




"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging


if TYPE_CHECKING:
					from ...onnx.config import PatchingSpec
					from ...tokenization_utils_base import PreTrainedTokenizerBase


a_				:    List[Any]										=     logging.get_logger(__name__)

a_				:    Tuple										=     {
    '''allenai/longformer-base-4096''': '''https://huggingface.co/allenai/longformer-base-4096/resolve/main/config.json''',
    '''allenai/longformer-large-4096''': '''https://huggingface.co/allenai/longformer-large-4096/resolve/main/config.json''',
    '''allenai/longformer-large-4096-finetuned-triviaqa''': (
        '''https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/config.json'''
    ),
    '''allenai/longformer-base-4096-extra.pos.embd.only''': (
        '''https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/config.json'''
    ),
    '''allenai/longformer-large-4096-extra.pos.embd.only''': (
        '''https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/config.json'''
    ),
}

class __lowercase(      a__				):




					'''simple docstring'''


					__a						:						Union[str, Any]     		= """longformer"""
					def __init__(    self						,	__a = 512						,	__a = 2						,	__a = 1						,	__a = 0						,	__a = 2						,	__a = 30522						,	__a = 768						,	__a = 12						,	__a = 12						,	__a = 3072						,	__a = "gelu"						,	__a = 0.1						,	__a = 0.1						,	__a = 512						,	__a = 2						,	__a = 0.02						,	__a = 1E-12						,	__a = False						,	**__a						,	):
								super().__init__(pad_token_id=lowerCAmelCase__						,	**lowerCAmelCase__     )

								__lowerCamelCase					:	Optional[Any]	       =				attention_window
								__lowerCamelCase					:	Dict	       =				sep_token_id
								__lowerCamelCase					:	int	       =				bos_token_id
								__lowerCamelCase					:	Union[str, Any]	       =				eos_token_id
								__lowerCamelCase					:	Tuple	       =				vocab_size
								__lowerCamelCase					:	Optional[Any]	       =				hidden_size
								__lowerCamelCase					:	Union[str, Any]	       =				num_hidden_layers
								__lowerCamelCase					:	int	       =				num_attention_heads
								__lowerCamelCase					:	List[Any]	       =				hidden_act
								__lowerCamelCase					:	Tuple	       =				intermediate_size
								__lowerCamelCase					:	int	       =				hidden_dropout_prob
								__lowerCamelCase					:	Tuple	       =				attention_probs_dropout_prob
								__lowerCamelCase					:	Any	       =				max_position_embeddings
								__lowerCamelCase					:	Union[str, Any]	       =				type_vocab_size
								__lowerCamelCase					:	Dict	       =				initializer_range
								__lowerCamelCase					:	str	       =				layer_norm_eps
								__lowerCamelCase					:	Tuple	       =				onnx_export



class __lowercase(      a__				):




					'''simple docstring'''


					def __init__(    self						,	__a						,	__a = "default"						,	__a = None     ):
								super().__init__(lowerCAmelCase__						,	lowerCAmelCase__						,	lowerCAmelCase__     )
								__lowerCamelCase					:	Dict	       =				True
					@property
					def     snake_case_				(    self     ):
								if self.task == "multiple-choice":
											__lowerCamelCase					:	Any	       =				{0: "batch", 1: "choice", 2: "sequence"}
								else:
											__lowerCamelCase					:	Optional[Any]	       =				{0: "batch", 1: "sequence"}
								return OrderedDict(
								    [
								        ('input_ids', dynamic_axis),
								        ('attention_mask', dynamic_axis),
								        ('global_attention_mask', dynamic_axis),
								    ]     )
					@property
					def     snake_case_				(    self     ):
								__lowerCamelCase					:	Tuple	       =				super().outputs
								if self.task == "default":
											__lowerCamelCase					:	Any	       =				{0: "batch"}
								return outputs
					@property
					def     snake_case_				(    self     ):
								return 1E-4
					@property
					def     snake_case_				(    self     ):
								# needs to be >= 14 to support tril operator
								return max(super().default_onnx_opset						,	14     )





					def     snake_case_				(    self						,	__a						,	__a = -1						,	__a = -1						,	__a = False						,	__a = None						,	):
								__lowerCamelCase					:	Tuple	       =				super().generate_dummy_inputs(
								    preprocessor=lowerCAmelCase__						,	batch_size=lowerCAmelCase__						,	seq_length=lowerCAmelCase__						,	is_pair=lowerCAmelCase__						,	framework=lowerCAmelCase__     )
								import torch

								# for some reason, replacing this code by inputs["global_attention_mask"] = torch.randint(2, inputs["input_ids"].shape, dtype=torch.int64)
								# makes the export fail randomly
								__lowerCamelCase					:	Optional[int]	       =				torch.zeros_like(inputs['input_ids']     )
								# make every second token global
								__lowerCamelCase					:	Optional[Any]	       =				1

								return inputs









"""simple docstring"""
def 						UpperCAmelCase				(			A__:    int							,				A__:    list[int]							,				A__:    int     )  ->     int:

			def count_of_possible_combinations(A__:    int     ) -> 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(A__     )





def 						UpperCAmelCase				(			A__:    int							,				A__:    list[int]							,				A__:    int     )  ->     int:

			def count_of_possible_combinations_with_dp_array(
			    A__:    int							,				A__:    list[int]     ) -> int:
						if target < 0:
									return 0
						if target == 0:
									return 1
						if dp_array[target] != -1:
									return dp_array[target]
						__lowerCamelCase					:	Dict	       =				sum(
						    count_of_possible_combinations_with_dp_array(target - item							,				A__     )
						    for item in array     )
						__lowerCamelCase					:	str	       =				answer
						return answer

			__lowerCamelCase					:	Union[str, Any]	       =				[-1] * (target + 1)
			return count_of_possible_combinations_with_dp_array(A__							,				A__     )





def 						UpperCAmelCase				(			A__:    int							,				A__:    list[int]							,				A__:    int     )  ->     int:
			__lowerCamelCase					:	int	       =				[0] * (target + 1)
			__lowerCamelCase					:	str	       =				1

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

			return dp_array[target]


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					a_				:    Any										=     3
					a_				:    str										=     5
					a_				:    List[Any]										=     [1, 2, 5]
					print(combination_sum_iv(n, array, target))



