:       Dict=False	,_UpperCAmelCase					:       Any=True	,**_UpperCAmelCase					:       int	,):
									super().__init__(pad_token_id=_UpperCAmelCase	,**_UpperCAmelCase		)

									_a     :      List[Any]        =							vocab_size
									_a     :      Tuple        =							hidden_size if embedding_size is None else embedding_size
									_a     :      int        =							hidden_size
									_a     :      Union[str, Any]        =							num_hidden_layers
									_a     :      Any        =							num_attention_heads
									_a     :      Tuple        =							hidden_act
									_a     :      Optional[Any]        =							intermediate_size
									_a     :      str        =							hidden_dropout_prob
									_a     :      str        =							attention_probs_dropout_prob
									_a     :      int        =							max_position_embeddings
									_a     :      int        =							type_vocab_size
									_a     :      str        =							initializer_range
									_a     :      List[Any]        =							layer_norm_eps
									_a     :      Any        =							rotary_value
									_a     :      int        =							use_cache

class 	__magic_name__						(    _UpperCamelCase   ):







							@property
							def 							__lowercase			(							self					:       Optional[Any]		):
									if self.task == "multiple-choice":
											_a     :      Union[str, Any]        =							{0: 'batch', 1: 'choice', 2: 'sequence'}
									else:
											_a     :      int        =							{0: 'batch', 1: 'sequence'}
									_a     :      List[Any]        =							{0: 'batch', 1: 'sequence'}
									return OrderedDict(
									    [
									        ('input_ids', dynamic_axis),
									        ('attention_mask', dynamic_axis),
									        ('token_type_ids', dynamic_axis),
									    ]		)









'''simple docstring'''

__lowerCAmelCase									=   {
    '''A''': ['''B''', '''C''', '''E'''],
    '''B''': ['''A''', '''D''', '''E'''],
    '''C''': ['''A''', '''F''', '''G'''],
    '''D''': ['''B'''],
    '''E''': ['''A''', '''B''', '''D'''],
    '''F''': ['''C'''],
    '''G''': ['''C'''],
}



def      __lowerCamelCase     (      lowerCAmelCase_						,			lowerCAmelCase_						,			lowerCAmelCase_  )			->      list[str]:
		_a     :      List[Any]        =							set()
		# keep track of all the paths to be checked
		_a     :      Any        =							[[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
				_a     :      Tuple        =							queue.pop(0  )
				# get the last node from the path
				_a     :      Tuple        =							path[-1]
				if node not in explored:
						_a     :      Optional[Any]        =							graph[node]
						# go through all neighbour nodes, construct a new path and
						# push it into the queue
						for neighbour in neighbours:
								_a     :      Any        =							list(lowerCAmelCase_  )
								new_path.append(lowerCAmelCase_  )
								queue.append(lowerCAmelCase_  )
								# return path if neighbour is goal
								if neighbour == goal:
										return new_path

            # mark node as explored
						explored.add(lowerCAmelCase_  )

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



def      __lowerCamelCase     (      lowerCAmelCase_						,			lowerCAmelCase_						,			lowerCAmelCase_  )			->      int:
		if not graph or start not in graph or target not in graph:
				return -1
		if start == target:
				return 0
		_a     :      Optional[int]        =							[start]
		_a     :      Dict        =							set(lowerCAmelCase_  )
		# Keep tab on distances from `start` node.
		_a     :      Dict        =							{start: 0, target: -1}
		while queue:
				_a     :      List[str]        =							queue.pop(0  )
				if node == target:
						_a     :      Any        =							(
						    dist[node] if dist[target] == -1 else min(dist[target]						,			dist[node]  )
						)
				for adjacent in graph[node]:
						if adjacent not in visited:
								visited.add(lowerCAmelCase_  )
								queue.append(lowerCAmelCase_  )
								_a     :      Any        =							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




