

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		(snake_case_				:    Optional[int]						,					snake_case_				:    Union[str, Any]     )       ->		List[str]:
  __UpperCAmelCase  :     Any		=    copy.deepcopy(snake_case_     )
  __UpperCAmelCase  :     List[Any]		=    sorted(snake_case_     )
  __UpperCAmelCase  :     int		=    [bisect.bisect_right(snake_case_						,					snake_case_     ) for y in x]
  return quantized





def    _snake_case		(snake_case_				:    Any						,					snake_case_				:    Dict=0     )       ->		Dict:
  __UpperCAmelCase  :     Optional[Any]		=    np.arange(start=3						,					stop=snake_case_						,					step=4     ).tolist() if k > 0 else [10]
  __UpperCAmelCase  :     List[str]		=    _quantize(snake_case_						,					snake_case_     )
  # count number of elements per group
  __UpperCAmelCase  :     str		=    np.unique(snake_case_						,					return_counts=snake_case_     )[1]
  __UpperCAmelCase  :     str		=    [0] + bins + [np.inf]
  logger.info('Using {} as bins for aspect lengths quantization'.format(snake_case_     )     )
  logger.info('Count of instances per bin: {}'.format(snake_case_     )     )
  return groups







class     lowerCamelCase_   ( _lowerCAmelCase):




 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  :     Any		=    sampler
   __UpperCAmelCase  :     Any		=    group_ids
   __UpperCAmelCase  :     str		=    batch_size




 def __iter__( self       ):
   __UpperCAmelCase  :     List[str]		=    defaultdict(_UpperCAmelCase       )
   __UpperCAmelCase  :     List[Any]		=    defaultdict(_UpperCAmelCase       )

   __UpperCAmelCase  :     List[Any]		=    0
   for idx in self.sampler:
     __UpperCAmelCase  :     Union[str, Any]		=    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  :     Optional[Any]		=    len(self       )
   __UpperCAmelCase  :     Optional[Any]		=    expected_num_batches - num_batches
   if num_remaining > 0:
     # for the remaining batches, group the batches by similar lengths
     __UpperCAmelCase  :     Any		=    []
     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  :     Tuple		=    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








def    _snake_case		(snake_case_				:    int						,					snake_case_				:    int						,					snake_case_				:    int						,					snake_case_				:    int     )       ->		int:
  return len_board * len_board_column * row + column





def    _snake_case		(snake_case_				:    list[list[str]]						,					snake_case_				:    str						,					snake_case_				:    int						,					snake_case_				:    int						,					snake_case_				:    int						,					snake_case_				:    set[int]						,					)       ->		bool:

  if board[row][column] != word[word_index]:
    return False

  if word_index == len(snake_case_     ) - 1:
    return True

  __UpperCAmelCase  :     List[Any]		=    [(0, 1), (0, -1), (-1, 0), (1, 0)]
  __UpperCAmelCase  :     Dict		=    len(snake_case_     )
  __UpperCAmelCase  :     str		=    len(board[0]     )
  for direction in traverts_directions:
    __UpperCAmelCase  :     Dict		=    row + direction[0]
    __UpperCAmelCase  :     Optional[int]		=    column + direction[1]
    if not (0 <= next_i < len_board and 0 <= next_j < len_board_column):
      continue

    __UpperCAmelCase  :     str		=    get_point_key(snake_case_						,					snake_case_						,					snake_case_						,					snake_case_     )
    if key in visited_points_set:
      continue

    visited_points_set.add(snake_case_     )
    if exits_word(snake_case_						,					snake_case_						,					snake_case_						,					snake_case_						,					word_index + 1						,					snake_case_     ):
      return True

    visited_points_set.remove(snake_case_     )

  return False





def    _snake_case		(snake_case_				:    list[list[str]]						,					snake_case_				:    str     )       ->		bool:
  __UpperCAmelCase  :     str		=    (
      'The board should be a non empty matrix of single chars strings.'
  )

  __UpperCAmelCase  :     Any		=    len(snake_case_     )
  if not isinstance(snake_case_						,					snake_case_     ) or len(snake_case_     ) == 0:
    raise ValueError(snake_case_     )

  for row in board:
    if not isinstance(snake_case_						,					snake_case_     ) or len(snake_case_     ) == 0:
      raise ValueError(snake_case_     )

    for item in row:
      if not isinstance(snake_case_						,					snake_case_     ) or len(snake_case_     ) != 1:
        raise ValueError(snake_case_     )

    # Validate word
  if not isinstance(snake_case_						,					snake_case_     ) or len(snake_case_     ) == 0:
    raise ValueError(
        'The word parameter should be a string of length greater than 0.'     )

  __UpperCAmelCase  :     str		=    len(board[0]     )
  for i in range(snake_case_     ):
    for j in range(snake_case_     ):
      if exits_word(
          snake_case_						,					snake_case_						,					snake_case_						,					snake_case_						,					0						,					{get_point_key(snake_case_						,					snake_case_						,					snake_case_						,					snake_case_     )}     ):
        return True

  return False


if __name__ == "__main__":
      import doctest

      doctest.testmod()





