





'''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  _a     (				lowerCAmelCase_      ,   lowerCAmelCase_						):





      """simple docstring"""



      _snake_case		:						Dict         =  copy.deepcopy(lowerCAmelCase_						)
      _snake_case		:						Any         =  sorted(lowerCAmelCase_						)
      _snake_case		:						Optional[int]         =  [bisect.bisect_right(lowerCAmelCase_      ,   lowerCAmelCase_						) for y in x]
      return quantized




def  _a     (				lowerCAmelCase_      ,   lowerCAmelCase_=0						):





      """simple docstring"""



      _snake_case		:						Any         =  np.arange(start=3      ,   stop=lowerCAmelCase_      ,   step=4						).tolist() if k > 0 else [10]
      _snake_case		:						List[Any]         =  _quantize(lowerCAmelCase_      ,   lowerCAmelCase_						)
      # count number of elements per group
      _snake_case		:						str         =  np.unique(lowerCAmelCase_      ,   return_counts=lowerCAmelCase_						)[1]
      _snake_case		:						List[str]         =  [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    (a__       ):







  def __init__(		self  ,  lowercase__  ,  lowercase__  ,  lowercase__		)		->    Union[str, Any]:






        """simple docstring"""





        if not isinstance(lowercase__  ,  lowercase__		):
              raise ValueError(
                  '''sampler should be an instance of torch.utils.data.Sampler, but got sampler={}'''.format(lowercase__		)		)
        _snake_case		:						Tuple         =  sampler
        _snake_case		:						int         =  group_ids
        _snake_case		:						Union[str, Any]         =  batch_size







  def __iter__(		self		)		->    int:






        """simple docstring"""





        _snake_case		:						List[Any]         =  defaultdict(lowercase__		)
        _snake_case		:						str         =  defaultdict(lowercase__		)

        _snake_case		:						Any         =  0
        for idx in self.sampler:
              _snake_case		:						List[Any]         =  self.group_ids[idx]
              buffer_per_group[group_id].append(lowercase__		)
              samples_per_group[group_id].append(lowercase__		)
              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
        _snake_case		:						Any         =  len(self		)
        _snake_case		:						Optional[int]         =  expected_num_batches - num_batches
        if num_remaining > 0:
              # for the remaining batches, group the batches by similar lengths
              _snake_case		:						Dict         =  []
              for group_id, idxs in sorted(buffer_per_group.items()  ,  key=lambda lowercase__		: x[0]		):
                    batch_idx.extend(lowercase__		)
                    if len(lowercase__		) >= self.batch_size:
                          yield batch_idx[: self.batch_size]
                          _snake_case		:						List[Any]         =  batch_idx[self.batch_size :]
                          num_remaining -= 1
              if len(lowercase__		) > 0:
                    yield batch_idx
                    num_remaining -= 1
        assert num_remaining == 0







  def __len__(		self		)		->    Dict:






        """simple docstring"""





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









'''simple docstring'''

import math




def  _a     (				lowerCAmelCase_						):





      """simple docstring"""



      if 1 < number < 4:
            # 2 and 3 are primes
            return True
      elif number < 2 or number % 2 == 0 or number % 3 == 0:
            # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
            return False

      # All primes number are in format of 6k +/- 1
      for i in range(5      ,   int(math.sqrt(lowerCAmelCase_						) + 1						)      ,   6						):
            if number % i == 0 or number % (i + 2) == 0:
                  return False
      return True




def  _a     (				lowerCAmelCase_ = 2_000_000						):





      """simple docstring"""



      return sum(num for num in range(3      ,   lowerCAmelCase_      ,   2						) if is_prime(lowerCAmelCase_						)						) + 2 if n > 2 else 0


if __name__ == "__main__":
   print(F"""{solution() = }""")


