



'''simple docstring'''







import bisect
import copy
from collections import defaultdict

import numpy as np
from torch.utils.data import BatchSampler, Sampler

from utils import logger





def 						snake_case__ (lowerCAmelCase_					,  lowerCAmelCase_	):
    UpperCamelCase__      =			copy.deepcopy(lowerCAmelCase_	)
    UpperCamelCase__      =			sorted(lowerCAmelCase_	)
    UpperCamelCase__      =			[bisect.bisect_right(lowerCAmelCase_					,  lowerCAmelCase_	) for y in x]
    return quantized





def 						snake_case__ (lowerCAmelCase_					,  lowerCAmelCase_=0	):
    UpperCamelCase__      =			np.arange(start=3					,  stop=lowerCAmelCase_					,  step=4	).tolist() if k > 0 else [10]
    UpperCamelCase__      =			_quantize(lowerCAmelCase_					,  lowerCAmelCase_	)
    # count number of elements per group
    UpperCamelCase__      =			np.unique(lowerCAmelCase_					,  return_counts=lowerCAmelCase_	)[1]
    UpperCamelCase__      =			[0] + bins + [np.inf]
    logger.info("Using {} as bins for aspect lengths quantization".format(lowerCAmelCase_	)	)
    logger.info("Count of instances per bin: {}".format(lowerCAmelCase_	)	)
    return groups





class       lowerCamelCase_							(	lowerCAmelCase_  ):






   '''simple docstring'''

   def __init__(  self     ,						__UpperCamelCase     ,						__UpperCamelCase     ,						__UpperCamelCase ):
       if not isinstance(__UpperCamelCase     ,						__UpperCamelCase ):
           raise ValueError(
               "sampler should be an instance of torch.utils.data.Sampler, but got sampler={}".format(__UpperCamelCase ) )
       UpperCamelCase__      =			sampler
       UpperCamelCase__      =			group_ids
       UpperCamelCase__      =			batch_size


   def __iter__(  self ):
       UpperCamelCase__      =			defaultdict(__UpperCamelCase )
       UpperCamelCase__      =			defaultdict(__UpperCamelCase )

       UpperCamelCase__      =			0
       for idx in self.sampler:
           UpperCamelCase__      =			self.group_ids[idx]
           buffer_per_group[group_id].append(__UpperCamelCase )
           samples_per_group[group_id].append(__UpperCamelCase )
           if len(buffer_per_group[group_id] ) == self.batch_size:
               yield buffer_per_group[group_id]  # TODO
               num_batches += 1
               del buffer_per_group[group_id]
           assert len(buffer_per_group[group_id] ) < self.batch_size

       # now we have run out of elements that satisfy
       # the group criteria, let's return the remaining
       # elements so that the size of the sampler is
       # deterministic
       UpperCamelCase__      =			len(self )
       UpperCamelCase__      =			expected_num_batches - num_batches
       if num_remaining > 0:
           # for the remaining batches, group the batches by similar lengths
           UpperCamelCase__      =			[]
           for group_id, idxs in sorted(buffer_per_group.items()     ,						key=lambda __UpperCamelCase : x[0] ):
               batch_idx.extend(__UpperCamelCase )
               if len(__UpperCamelCase ) >= self.batch_size:
                   yield batch_idx[: self.batch_size]
                   UpperCamelCase__      =			batch_idx[self.batch_size :]
                   num_remaining -= 1
           if len(__UpperCamelCase ) > 0:
               yield batch_idx
               num_remaining -= 1
       assert num_remaining == 0







   def __len__(  self ):
       return (len(self.sampler ) + self.batch_size - 1) // self.batch_size









'''simple docstring'''







import heapq





def 						snake_case__ (lowerCAmelCase_					,  lowerCAmelCase_					,  lowerCAmelCase_	):
    UpperCamelCase__      =			[(0, start)]  # cost from start node,end node
    UpperCamelCase__      =			set()
    while heap:
        ((UpperCamelCase__)    ,  (UpperCamelCase__))      =			heapq.heappop(lowerCAmelCase_	)
        if u in visited:
            continue
        visited.add(lowerCAmelCase_	)
        if u == end:
            return cost
        for v, c in graph[u]:
            if v in visited:
                continue
            UpperCamelCase__      =			cost + c
            heapq.heappush(lowerCAmelCase_					,  (next_item, v)	)
    return -1


lowercase__     :  Any    					=			{
    'A': [['B', 2], ['C', 5]],
    'B': [['A', 2], ['D', 3], ['E', 1], ['F', 1]],
    'C': [['A', 5], ['F', 3]],
    'D': [['B', 3]],
    'E': [['B', 4], ['F', 3]],
    'F': [['C', 3], ['E', 3]],
}
lowercase__     :  Optional[int]    					=			{
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['F', 3]],
    'F': [],
}
lowercase__     :  Union[str, Any]    					=			{
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['G', 2]],
    'F': [],
    'G': [['F', 1]],
}

lowercase__     :  Union[str, Any]    					=			dijkstra(G, 'E', 'C')
print(short_distance)  # E -- 3 --> F -- 3 --> C == 6

lowercase__     :  Optional[int]    					=			dijkstra(Ga, 'E', 'F')
print(short_distance)  # E -- 3 --> F == 3

lowercase__     :  Any    					=			dijkstra(Ga, 'E', 'F')
print(short_distance)  # E -- 2 --> G -- 1 --> F == 3

if __name__ == "__main__":
      import doctest

      doctest.testmod()




