

import bisect
import copy
from collections import defaultdict

import numpy as np
from torch.utils.data import BatchSampler, Sampler

from utils import logger



def 					__lowerCAmelCase					(  A				,   A			):
	UpperCAmelCase_				 =	copy.deepcopy(__lowerCamelCase			)
	UpperCAmelCase_				 =	sorted(__lowerCamelCase			)
	UpperCAmelCase_				 =	[bisect.bisect_right(__lowerCamelCase				,   __lowerCamelCase			) for y in x]
	return quantized



def 					__lowerCAmelCase					(  A				,   A=0			):
	UpperCAmelCase_				 =	np.arange(start=3				,   stop=__lowerCamelCase				,   step=4			).tolist() if k > 0 else [10]
	UpperCAmelCase_				 =	_quantize(__lowerCamelCase				,   __lowerCamelCase			)
	# count number of elements per group
	UpperCAmelCase_				 =	np.unique(__lowerCamelCase				,   return_counts=__lowerCamelCase			)[1]
	UpperCAmelCase_				 =	[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   __UpperCamelCase			(    __lowercase  ):




	def __init__(						self		:  Tuple						,		lowerCAmelCase		:  Dict						,		lowerCAmelCase		:  Tuple						,		lowerCAmelCase		:  Union[str, Any]							):


		'''simple docstring'''







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




	def __iter__(						self		:  str							):


		'''simple docstring'''







		UpperCAmelCase_				 =	defaultdict(__lowerCamelCase							)
		UpperCAmelCase_				 =	defaultdict(__lowerCamelCase							)

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




	def __len__(						self		:  int							):


		'''simple docstring'''







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






from typing import Literal

UpperCamelCase__          ='ABCDEFGHIJKLMNOPQRSTUVWXYZ'






def 			lowerCamelCase__	(__lowerCamelCase,				__lowerCamelCase,				__lowerCamelCase		):
     _SCREAMING_SNAKE_CASE				:		Tuple  			=							LETTERS if mode == "decrypt" else key
     _SCREAMING_SNAKE_CASE				:		Tuple  			=							key if mode == "decrypt" else LETTERS
     _SCREAMING_SNAKE_CASE				:		Dict  			=							""
     # loop through each symbol in the message
     for symbol in message:
          if symbol.upper() in chars_a:
               # encrypt/decrypt the symbol
               _SCREAMING_SNAKE_CASE				:		List[str]  			=							chars_a.find(symbol.upper()		)
               if symbol.isupper():
                    translated += chars_b[sym_index].upper()
               else:
                    translated += chars_b[sym_index].lower()
          else:
               # symbol is not in LETTERS, just add it
               translated += symbol
     return translated






def 			lowerCamelCase__	(__lowerCamelCase,				__lowerCamelCase		):
     return translate_message(__lowerCamelCase,				__lowerCamelCase,				"encrypt"		)






def 			lowerCamelCase__	(__lowerCamelCase,				__lowerCamelCase		):
     return translate_message(__lowerCamelCase,				__lowerCamelCase,				"decrypt"		)






def 			lowerCamelCase__	():
     _SCREAMING_SNAKE_CASE				:		str  			=							"Hello World"
     _SCREAMING_SNAKE_CASE				:		List[str]  			=							"QWERTYUIOPASDFGHJKLZXCVBNM"
     _SCREAMING_SNAKE_CASE				:		Any  			=							"decrypt"  # set to 'encrypt' or 'decrypt'

     if mode == "encrypt":
          _SCREAMING_SNAKE_CASE				:		int  			=							encrypt_message(__lowerCamelCase,				__lowerCamelCase		)
     elif mode == "decrypt":
          _SCREAMING_SNAKE_CASE				:		Optional[int]  			=							decrypt_message(__lowerCamelCase,				__lowerCamelCase		)
     print(f"""Using the key {key}, the {mode}ed message is: {translated}"""		)


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       main()