


'''simple docstring'''




from __future__ import annotations

__snake_case    						={
    """A""": ["""B""", """C""", """E"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F""", """G"""],
    """D""": ["""B"""],
    """E""": ["""A""", """B""", """D"""],
    """F""": ["""C"""],
    """G""": ["""C"""],
}

class 		UpperCAmelCase_      :





     def __init__( self       :      List[Any]    ,      UpperCAmelCase__       :      dict[str, list[str]]    ,      UpperCAmelCase__       :      str    )				->  None:
        lowerCAmelCase     =			graph
        # mapping node to its parent in resulting breadth first tree
        lowerCAmelCase     =			{}
        lowerCAmelCase     =			source_vertex





     def 							__UpperCAmelCase      ( self       :      Tuple    )				->  None:
        lowerCAmelCase     =			{self.source_vertex}
        lowerCAmelCase     =			None
        lowerCAmelCase     =			[self.source_vertex]  # first in first out queue

        while queue:
           lowerCAmelCase     =			queue.pop(0    )
           for adjacent_vertex in self.graph[vertex]:
              if adjacent_vertex not in visited:
                 visited.add(UpperCAmelCase__    )
                 lowerCAmelCase     =			vertex
                 queue.append(UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      List[str]    ,      UpperCAmelCase__       :      str    )				->  str:
        if target_vertex == self.source_vertex:
           return self.source_vertex

        lowerCAmelCase     =			self.parent.get(UpperCAmelCase__    )
        if target_vertex_parent is None:
           lowerCAmelCase     =			(
               F'''No path from vertex: {self.source_vertex} to vertex: {target_vertex}'''
           )
           raise ValueError(UpperCAmelCase__    )

        return self.shortest_path(UpperCAmelCase__    ) + F'''->{target_vertex}'''


if __name__ == "__main__":
       __snake_case    						=Graph(graph, """G""")
       g.breath_first_search()
       print(g.shortest_path("""D"""))
       print(g.shortest_path("""G"""))
       print(g.shortest_path("""Foo"""))









'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case    						=logging.get_logger(__name__)

__snake_case    						={
    """facebook/s2t-wav2vec2-large-en-de""": (
        """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json"""
    ),
    # See all Speech2Text models at https://huggingface.co/models?filter=speech2text2
}

class 		UpperCAmelCase_      (  __lowercase		):
     lowerCamelCase				:	Union[str, Any]		=     '''speech_to_text_2'''
     lowerCamelCase				:	Any		=     ['''past_key_values''']
     lowerCamelCase				:	Optional[Any]		=     {'''num_attention_heads''': '''decoder_attention_heads''', '''hidden_size''': '''d_model'''}





     def __init__( self       :      Optional[int]    ,      UpperCAmelCase__       :      Optional[Any]=1_0_0_0_0    ,      UpperCAmelCase__       :      int=6    ,      UpperCAmelCase__       :      Optional[Any]=2_0_4_8    ,      UpperCAmelCase__       :      Union[str, Any]=4    ,      UpperCAmelCase__       :      List[Any]=0.0    ,      UpperCAmelCase__       :      str=True    ,      UpperCAmelCase__       :      str="relu"    ,      UpperCAmelCase__       :      Any=2_5_6    ,      UpperCAmelCase__       :      Optional[Any]=0.1    ,      UpperCAmelCase__       :      Any=0.0    ,      UpperCAmelCase__       :      Tuple=0.0    ,      UpperCAmelCase__       :      List[Any]=0.02    ,      UpperCAmelCase__       :      List[Any]=2    ,      UpperCAmelCase__       :      str=True    ,      UpperCAmelCase__       :      List[str]=1    ,      UpperCAmelCase__       :      Any=0    ,      UpperCAmelCase__       :      Dict=2    ,      UpperCAmelCase__       :      int=1_0_2_4    ,      **UpperCAmelCase__       :      Optional[Any]    ,      )				->  Dict:
        lowerCAmelCase     =			vocab_size
        lowerCAmelCase     =			d_model
        lowerCAmelCase     =			decoder_ffn_dim
        lowerCAmelCase     =			decoder_layers
        lowerCAmelCase     =			decoder_attention_heads
        lowerCAmelCase     =			dropout
        lowerCAmelCase     =			attention_dropout
        lowerCAmelCase     =			activation_dropout
        lowerCAmelCase     =			activation_function
        lowerCAmelCase     =			init_std
        lowerCAmelCase     =			decoder_layerdrop
        lowerCAmelCase     =			use_cache
        lowerCAmelCase     =			decoder_layers
        lowerCAmelCase     =			scale_embedding  # scale factor will be sqrt(d_model) if True
        lowerCAmelCase     =			max_target_positions

        super().__init__(
            pad_token_id=UpperCAmelCase__    ,      bos_token_id=UpperCAmelCase__    ,      eos_token_id=UpperCAmelCase__    ,      decoder_start_token_id=UpperCAmelCase__    ,      **UpperCAmelCase__    ,      )





