

from dataclasses import dataclass
from typing import Callable, Optional

import datasets



@dataclass
class 					A__(datasets.BuilderConfig       ):
						"""simple docstring"""






						_A						:							Optional[Callable]									= None
						_A						:							Optional[dict]									= None
						_A						:							Optional[datasets.Features]									= None





						def  UpperCamelCase__				(						self						)    ->   Tuple:
									assert self.generator is not None, "generator must be specified"

									if self.gen_kwargs is None:
												a_	:	Tuple          =   {}







class 					A__(datasets.GeneratorBasedBuilder       ):
						"""simple docstring"""






						_A						:							Dict									= GeneratorConfig





						def  UpperCamelCase__				(						self						)    ->   List[Any]:
									return datasets.DatasetInfo(features=self.config.features						)





						def  UpperCamelCase__				(						self     ,			_lowercase						)    ->   List[Any]:
									return [datasets.SplitGenerator(name=datasets.Split.TRAIN     ,			gen_kwargs=self.config.gen_kwargs						)]





						def  UpperCamelCase__				(						self     ,			**_lowercase						)    ->   Tuple:
									for idx, ex in enumerate(self.config.generator(**_lowercase						)						):
												yield idx, ex





from collections import defaultdict


def 				_UpperCAmelCase							(	a__):

			'''simple docstring'''



			a_	:	defaultdict[str, int]          =   defaultdict(a__)
			# Creating a dictionary containing count of each word
			for word in sentence.split():
						occurrence[word] += 1
			return occurrence


if __name__ == "__main__":
	for word, count in word_occurrence("""INPUT STRING""").items():
		print(F"""{word}: {count}""")


