





'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCamelCase : Optional[int]											=			logging.get_logger(__name__)

__lowerCamelCase : int											=			{
    "microsoft/trocr-base-handwritten": (
        "https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json"
    ),
    # See all TrOCR models at https://huggingface.co/models?filter=trocr
}

class       UpperCAmelCase (						_lowercase  ):
		UpperCAmelCase					:	Any 			=		'''trocr'''
		UpperCAmelCase					:	List[str] 			=		['''past_key_values''']
		UpperCAmelCase					:	List[Any] 			=		{
		    '''num_attention_heads''': '''decoder_attention_heads''',
		    '''hidden_size''': '''d_model''',
		    '''num_hidden_layers''': '''decoder_layers''',
		}




		def __init__(self      :	Union[str, Any]							,			A__      :	List[Any]=5_0_2_6_5							,			A__      :	List[str]=1_0_2_4							,			A__      :	Union[str, Any]=1_2							,			A__      :	Optional[int]=1_6							,			A__      :	Union[str, Any]=4_0_9_6							,			A__      :	Optional[Any]="gelu"							,			A__      :	Any=5_1_2							,			A__      :	Any=0.1							,			A__      :	Dict=0.0							,			A__      :	List[Any]=0.0							,			A__      :	Union[str, Any]=2							,			A__      :	Optional[int]=0.0_2							,			A__      :	int=0.0							,			A__      :	int=True							,			A__      :	Any=False							,			A__      :	Union[str, Any]=True							,			A__      :	Any=True							,			A__      :	Tuple=1							,			A__      :	List[Any]=0							,			A__      :	List[str]=2							,			**A__      :	Optional[int]							,			)					-> Any:
						lowercase         = vocab_size
						lowercase         = d_model
						lowercase         = decoder_layers
						lowercase         = decoder_attention_heads
						lowercase         = decoder_ffn_dim
						lowercase         = activation_function
						lowercase         = max_position_embeddings
						lowercase         = dropout
						lowercase         = attention_dropout
						lowercase         = activation_dropout
						lowercase         = init_std
						lowercase         = decoder_layerdrop
						lowercase         = use_cache
						lowercase         = scale_embedding
						lowercase         = use_learned_position_embeddings
						lowercase         = layernorm_embedding

						super().__init__(
						    pad_token_id=A__							,			bos_token_id=A__							,			eos_token_id=A__							,			decoder_start_token_id=A__							,			**A__							,			)











'''simple docstring'''

import functools







def 							UpperCAmelCase_    (	lowerCAmelCase_		,							lowerCAmelCase_							):

				"""simple docstring"""






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

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

				if len(lowerCAmelCase_							) == 0:
								return 0

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

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

				lowercase         = set(lowerCAmelCase_							)

				@functools.cache
				def dynamic_programming(lowerCAmelCase_							) -> 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()




