



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						(    _UpperCAmelCase       ,			_UpperCAmelCase				):
					"""simple docstring"""






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





def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase=0				):
					"""simple docstring"""






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




class 	a__       (       _snake_case       ):


					"""simple docstring"""



					def __init__(		self     :List[Any]      ,  lowercase__     :List[str]      ,  lowercase__     :str      ,  lowercase__     :List[Any]    ):
										if not isinstance(lowercase__      ,  lowercase__    ):
															raise ValueError(
															    'sampler should be an instance of torch.utils.data.Sampler, but got sampler={}'.format(lowercase__    )    )
										lowercase						   =       sampler
										lowercase						   =       group_ids
										lowercase						   =       batch_size

					def __iter__(		self     :Optional[int]    ):
										lowercase						   =       defaultdict(lowercase__    )
										lowercase						   =       defaultdict(lowercase__    )

										lowercase						   =       0
										for idx in self.sampler:
															lowercase						   =       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
										lowercase						   =       len(self    )
										lowercase						   =       expected_num_batches - num_batches
										if num_remaining > 0:
															# for the remaining batches, group the batches by similar lengths
															lowercase						   =       []
															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]
																									lowercase						   =       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     :List[Any]    ):
										return (len(self.sampler    ) + self.batch_size - 1) // self.batch_size











from collections.abc import Callable

__magic_name__       =     Callable[[float], float]  # type alias for a real -> real function





def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase       ,			):
					"""simple docstring"""






					lowercase						   =       float(_UpperCAmelCase				)
					while True:
										try:
															lowercase						   =       prev_guess - function(_UpperCAmelCase				) / derivative(_UpperCAmelCase				)
										except ZeroDivisionError:
															raise ZeroDivisionError('Could not find root'				) from None
										if abs(prev_guess - next_guess				) < 10**-5:
															return next_guess
										lowercase						   =       next_guess





def 		__snake_case						(    _UpperCAmelCase				):
					"""simple docstring"""






					return (x**3) - (2 * x) - 5





def 		__snake_case						(    _UpperCAmelCase				):
					"""simple docstring"""






					return 3 * (x**2) - 2


if __name__ == "__main__":
		print(newton(f, fa, 3))






