






from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding


class     __SCREAMING_SNAKE_CASE					(   __lowercase):
						_SCREAMING_SNAKE_CASE	:       Tuple   =					'''ClapFeatureExtractor'''
						_SCREAMING_SNAKE_CASE	:       Optional[int]   =					('''RobertaTokenizer''', '''RobertaTokenizerFast''')






						def __init__(	self     ,						_UpperCamelCase     ,						_UpperCamelCase   ):






												"""simple docstring"""
												super().__init__(_UpperCamelCase     ,						_UpperCamelCase   )






						def __call__(	self     ,						_UpperCamelCase=None     ,						_UpperCamelCase=None     ,						_UpperCamelCase=None     ,						**_UpperCamelCase   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						kwargs.pop('sampling_rate'     ,						_UpperCamelCase   )

												if text is None and audios is None:
																		raise ValueError('You have to specify either text or audios. Both cannot be none.'   )

												if text is not None:
																		lowerCAmelCase__    						=						self.tokenizer(_UpperCamelCase     ,						return_tensors=_UpperCamelCase     ,						**_UpperCamelCase   )

												if audios is not None:
																		lowerCAmelCase__    						=						self.feature_extractor(
																		    _UpperCamelCase     ,						sampling_rate=_UpperCamelCase     ,						return_tensors=_UpperCamelCase     ,						**_UpperCamelCase   )

												if text is not None and audios is not None:
																		lowerCAmelCase__    						=						audio_features.input_features
																		return encoding
												elif text is not None:
																		return encoding
												else:
																		return BatchEncoding(data=dict(**_UpperCamelCase   )     ,						tensor_type=_UpperCamelCase   )






						def       UpperCamelCase__      (	self     ,						*_UpperCamelCase     ,						**_UpperCamelCase   ):






												"""simple docstring"""
												return self.tokenizer.batch_decode(*_UpperCamelCase     ,						**_UpperCamelCase   )






						def       UpperCamelCase__      (	self     ,						*_UpperCamelCase     ,						**_UpperCamelCase   ):






												"""simple docstring"""
												return self.tokenizer.decode(*_UpperCamelCase     ,						**_UpperCamelCase   )







						@property
						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						self.tokenizer.model_input_names
												lowerCAmelCase__    						=						self.feature_extractor.model_input_names
												return list(dict.fromkeys(tokenizer_input_names + feature_extractor_input_names   )   )













from __future__ import annotations

from functools import lru_cache
from math import ceil

__snake_case    :    Union[str, Any]         =     1_00

__snake_case    :    Tuple         =     set(range(3, NUM_PRIMES, 2))
primes.add(2)
__snake_case    :    int

for prime in range(3, ceil(NUM_PRIMES**0.5), 2):
					if prime not in primes:
										continue
					primes.difference_update(set(range(prime * prime, NUM_PRIMES, prime)))







@lru_cache(maxsize=100		)
def 	_UpperCamelCase   (    UpperCamelCase_       :					int		)  ->   set[int]:

						"""simple docstring"""



						if number_to_partition < 0:
												return set()
						elif number_to_partition == 0:
												return {1}

						lowerCAmelCase__    						=						set()
						lowerCAmelCase__    						=						42
						lowerCAmelCase__    						=						42

						for prime in primes:
												if prime > number_to_partition:
																		continue
												for sub in partition(number_to_partition - prime		):
																		ret.add(sub * prime		)

						return ret







def 	_UpperCamelCase   (    UpperCamelCase_       :					int = 5000		)  ->   int | None:

						"""simple docstring"""



						for number_to_partition in range(1    ,       UpperCamelCase_		):
												if len(partition(UpperCamelCase_		)		) > number_unique_partitions:
																		return number_to_partition
						return None


if __name__ == "__main__":
					print(f'{solution() = }')





