


'''simple docstring'''



from typing import List, Optional, Union

from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType


class 						_snake_case   (       a__		):
					lowerCAmelCase :Optional[Any]						=   ['''image_processor''', '''tokenizer''']
					lowerCAmelCase :List[str]						=   '''BlipImageProcessor'''
					lowerCAmelCase :List[Any]						=   ('''BertTokenizer''', '''BertTokenizerFast''')




					def __init__( self							,							_lowerCamelCase							,							_lowerCamelCase):
								UpperCAmelCase__					:   Any       				=       False
								super().__init__(_lowerCamelCase							,							_lowerCamelCase)
								UpperCAmelCase__					:   Any       				=       self.image_processor




					def __call__( self							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = True							,							_lowerCamelCase = False							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = 0							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = False							,							_lowerCamelCase = False							,							_lowerCamelCase = False							,							_lowerCamelCase = False							,							_lowerCamelCase = False							,							_lowerCamelCase = True							,							_lowerCamelCase = None							,							**_lowerCamelCase							,							):
								if images is None and text is None:
											raise ValueError("""You have to specify either images or text.""")

								# Get only text
								if images is None:
											UpperCAmelCase__					:   Union[str, Any]       				=       self.tokenizer
											UpperCAmelCase__					:   Dict       				=       self.tokenizer(
											    text=_lowerCamelCase							,							add_special_tokens=_lowerCamelCase							,							padding=_lowerCamelCase							,							truncation=_lowerCamelCase							,							max_length=_lowerCamelCase							,							stride=_lowerCamelCase							,							pad_to_multiple_of=_lowerCamelCase							,							return_attention_mask=_lowerCamelCase							,							return_overflowing_tokens=_lowerCamelCase							,							return_special_tokens_mask=_lowerCamelCase							,							return_offsets_mapping=_lowerCamelCase							,							return_token_type_ids=_lowerCamelCase							,							return_length=_lowerCamelCase							,							verbose=_lowerCamelCase							,							return_tensors=_lowerCamelCase							,							**_lowerCamelCase							,							)
											return text_encoding

								# add pixel_values
								UpperCAmelCase__					:   List[str]       				=       self.image_processor(_lowerCamelCase							,							return_tensors=_lowerCamelCase)

								if text is not None:
											UpperCAmelCase__					:   int       				=       self.tokenizer(
											    text=_lowerCamelCase							,							add_special_tokens=_lowerCamelCase							,							padding=_lowerCamelCase							,							truncation=_lowerCamelCase							,							max_length=_lowerCamelCase							,							stride=_lowerCamelCase							,							pad_to_multiple_of=_lowerCamelCase							,							return_attention_mask=_lowerCamelCase							,							return_overflowing_tokens=_lowerCamelCase							,							return_special_tokens_mask=_lowerCamelCase							,							return_offsets_mapping=_lowerCamelCase							,							return_token_type_ids=_lowerCamelCase							,							return_length=_lowerCamelCase							,							verbose=_lowerCamelCase							,							return_tensors=_lowerCamelCase							,							**_lowerCamelCase							,							)
								else:
											UpperCAmelCase__					:   Any       				=       None

								if text_encoding is not None:
											encoding_image_processor.update(_lowerCamelCase)

								return encoding_image_processor




					def 			snake_case__  ( self							,							*_lowerCamelCase							,							**_lowerCamelCase):
								return self.tokenizer.batch_decode(*_lowerCamelCase							,							**_lowerCamelCase)




					def 			snake_case__  ( self							,							*_lowerCamelCase							,							**_lowerCamelCase):
								return self.tokenizer.decode(*_lowerCamelCase							,							**_lowerCamelCase)




					@property
					def 			snake_case__  ( self):
								UpperCAmelCase__					:   List[str]       				=       self.tokenizer.model_input_names
								UpperCAmelCase__					:   int       				=       self.image_processor.model_input_names
								return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names))



'''simple docstring'''



import functools







def       _UpperCamelCase (						UpperCamelCase__	, UpperCamelCase__   ):

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

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

			if len(UpperCamelCase__   ) == 0:
						return 0

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

			if max(UpperCamelCase__   ) >= 3_6_6:
						raise ValueError("""All days elements should be less than 366"""   )

			UpperCAmelCase__					:   Union[str, Any]       				=       set(UpperCamelCase__   )

			@functools.cache
			def dynamic_programming(UpperCamelCase__   ) -> int:
						if index > 3_6_5:
									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 + 3_0   )	, )

			return dynamic_programming(1   )


if __name__ == "__main__":
		import doctest

		doctest.testmod()