




'''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      _UpperCamelCase	(_lowerCamelCase							:       Union[str, Any]				,		_lowerCamelCase							:       Optional[int]		)->				List[str]:




     '''simple docstring'''





     __snake_case         =					copy.deepcopy(_lowerCamelCase		)
     __snake_case         =					sorted(_lowerCamelCase		)
     __snake_case         =					[bisect.bisect_right(_lowerCamelCase				,		_lowerCamelCase		) for y in x]
     return quantized







def      _UpperCamelCase	(_lowerCamelCase							:       int				,		_lowerCamelCase							:       Any=0		)->				Union[str, Any]:




     '''simple docstring'''





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


       def __init__(				self      ,					__SCREAMING_SNAKE_CASE      ,					__SCREAMING_SNAKE_CASE      ,					__SCREAMING_SNAKE_CASE					) ->					List[Any]:



            '''simple docstring'''




            if not isinstance(__SCREAMING_SNAKE_CASE      ,					__SCREAMING_SNAKE_CASE					):
                 raise ValueError(
                     '''sampler should be an instance of torch.utils.data.Sampler, but got sampler={}'''.format(__SCREAMING_SNAKE_CASE					)					)
            __snake_case         =					sampler
            __snake_case         =					group_ids
            __snake_case         =					batch_size


       def __iter__(				self					) ->					Optional[int]:



            '''simple docstring'''




            __snake_case         =					defaultdict(__SCREAMING_SNAKE_CASE					)
            __snake_case         =					defaultdict(__SCREAMING_SNAKE_CASE					)

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



from __future__ import annotations

from collections.abc import Iterator
from typing import Any





class       lowerCAmelCase				:


       def __init__(				self      ,					__SCREAMING_SNAKE_CASE					) ->					None:



            '''simple docstring'''




            __snake_case         =					data
            __snake_case         =					None




       def __str__(				self					) ->					str:



            '''simple docstring'''




            return F'''{self.data}'''





class       lowerCAmelCase				:


       def __init__(				self					) ->					None:



            '''simple docstring'''




            __snake_case         =					None
            __snake_case         =					None


       def __iter__(				self					) ->					Iterator[Any]:



            '''simple docstring'''




            __snake_case         =					self.front
            while node:
                 yield node.data
                 __snake_case         =					node.next


       def __len__(				self					) ->					int:



            '''simple docstring'''




            return len(tuple(iter(self					)					)					)


       def __str__(				self					) ->					str:



            '''simple docstring'''




            return " <- ".join(str(__SCREAMING_SNAKE_CASE					) for item in self					)


       def  lowerCAmelCase (				self					) ->					bool:



            '''simple docstring'''




            return len(self					) == 0


       def  lowerCAmelCase (				self      ,					__SCREAMING_SNAKE_CASE					) ->					None:



            '''simple docstring'''




            __snake_case         =					Node(__SCREAMING_SNAKE_CASE					)
            if self.is_empty():
                 __snake_case         =					__snake_case         =					node
            else:
                 assert isinstance(self.rear      ,					__SCREAMING_SNAKE_CASE					)
                 __snake_case         =					node
                 __snake_case         =					node


       def  lowerCAmelCase (				self					) ->					Any:



            '''simple docstring'''




            if self.is_empty():
                 raise IndexError('''dequeue from empty queue'''					)
            assert isinstance(self.front      ,					__SCREAMING_SNAKE_CASE					)
            __snake_case         =					self.front
            __snake_case         =					self.front.next
            if self.front is None:
                 __snake_case         =					None
            return node.data




       def  lowerCAmelCase (				self					) ->					None:



            '''simple docstring'''




            __snake_case         =					__snake_case         =					None


if __name__ == "__main__":
     from doctest import testmod

     testmod()






