





'''simple docstring'''







import functools






def  _lowerCamelCase				( lowercase						:      list[int]    ,							lowercase						:      list[int]						)	->	int:

				# Validation
				if not isinstance(lowercase    ,							lowercase						) or not all(isinstance(lowercase    ,							lowercase						) for day in days						):
								raise ValueError("The parameter days should be a list of integers"						)

				if len(lowercase						) != 3 or not all(isinstance(lowercase    ,							lowercase						) for cost in costs						):
								raise ValueError("The parameter costs should be a list of three integers"						)

				if len(lowercase						) == 0:
								return 0

				if min(lowercase						) <= 0:
								raise ValueError("All days elements should be greater than 0"						)

				if max(lowercase						) >= 366:
								raise ValueError("All days elements should be less than 366"						)

				_a								= set(lowercase						)

				@functools.cache
				def dynamic_programming(lowercase						:      int						) -> int:
								if index > 365:
												return 0

								if index not in days_set:
												return dynamic_programming(index + 1						)

								return min(
								    costs[0] + dynamic_programming(index + 1						)    ,							costs[1] + dynamic_programming(index + 7						)    ,							costs[2] + dynamic_programming(index + 30						)    ,							)

				return dynamic_programming(1						)


if __name__ == "__main__":
					import doctest

					doctest.testmod()







'''simple docstring'''







from typing import TYPE_CHECKING

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


lowerCAmelCase_					:    int      	=			{'configuration_gpt_neox': ['GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoXConfig']}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_					:    Optional[int]      	=			['GPTNeoXTokenizerFast']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_					:    List[str]      	=			[
					    'GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'GPTNeoXForCausalLM',
					    'GPTNeoXForQuestionAnswering',
					    'GPTNeoXForSequenceClassification',
					    'GPTNeoXForTokenClassification',
					    'GPTNeoXLayer',
					    'GPTNeoXModel',
					    'GPTNeoXPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_gpt_neox import (
										    GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GPTNeoXForCausalLM,
										    GPTNeoXForQuestionAnswering,
										    GPTNeoXForSequenceClassification,
										    GPTNeoXForTokenClassification,
										    GPTNeoXLayer,
										    GPTNeoXModel,
										    GPTNeoXPreTrainedModel,
										)


else:
					import sys

					lowerCAmelCase_					:    List[str]      	=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
