




from __future__ import annotations

from collections import deque
from enum import Enum
from math import atana, degrees
from sys import maxsize


class 				__SCREAMING_SNAKE_CASE							(		lowerCamelCase  ):
					_lowerCamelCase		  = 1
					_lowerCamelCase		  = 2
					_lowerCamelCase		  = 3

					def __repr__(				self					):







						'''simple docstring'''




						return f"{self.__class__.__name__}.{self.name}"






def 					snake_case					(							A						,   A						,   A			)							->							float:




	'''simple docstring'''


	lowerCamelCase_   ,			lowerCamelCase_							:		Any							   =							point
	return degrees(atana(y - miny						,   x - minx			)			)






def 					snake_case					(							A						,   A						,   A			)							->							Direction:




	'''simple docstring'''


	lowerCamelCase_   ,			lowerCamelCase_							:		Any							   =							starting
	lowerCamelCase_   ,			lowerCamelCase_							:		List[str]							   =							via
	lowerCamelCase_   ,			lowerCamelCase_							:		Tuple							   =							target
	lowerCamelCase_							:		List[Any]							   =							degrees(atana(ya - ya						,   xa - xa			)			)
	via_angle %= 360
	lowerCamelCase_							:		int							   =							degrees(atana(ya - ya						,   xa - xa			)			)
	target_angle %= 360
	# t-
	#  \ \
	#   \ v
	#    \|
	#     s
	# via_angle is always lower than target_angle, if direction is left.
	# If they are same, it means they are on a same line of convex hull.
	if target_angle > via_angle:
		return Direction.left
	elif target_angle == via_angle:
		return Direction.straight
	else:
		return Direction.right






def 					snake_case					(							A			)							->							list[tuple[int, int]]:




	'''simple docstring'''


	if len(A			) <= 2:
		# There is no convex hull
		raise ValueError('graham_scan: argument must contain more than 3 points.'			)
	if len(A			) == 3:
		return points
	# find the lowest and the most left point
	lowerCamelCase_							:		Tuple							   =							0
	lowerCamelCase_   ,			lowerCamelCase_							:		Any							   =							maxsize, maxsize
	for i, point in enumerate(A			):
		lowerCamelCase_							:		Any							   =							point[0]
		lowerCamelCase_							:		Optional[Any]							   =							point[1]
		if y < miny:
			lowerCamelCase_							:		Any							   =							y
			lowerCamelCase_							:		List[str]							   =							x
			lowerCamelCase_							:		int							   =							i
		if y == miny and x < minx:
			lowerCamelCase_							:		Optional[Any]							   =							x
			lowerCamelCase_							:		List[str]							   =							i

    # remove the lowest and the most left point from points for preparing for sort
	points.pop(A			)

	lowerCamelCase_							:		List[Any]							   =							sorted(A						,   key=lambda A			: angle_comparer(A						,   A						,   A			)			)
	# This insert actually costs complexity,
	# and you should instead add (minx, miny) into stack later.
	# I'm using insert just for easy understanding.
	sorted_points.insert(0						,   (minx, miny)			)

	lowerCamelCase_							:		deque[tuple[int, int]]							   =							deque()
	stack.append(sorted_points[0]			)
	stack.append(sorted_points[1]			)
	stack.append(sorted_points[2]			)
	# In any ways, the first 3 points line are towards left.
	# Because we sort them the angle from minx, miny.
	lowerCamelCase_							:		Optional[Any]							   =							Direction.left

	for i in range(3						,   len(A			)			):
		while True:
			lowerCamelCase_							:		Any							   =							stack[-2]
			lowerCamelCase_							:		List[str]							   =							stack[-1]
			lowerCamelCase_							:		int							   =							sorted_points[i]
			lowerCamelCase_							:		Any							   =							check_direction(A						,   A						,   A			)

			if next_direction == Direction.left:
				lowerCamelCase_							:		List[str]							   =							Direction.left
				break
			if next_direction == Direction.straight:
				if current_direction == Direction.left:
					# We keep current_direction as left.
					# Because if the straight line keeps as straight,
					# we want to know if this straight line is towards left.
					break
				elif current_direction == Direction.right:
					# If the straight line is towards right,
					# every previous points on those straigh line is not convex hull.
					stack.pop()
			if next_direction == Direction.right:
				stack.pop()
		stack.append(sorted_points[i]			)
	return list(A			)

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





def      _UpperCAmelCase    (							_UpperCamelCase    :	str,   _UpperCamelCase    :	Tuple=0   )	->      str:
    A_     =   np.arange(start=3,   stop=_UpperCamelCase,   step=4   ).tolist() if k > 0 else [10]
    A_     =   _quantize(_UpperCamelCase,   _UpperCamelCase   )
    # count number of elements per group
    A_     =   np.unique(_UpperCamelCase,   return_counts=_UpperCamelCase   )[1]
    A_     =   [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 	__UpperCAmelCase				(				_UpperCamelCase     ):





       '''simple docstring'''



       def __init__(      self    ,     _SCREAMING_SNAKE_CASE    ,     _SCREAMING_SNAKE_CASE    ,     _SCREAMING_SNAKE_CASE )		->     Dict:
           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 ) )
           A_     =   sampler
           A_     =   group_ids
           A_     =   batch_size

       def __iter__(      self )		->     Tuple:
           A_     =   defaultdict(_SCREAMING_SNAKE_CASE )
           A_     =   defaultdict(_SCREAMING_SNAKE_CASE )

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






