
'''simple docstring'''






from itertools import combinations_with_replacement







def 		SCREAMING_SNAKE_CASE__					(							_SCREAMING_SNAKE_CASE = 100  ):
		lowerCAmelCase_   :       list[int]    							=[*list(range(1  ,					21  )  ), 25]
		lowerCAmelCase_   :       list[int]    							=[2 * x for x in range(1  ,					21  )] + [50]
		lowerCAmelCase_   :       list[int]    							=[3 * x for x in range(1  ,					21  )]
		lowerCAmelCase_   :       list[int]    							=singles + doubles + triples + [0]

		lowerCAmelCase_   :       int    							=0
		lowerCAmelCase_   :       int
		lowerCAmelCase_   :       int
		lowerCAmelCase_   :       int
		lowerCAmelCase_   :       int

		for double in doubles:
				for throwa, throwa in combinations_with_replacement(_SCREAMING_SNAKE_CASE  ,					2  ):
						lowerCAmelCase_   :       List[Any]    							=double + throwa + throwa
						if checkout_total < limit:
								num_checkouts += 1

		return num_checkouts


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








'''simple docstring'''






from typing import TYPE_CHECKING

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


__lowercase	=    {
    '''configuration_xlm_prophetnet''': ['''XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMProphetNetConfig'''],
}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowercase	=    ['''XLMProphetNetTokenizer''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowercase	=    [
							    '''XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''XLMProphetNetDecoder''',
							    '''XLMProphetNetEncoder''',
							    '''XLMProphetNetForCausalLM''',
							    '''XLMProphetNetForConditionalGeneration''',
							    '''XLMProphetNetModel''',
							    '''XLMProphetNetPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_xlm_prophetnet import (
														    XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
														    XLMProphetNetDecoder,
														    XLMProphetNetEncoder,
														    XLMProphetNetForCausalLM,
														    XLMProphetNetForConditionalGeneration,
														    XLMProphetNetModel,
														    XLMProphetNetPreTrainedModel,
														)

else:
							import sys

							__lowercase	=    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






