
'''simple docstring'''

from __future__ import annotations

from collections import Counter
from random import random


class  _UpperCAmelCase :

     """simple docstring"""

     def __init__(      self ):

       '''simple docstring'''

       a_      :	Optional[int]      =							{}


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_ ):

       '''simple docstring'''

       a_      :	Dict      =							{}


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_							,		lowerCAmelCase_							,		lowerCAmelCase_ ):

       '''simple docstring'''

       if nodea not in self.connections:
         self.add_node(lowerCAmelCase_ )
       if nodea not in self.connections:
         self.add_node(lowerCAmelCase_ )
       a_      :	Dict      =							probability


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       return list(self.connections )






     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_ ):

       '''simple docstring'''

       a_      :	Tuple      =							0
       a_      :	Dict      =							random()

       for dest in self.connections[node]:
         current_probability += self.connections[node][dest]
         if current_probability > random_value:
           return dest
       return ""







def 	_snake_case						(      A_       :    str     ,		A_       :    list[tuple[str, str, float]]     ,		A_       :    int   ):
  """simple docstring"""







  a_      :	Optional[Any]      =							MarkovChainGraphUndirectedUnweighted()

  for nodea, nodea, probability in transitions:
    graph.add_transition_probability(A_     ,		A_     ,		A_   )

  a_      :	Any      =							Counter(graph.get_nodes()   )
  a_      :	Optional[Any]      =							start

  for _ in range(A_   ):
    a_      :	List[Any]      =							graph.transition(A_   )
    visited[node] += 1

  return visited


if __name__ == "__main__":
    import doctest

    doctest.testmod()




'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


__snake_case:  Dict								=			{"configuration_encoder_decoder": ["EncoderDecoderConfig"]}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case:  List[str]								=			["EncoderDecoderModel"]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case:  Any								=			["TFEncoderDecoderModel"]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case:  List[str]								=			["FlaxEncoderDecoderModel"]

if TYPE_CHECKING:
    from .configuration_encoder_decoder import EncoderDecoderConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_encoder_decoder import EncoderDecoderModel

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_encoder_decoder import TFEncoderDecoderModel

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_encoder_decoder import FlaxEncoderDecoderModel

else:
    import sys

    __snake_case:  Tuple								=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


