




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


UpperCAmelCase_						=logging.get_logger(__name__)

UpperCAmelCase_						={
    """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			( __UpperCAmelCase  ):





							'''simple docstring'''



							__a							: Any										="""trocr"""
							__a							: List[Any]										=["""past_key_values"""]
							__a							: Dict										={
							    """num_attention_heads""": """decoder_attention_heads""",
							    """hidden_size""": """d_model""",
							    """num_hidden_layers""": """decoder_layers""",
							}



							def __init__( self       , UpperCAmelCase_=5_02_65       , UpperCAmelCase_=10_24       , UpperCAmelCase_=12       , UpperCAmelCase_=16       , UpperCAmelCase_=40_96       , UpperCAmelCase_="gelu"       , UpperCAmelCase_=5_12       , UpperCAmelCase_=0.1       , UpperCAmelCase_=0.0       , UpperCAmelCase_=0.0       , UpperCAmelCase_=2       , UpperCAmelCase_=0.02       , UpperCAmelCase_=0.0       , UpperCAmelCase_=True       , UpperCAmelCase_=False       , UpperCAmelCase_=True       , UpperCAmelCase_=True       , UpperCAmelCase_=1       , UpperCAmelCase_=0       , UpperCAmelCase_=2       , **UpperCAmelCase_       , ):
														lowerCAmelCase   =		vocab_size
														lowerCAmelCase   =		d_model
														lowerCAmelCase   =		decoder_layers
														lowerCAmelCase   =		decoder_attention_heads
														lowerCAmelCase   =		decoder_ffn_dim
														lowerCAmelCase   =		activation_function
														lowerCAmelCase   =		max_position_embeddings
														lowerCAmelCase   =		dropout
														lowerCAmelCase   =		attention_dropout
														lowerCAmelCase   =		activation_dropout
														lowerCAmelCase   =		init_std
														lowerCAmelCase   =		decoder_layerdrop
														lowerCAmelCase   =		use_cache
														lowerCAmelCase   =		scale_embedding
														lowerCAmelCase   =		use_learned_position_embeddings
														lowerCAmelCase   =		layernorm_embedding

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









def       UpperCAmelCase       (     _snake_case						, _snake_case						, _snake_case							):

							def count_of_possible_combinations(_snake_case							) -> int:
														if target < 0:
																					return 0
														if target == 0:
																					return 1
														return sum(count_of_possible_combinations(target - item							) for item in array							)

							return count_of_possible_combinations(_snake_case							)



def       UpperCAmelCase       (     _snake_case						, _snake_case						, _snake_case							):

							def count_of_possible_combinations_with_dp_array(
							    _snake_case						, _snake_case							) -> int:
														if target < 0:
																					return 0
														if target == 0:
																					return 1
														if dp_array[target] != -1:
																					return dp_array[target]
														lowerCAmelCase   =		sum(
														    count_of_possible_combinations_with_dp_array(target - item						, _snake_case							)
														    for item in array							)
														lowerCAmelCase   =		answer
														return answer

							lowerCAmelCase   =		[-1] * (target + 1)
							return count_of_possible_combinations_with_dp_array(_snake_case						, _snake_case							)



def       UpperCAmelCase       (     _snake_case						, _snake_case						, _snake_case							):
							lowerCAmelCase   =		[0] * (target + 1)
							lowerCAmelCase   =		1

							for i in range(1						, target + 1							):
														for j in range(_snake_case							):
																					if i - array[j] >= 0:
																												dp_array[i] += dp_array[i - array[j]]

							return dp_array[target]


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		UpperCAmelCase_						=3
		UpperCAmelCase_						=5
		UpperCAmelCase_						=[1, 2, 5]
		print(combination_sum_iv(n, array, target))



