


'''simple docstring'''




from typing import Mapping

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


__snake_case    						=logging.get_logger(__name__)

__snake_case    						={
    """t5-small""": """https://huggingface.co/t5-small/resolve/main/config.json""",
    """t5-base""": """https://huggingface.co/t5-base/resolve/main/config.json""",
    """t5-large""": """https://huggingface.co/t5-large/resolve/main/config.json""",
    """t5-3b""": """https://huggingface.co/t5-3b/resolve/main/config.json""",
    """t5-11b""": """https://huggingface.co/t5-11b/resolve/main/config.json""",
}

class 		UpperCAmelCase_      (  __lowercase		):
     lowerCamelCase				:	Optional[Any]		=     '''t5'''
     lowerCamelCase				:	Optional[Any]		=     ['''past_key_values''']
     lowerCamelCase				:	List[str]		=     {'''hidden_size''': '''d_model''', '''num_attention_heads''': '''num_heads''', '''num_hidden_layers''': '''num_layers'''}





     def __init__( self       :      str    ,      UpperCAmelCase__       :      int=3_2_1_2_8    ,      UpperCAmelCase__       :      Optional[int]=5_1_2    ,      UpperCAmelCase__       :      Tuple=6_4    ,      UpperCAmelCase__       :      Union[str, Any]=2_0_4_8    ,      UpperCAmelCase__       :      str=6    ,      UpperCAmelCase__       :      Union[str, Any]=None    ,      UpperCAmelCase__       :      int=8    ,      UpperCAmelCase__       :      Tuple=3_2    ,      UpperCAmelCase__       :      Dict=1_2_8    ,      UpperCAmelCase__       :      List[Any]=0.1    ,      UpperCAmelCase__       :      Optional[Any]=1E-6    ,      UpperCAmelCase__       :      str=1.0    ,      UpperCAmelCase__       :      str="relu"    ,      UpperCAmelCase__       :      int=True    ,      UpperCAmelCase__       :      Optional[Any]=True    ,      UpperCAmelCase__       :      Dict=0    ,      UpperCAmelCase__       :      Tuple=1    ,      **UpperCAmelCase__       :      str    ,      )				->  Optional[int]:
        lowerCAmelCase     =			vocab_size
        lowerCAmelCase     =			d_model
        lowerCAmelCase     =			d_kv
        lowerCAmelCase     =			d_ff
        lowerCAmelCase     =			num_layers
        lowerCAmelCase     =			(
            num_decoder_layers if num_decoder_layers is not None else self.num_layers
        )  # default = symmetry
        lowerCAmelCase     =			num_heads
        lowerCAmelCase     =			relative_attention_num_buckets
        lowerCAmelCase     =			relative_attention_max_distance
        lowerCAmelCase     =			dropout_rate
        lowerCAmelCase     =			layer_norm_epsilon
        lowerCAmelCase     =			initializer_factor
        lowerCAmelCase     =			feed_forward_proj
        lowerCAmelCase     =			use_cache

        lowerCAmelCase     =			self.feed_forward_proj.split('-'    )
        lowerCAmelCase     =			act_info[-1]
        lowerCAmelCase     =			act_info[0] == 'gated'

        if len(UpperCAmelCase__    ) > 1 and act_info[0] != "gated" or len(UpperCAmelCase__    ) > 2:
           raise ValueError(
               F'''`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer.'''
               'Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '
               '\'gated-gelu\' or \'relu\''    )

        # for backwards compatibility
        if feed_forward_proj == "gated-gelu":
           lowerCAmelCase     =			'gelu_new'

        super().__init__(
            pad_token_id=UpperCAmelCase__    ,      eos_token_id=UpperCAmelCase__    ,      is_encoder_decoder=UpperCAmelCase__    ,      **UpperCAmelCase__    ,      )




class 		UpperCAmelCase_      (  __lowercase		):





     @property
     def 							__UpperCAmelCase      ( self       :      Tuple    )				->  Mapping[str, Mapping[int, str]]:
        lowerCAmelCase     =			{
            'input_ids': {0: 'batch', 1: 'encoder_sequence'},
            'attention_mask': {0: 'batch', 1: 'encoder_sequence'},
        }
        if self.use_past:
           lowerCAmelCase     =			'past_encoder_sequence + sequence'
           lowerCAmelCase     =			{0: 'batch'}
           lowerCAmelCase     =			{0: 'batch', 1: 'past_decoder_sequence + sequence'}
        else:
           lowerCAmelCase     =			{0: 'batch', 1: 'decoder_sequence'}
           lowerCAmelCase     =			{0: 'batch', 1: 'decoder_sequence'}

        if self.use_past:
           self.fill_with_past_key_values_(UpperCAmelCase__    ,      direction='inputs'    )

        return common_inputs





     @property
     def 							__UpperCAmelCase      ( self       :      Optional[Any]    )				->  int:
        return 1_3






from __future__ import annotations

_SCREAMING_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 				a							:







 """simple docstring"""






 def __init__(					self		,				lowerCAmelCase_		,				lowerCAmelCase_							)  ->					None:
        _A        =  graph
        # mapping node to its parent in resulting breadth first tree
        _A        =  {}
        _A        =  source_vertex



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

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



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_							)  ->					str:
        if target_vertex == self.source_vertex:
               return self.source_vertex

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

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


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




