


from functools import lru_cache






def 	__lowerCamelCase						(							lowerCamelCase__		:						int      ):





			'''simple docstring'''




			lowerCamelCase    		=  2
			lowerCamelCase    		=  set()
			while i * i <= n:
						if n % i:
									i += 1
						else:
									n //= i
									factors.add(lowerCamelCase__      )
			if n > 1:
						factors.add(lowerCamelCase__      )
			return factors






@lru_cache
def 	__lowerCamelCase						(							lowerCamelCase__		:						int      ):





			'''simple docstring'''




			return len(unique_prime_factors(lowerCamelCase__      )      )






def 	__lowerCamelCase						(							lowerCamelCase__		:						list      ):





			'''simple docstring'''




			return len(set(lowerCamelCase__      )      ) in (0, 1)






def 	__lowerCamelCase						(							lowerCamelCase__		:						int      ):





			'''simple docstring'''




			lowerCamelCase    		=  2

			while True:
						# Increment each value of a generated range
						lowerCamelCase    		=  [base + i for i in range(lowerCamelCase__      )]

						# Run elements through out unique_prime_factors function
						# Append our target number to the end.
						lowerCamelCase    		=  [upf_len(lowerCamelCase__      ) for x in group]
						checker.append(lowerCamelCase__      )

						# If all numbers in the list are equal, return the group variable.
						if equality(lowerCamelCase__      ):
									return group

						# Increment our base variable by 1
						base += 1






def 	__lowerCamelCase						(							lowerCamelCase__		:						int = 4      ):





			'''simple docstring'''




			lowerCamelCase    		=  run(lowerCamelCase__      )
			return results[0] if len(lowerCamelCase__      ) else None


if __name__ == "__main__":
		print(solution())





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCAmelCase   :    Any     =		{
    "configuration_roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig"],
    "tokenization_roc_bert": ["RoCBertTokenizer"],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		pass

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCAmelCase   :    Union[str, Any]     =		[
		    "ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "RoCBertForCausalLM",
		    "RoCBertForMaskedLM",
		    "RoCBertForMultipleChoice",
		    "RoCBertForPreTraining",
		    "RoCBertForQuestionAnswering",
		    "RoCBertForSequenceClassification",
		    "RoCBertForTokenClassification",
		    "RoCBertLayer",
		    "RoCBertModel",
		    "RoCBertPreTrainedModel",
		    "load_tf_weights_in_roc_bert",
		]

if TYPE_CHECKING:
		from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
		from .tokenization_roc_bert import RoCBertTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				raise OptionalDependencyNotAvailable()

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_roc_bert import (
				    ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    RoCBertForCausalLM,
				    RoCBertForMaskedLM,
				    RoCBertForMultipleChoice,
				    RoCBertForPreTraining,
				    RoCBertForQuestionAnswering,
				    RoCBertForSequenceClassification,
				    RoCBertForTokenClassification,
				    RoCBertLayer,
				    RoCBertModel,
				    RoCBertPreTrainedModel,
				    load_tf_weights_in_roc_bert,
				)


else:
		import sys

		UpperCAmelCase   :    Tuple     =		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

