



import sys
from collections.abc import Mapping

import numpy as np
import pyarrow as pa

from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter



class 		_lowercase		(							TensorFormatter[Mapping, np.ndarray, Mapping]						):

   def __init__(   self      :							Optional[Any]				, __lowerCAmelCase      :							List[str]=None				, **__lowerCAmelCase      :							List[str]				)							->					Tuple:


    """simple docstring"""






    super().__init__(features=__lowerCAmelCase				)
    a							=		np_array_kwargs

   def 		A				(   self      :							Optional[Any]				, __lowerCAmelCase      :							int				)							->					Optional[Any]:


    """simple docstring"""






    if isinstance(__lowerCAmelCase				, __lowerCAmelCase				):
     if column and all(
         isinstance(__lowerCAmelCase				, np.ndarray				) and x.shape == column[0].shape and x.dtype == column[0].dtype for x in column				):
      return np.stack(__lowerCAmelCase				)
     else:
      # don't use np.array(column, dtype=object)
      # since it fails in certain cases
      # see https://stackoverflow.com/q/51005699
      a							=		np.empty(len(__lowerCAmelCase				)				, dtype=__lowerCAmelCase				)
      a							=		column
      return out
    return column

   def 		A				(   self      :							Optional[int]				, __lowerCAmelCase      :							Dict				)							->					List[Any]:


    """simple docstring"""






    if isinstance(__lowerCAmelCase				, (str, bytes, type(__lowerCAmelCase				))				):
     return value
    elif isinstance(__lowerCAmelCase				, (np.character, np.ndarray)				) and np.issubdtype(value.dtype				, np.character				):
     return value
    elif isinstance(__lowerCAmelCase				, np.number				):
     return value

    a							=		{}

    if isinstance(__lowerCAmelCase				, np.ndarray				) and np.issubdtype(value.dtype				, np.integer				):
     a							=		{"dtype": np.intaa}
    elif isinstance(__lowerCAmelCase				, np.ndarray				) and np.issubdtype(value.dtype				, np.floating				):
     a							=		{"dtype": np.floataa}
    elif config.PIL_AVAILABLE and "PIL" in sys.modules:
     import PIL.Image

     if isinstance(__lowerCAmelCase				, PIL.Image.Image				):
      return np.asarray(__lowerCAmelCase				, **self.np_array_kwargs				)

    return np.asarray(__lowerCAmelCase				, **{**default_dtype, **self.np_array_kwargs}				)

   def 		A				(   self      :							Optional[int]				, __lowerCAmelCase      :							Union[str, Any]				)							->					Any:


    """simple docstring"""






    if config.TORCH_AVAILABLE and "torch" in sys.modules:
     import torch

     if isinstance(__lowerCAmelCase				, torch.Tensor				):
      return self._tensorize(data_struct.detach().cpu().numpy()[()]				)
    if hasattr(__lowerCAmelCase				, "__array__"				) and not isinstance(__lowerCAmelCase				, (np.ndarray, np.character, np.number)				):
     a							=		data_struct.__array__()
    # support for nested types like struct of list of struct
    if isinstance(__lowerCAmelCase				, np.ndarray				):
     if data_struct.dtype == object:
      return self._consolidate([self.recursive_tensorize(__lowerCAmelCase				) for substruct in data_struct]				)
    if isinstance(__lowerCAmelCase				, (list, tuple)				):
     return self._consolidate([self.recursive_tensorize(__lowerCAmelCase				) for substruct in data_struct]				)
    return self._tensorize(__lowerCAmelCase				)

   def 		A				(   self      :							Any				, __lowerCAmelCase      :							dict				)							->					Optional[int]:


    """simple docstring"""






    return map_nested(self._recursive_tensorize				, __lowerCAmelCase				, map_list=__lowerCAmelCase				)

   def 		A				(   self      :							Dict				, __lowerCAmelCase      :							pa.Table				)							->					Mapping:


    """simple docstring"""






    a							=		self.numpy_arrow_extractor().extract_row(__lowerCAmelCase				)
    a							=		self.python_features_decoder.decode_row(__lowerCAmelCase				)
    return self.recursive_tensorize(__lowerCAmelCase				)

   def 		A				(   self      :							Tuple				, __lowerCAmelCase      :							pa.Table				)							->					np.ndarray:


    """simple docstring"""






    a							=		self.numpy_arrow_extractor().extract_column(__lowerCAmelCase				)
    a							=		self.python_features_decoder.decode_column(__lowerCAmelCase				, pa_table.column_names[0]				)
    a							=		self.recursive_tensorize(__lowerCAmelCase				)
    a							=		self._consolidate(__lowerCAmelCase				)
    return column




   def 		A				(   self      :							Tuple				, __lowerCAmelCase      :							pa.Table				)							->					Mapping:


    """simple docstring"""






    a							=		self.numpy_arrow_extractor().extract_batch(__lowerCAmelCase				)
    a							=		self.python_features_decoder.decode_batch(__lowerCAmelCase				)
    a							=		self.recursive_tensorize(__lowerCAmelCase				)
    for column_name in batch:
     a							=		self._consolidate(batch[column_name]				)
    return batch





'''simple docstring'''




from collections import deque





def 				a_							(    lowercase     )      ->Tuple:






				'''simple docstring'''

				return input(lowercase     ).strip().split(" "     )





def 				a_							(    lowercase				,    lowercase     )      ->dict[int, list[int]]:






				'''simple docstring'''

				__lowerCamelCase		:   dict[int, list[int]]           =       {}
				for i in range(lowercase     ):
								__lowerCamelCase		:   int           =       []

				for e in range(lowercase     ):
								__lowerCamelCase    ,       __lowerCamelCase		:   int           =       (int(lowercase     ) for i in _input(F'Edge {e + 1}: <node1> <node2> '     ))
								graph[x].append(lowercase     )
				return graph





def 				a_							(    lowercase				,    lowercase     )      ->dict[int, list[int]]:






				'''simple docstring'''

				__lowerCamelCase		:   dict[int, list[int]]           =       {}
				for i in range(lowercase     ):
								__lowerCamelCase		:   Any           =       []

				for e in range(lowercase     ):
								__lowerCamelCase    ,       __lowerCamelCase		:   Dict           =       (int(lowercase     ) for i in _input(F'Edge {e + 1}: <node1> <node2> '     ))
								graph[x].append(lowercase     )
								graph[y].append(lowercase     )
				return graph





def 				a_							(    lowercase				,    lowercase     )      ->dict[int, list[tuple[int, int]]]:






				'''simple docstring'''

				__lowerCamelCase		:   dict[int, list[tuple[int, int]]]           =       {}
				for i in range(lowercase     ):
								__lowerCamelCase		:   List[Any]           =       []

				for e in range(lowercase     ):
								__lowerCamelCase    ,       __lowerCamelCase    ,       __lowerCamelCase		:   int           =       (int(lowercase     ) for i in _input(F'Edge {e + 1}: <node1> <node2> <weight> '     ))
								graph[x].append((y, w)     )
								graph[y].append((x, w)     )
				return graph


if __name__ == "__main__":
				__lowercase		,		__lowercase	:   List[Any]   		=					(int(i) for i in _input("""Number of nodes and edges: """))

				__lowercase	:   Any   		=					int(
				    _input(
				        """Press 1 or 2 or 3 \n"""
				        """1. Unweighted directed \n"""
				        """2. Unweighted undirected \n"""
				        """3. Weighted undirected \n"""
				    )[0]
				)

				__lowercase	:   Any   		=					{
				    1: initialize_unweighted_directed_graph,
				    2: initialize_unweighted_undirected_graph,
				    3: initialize_weighted_undirected_graph,
				}[graph_choice](n, m)





def 				a_							(    lowercase				,    lowercase     )      ->Tuple:






				'''simple docstring'''

				__lowerCamelCase    ,       __lowerCamelCase		:   Dict           =       {s}, [s]
				print(lowercase     )
				while _s:
								__lowerCamelCase		:   int           =       0
								for i in g[_s[-1]]:
												if i not in vis:
																_s.append(lowercase     )
																vis.add(lowercase     )
																__lowerCamelCase		:   Tuple           =       1
																print(lowercase     )
																break
								if not flag:
												_s.pop()





def 				a_							(    lowercase				,    lowercase     )      ->List[str]:






				'''simple docstring'''

				__lowerCamelCase    ,       __lowerCamelCase		:   Tuple           =       {s}, deque([s]     )
				print(lowercase     )
				while q:
								__lowerCamelCase		:   Optional[Any]           =       q.popleft()
								for v in g[u]:
												if v not in vis:
																vis.add(lowercase     )
																q.append(lowercase     )
																print(lowercase     )





def 				a_							(    lowercase				,    lowercase     )      ->Any:






				'''simple docstring'''

				__lowerCamelCase    ,       __lowerCamelCase    ,       __lowerCamelCase		:   Optional[int]           =       {s: 0}, set(), {s: 0}
				while True:
								if len(lowercase     ) == len(lowercase     ) - 1:
												break
								__lowerCamelCase		:   str           =       10_0000
								for i in dist:
												if i not in known and dist[i] < mini:
																__lowerCamelCase		:   Any           =       dist[i]
																__lowerCamelCase		:   List[str]           =       i
								known.add(lowercase     )
								for v in g[u]:
												if v[0] not in known and dist[u] + v[1] < dist.get(v[0]				,    10_0000     ):
																__lowerCamelCase		:   Optional[int]           =       dist[u] + v[1]
																__lowerCamelCase		:   List[str]           =       u
				for i in dist:
								if i != s:
												print(dist[i]     )





def 				a_							(    lowercase				,    lowercase=None				,    lowercase=None     )      ->Optional[Any]:






				'''simple docstring'''

				if q is None:
								__lowerCamelCase		:   int           =       [1]
				if ind is None:
								__lowerCamelCase		:   Any           =       [0] * (len(lowercase     ) + 1)  # SInce oth Index is ignored
								for u in g:
												for v in g[u]:
																ind[v] += 1
								__lowerCamelCase		:   Tuple           =       deque()
								for i in g:
												if ind[i] == 0:
																q.append(lowercase     )
				if len(lowercase     ) == 0:
								return
				__lowerCamelCase		:   Optional[Any]           =       q.popleft()
				print(lowercase     )
				for w in g[v]:
								ind[w] -= 1
								if ind[w] == 0:
												q.append(lowercase     )
				topo(lowercase				,    lowercase				,    lowercase     )





def 				a_							(    )      ->Union[str, Any]:






				'''simple docstring'''

				__lowerCamelCase		:   Tuple           =       input().strip()
				__lowerCamelCase		:   Any           =       []
				for _ in range(lowercase     ):
								a.append(map(lowercase				,    input().strip().split()     )     )
				return a, n





def 				a_							(    lowercase     )      ->List[str]:






				'''simple docstring'''

				((__lowerCamelCase)    ,       (__lowerCamelCase))		:   Optional[int]           =       a_and_n
				__lowerCamelCase		:   Optional[int]           =       list(lowercase     )
				__lowerCamelCase		:   str           =       [[0] * n for i in range(lowercase     )]
				for k in range(lowercase     ):
								for i in range(lowercase     ):
												for j in range(lowercase     ):
																if dist[i][j] > dist[i][k] + dist[k][j]:
																				__lowerCamelCase		:   str           =       dist[i][k] + dist[k][j]
																				__lowerCamelCase		:   Tuple           =       k
				print(lowercase     )





def 				a_							(    lowercase				,    lowercase     )      ->Dict:






				'''simple docstring'''

				__lowerCamelCase    ,       __lowerCamelCase    ,       __lowerCamelCase		:   int           =       {s: 0}, set(), {s: 0}
				while True:
								if len(lowercase     ) == len(lowercase     ) - 1:
												break
								__lowerCamelCase		:   List[Any]           =       10_0000
								for i in dist:
												if i not in known and dist[i] < mini:
																__lowerCamelCase		:   str           =       dist[i]
																__lowerCamelCase		:   Optional[int]           =       i
								known.add(lowercase     )
								for v in g[u]:
												if v[0] not in known and v[1] < dist.get(v[0]				,    10_0000     ):
																__lowerCamelCase		:   Dict           =       v[1]
																__lowerCamelCase		:   List[str]           =       u
				return dist





def 				a_							(    )      ->Union[str, Any]:






				'''simple docstring'''

				__lowerCamelCase    ,       __lowerCamelCase		:   List[Any]           =       map(lowercase				,    input().split(" "     )     )
				__lowerCamelCase		:   Optional[Any]           =       []
				for _ in range(lowercase     ):
								edges.append(map(lowercase				,    input().split(" "     )     )     )
				return edges, n





def 				a_							(    lowercase     )      ->Optional[int]:






				'''simple docstring'''

				((__lowerCamelCase)    ,       (__lowerCamelCase))		:   Any           =       e_and_n
				e.sort(reverse=lowercase				,    key=lambda lowercase     : x[2]     )
				__lowerCamelCase		:   Optional[Any]           =       [{i} for i in range(1				,    n + 1     )]
				while True:
								if len(lowercase     ) == 1:
												break
								print(lowercase     )
								__lowerCamelCase		:   List[str]           =       e.pop()
								for i in range(len(lowercase     )     ):
												if x[0] in s[i]:
																break
								for j in range(len(lowercase     )     ):
												if x[1] in s[j]:
																if i == j:
																				break
																s[j].update(s[i]     )
																s.pop(lowercase     )
																break





def 				a_							(    lowercase     )      ->int:






				'''simple docstring'''

				__lowerCamelCase		:   Tuple           =       []
				for node in graph:
								if not graph[node]:
												isolated.append(lowercase     )
				return isolated





