





from typing import Mapping

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


__A							:			List[str]         =			logging.get_logger(__name__)

__A							:			Optional[Any]         =			{
    "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      lowerCamelCase(						__snake_case	):
     '''simple docstring'''


     __magic_name__   =			't5'
     __magic_name__   =			['past_key_values']
     __magic_name__   =			{'hidden_size': 'd_model', 'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}




     def __init__(    self				,     snake_case_=3_2128				,     snake_case_=512				,     snake_case_=64				,     snake_case_=2048				,     snake_case_=6				,     snake_case_=None				,     snake_case_=8				,     snake_case_=32				,     snake_case_=128				,     snake_case_=0.1				,     snake_case_=1E-6				,     snake_case_=1.0				,     snake_case_="relu"				,     snake_case_=True				,     snake_case_=True				,     snake_case_=0				,     snake_case_=1				,     **snake_case_				,     ):
         _A     =							vocab_size
         _A     =							d_model
         _A     =							d_kv
         _A     =							d_ff
         _A     =							num_layers
         _A     =							(
             num_decoder_layers if num_decoder_layers is not None else self.num_layers
         )  # default = symmetry
         _A     =							num_heads
         _A     =							relative_attention_num_buckets
         _A     =							relative_attention_max_distance
         _A     =							dropout_rate
         _A     =							layer_norm_epsilon
         _A     =							initializer_factor
         _A     =							feed_forward_proj
         _A     =							use_cache

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

         if len(snake_case_							) > 1 and act_info[0] != "gated" or len(snake_case_							) > 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":
             _A     =							'gelu_new'

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







class      lowerCamelCase(						__snake_case	):
     '''simple docstring'''


     @property
     def        lowerCAmelCase__		(    self							):
         _A     =							{
             'input_ids': {0: 'batch', 1: 'encoder_sequence'},
             'attention_mask': {0: 'batch', 1: 'encoder_sequence'},
         }
         if self.use_past:
             _A     =							'past_encoder_sequence + sequence'
             _A     =							{0: 'batch'}
             _A     =							{0: 'batch', 1: 'past_decoder_sequence + sequence'}
         else:
             _A     =							{0: 'batch', 1: 'decoder_sequence'}
             _A     =							{0: 'batch', 1: 'decoder_sequence'}

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

         return common_inputs




     @property
     def        lowerCAmelCase__		(    self							):
         return 13












def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> int:




    """simple docstring"""




    print('\nThe shortest path matrix using Floyd Warshall algorithm\n'				)
    for i in range(_SCREAMING_SNAKE_CASE				):
        for j in range(_SCREAMING_SNAKE_CASE				):
            if dist[i][j] != float('inf'				):
                print(int(dist[i][j]				)							,     end='\t'				)
            else:
                print('INF'							,     end='\t'				)
        print()





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> str:




    """simple docstring"""




    _A     =							[[float('inf'				) for _ in range(_SCREAMING_SNAKE_CASE				)] for _ in range(_SCREAMING_SNAKE_CASE				)]

    for i in range(_SCREAMING_SNAKE_CASE				):
        for j in range(_SCREAMING_SNAKE_CASE				):
            _A     =							graph[i][j]

            # check vertex k against all other vertices (i, j)
    for k in range(_SCREAMING_SNAKE_CASE				):
        # looping through rows of graph array
        for i in range(_SCREAMING_SNAKE_CASE				):
            # looping through columns of graph array
            for j in range(_SCREAMING_SNAKE_CASE				):
                if (
                    dist[i][k] != float('inf'				)
                    and dist[k][j] != float('inf'				)
                    and dist[i][k] + dist[k][j] < dist[i][j]
                ):
                    _A     =							dist[i][k] + dist[k][j]

    _print_dist(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)
    return dist, v


if __name__ == "__main__":
 __A							:			Dict         =			int(input("Enter number of vertices: "))
 __A							:			Union[str, Any]         =			int(input("Enter number of edges: "))

 __A							:			List[str]         =			[[float("inf") for i in range(v)] for j in range(v)]

 for i in range(v):
  __A							:			List[Any]         =			0.0

  # src and dst are indices that must be within the array size graph[e][v]
  # failure to follow this will result in an error
 for i in range(e):
  print("\nEdge ", i + 1)
  __A							:			Union[str, Any]         =			int(input("Enter source:"))
  __A							:			List[str]         =			int(input("Enter destination:"))
  __A							:			Union[str, Any]         =			float(input("Enter weight:"))
  __A							:			Any         =			weight

 floyd_warshall(graph, v)

 # Example Input
 # Enter number of vertices: 3
 # Enter number of edges: 2

 # # generated graph from vertex and edge inputs
 # [[inf, inf, inf], [inf, inf, inf], [inf, inf, inf]]
 # [[0.0, inf, inf], [inf, 0.0, inf], [inf, inf, 0.0]]

 # specify source, destination and weight for edge #1
 # Edge  1
 # Enter source:1
 # Enter destination:2
 # Enter weight:2

 # specify source, destination and weight for edge #2
 # Edge  2
 # Enter source:2
 # Enter destination:1
 # Enter weight:1

 # # Expected Output from the vertice, edge and src, dst, weight inputs!!
 # 0		INF	INF
 # INF	0	2
 # INF	1	0





