





"""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	     =					logging.get_logger(__name__)

A	     =					{
    '''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     (     _UpperCamelCase							):







					'''simple docstring'''




					__lowerCAmelCase					=					'''longformer'''







					def __init__(  self		,     _UpperCAmelCase = 512		,     _UpperCAmelCase = 2		,     _UpperCAmelCase = 1		,     _UpperCAmelCase = 0		,     _UpperCAmelCase = 2		,     _UpperCAmelCase = 30522		,     _UpperCAmelCase = 768		,     _UpperCAmelCase = 12		,     _UpperCAmelCase = 12		,     _UpperCAmelCase = 3072		,     _UpperCAmelCase = "gelu"		,     _UpperCAmelCase = 0.1		,     _UpperCAmelCase = 0.1		,     _UpperCAmelCase = 512		,     _UpperCAmelCase = 2		,     _UpperCAmelCase = 0.0_2		,     _UpperCAmelCase = 1e-1_2		,     _UpperCAmelCase = False		,     **_UpperCAmelCase		,     ):
									super().__init__(pad_token_id=_UpperCAmelCase		,     **_UpperCAmelCase       )

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






class 			__lowercase     (     _UpperCamelCase							):







					'''simple docstring'''




					def __init__(  self		,     _UpperCAmelCase		,     _UpperCAmelCase = "default"		,     _UpperCAmelCase = None       ):
									super().__init__(_UpperCAmelCase		,     _UpperCAmelCase		,     _UpperCAmelCase       )
									__a	:  Optional[int]         =					True







					@property
					def 	_lowerCamelCase						(  self       ):
									if self.task == "multiple-choice":
													__a	:  List[str]         =					{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
									else:
													__a	:  str         =					{0: '''batch''', 1: '''sequence'''}
									return OrderedDict(
									    [
									        ('''input_ids''', dynamic_axis),
									        ('''attention_mask''', dynamic_axis),
									        ('''global_attention_mask''', dynamic_axis),
									    ]       )







					@property
					def 	_lowerCamelCase						(  self       ):
									__a	:  Tuple         =					super().outputs
									if self.task == "default":
													__a	:  List[str]         =					{0: '''batch'''}
									return outputs







					@property
					def 	_lowerCamelCase						(  self       ):
									return 1e-4







					@property
					def 	_lowerCamelCase						(  self       ):
									# needs to be >= 14 to support tril operator
									return max(super().default_onnx_opset		,     14       )







					def 	_lowerCamelCase						(  self		,     _UpperCAmelCase		,     _UpperCAmelCase = -1		,     _UpperCAmelCase = -1		,     _UpperCAmelCase = False		,     _UpperCAmelCase = None		,     ):
									__a	:  Union[str, Any]         =					super().generate_dummy_inputs(
									    preprocessor=_UpperCAmelCase		,     batch_size=_UpperCAmelCase		,     seq_length=_UpperCAmelCase		,     is_pair=_UpperCAmelCase		,     framework=_UpperCAmelCase       )
									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
									__a	:  Optional[int]         =					torch.zeros_like(inputs['''input_ids''']       )
									# make every second token global
									__a	:  Dict         =					1

									return inputs






"""simple docstring"""






def       __A (     a_  :int = 1_00_00_00)						->						int:
				__a	:  Tuple         =					[i - 1 for i in range(limit + 1)]

				for i in range(2				,    limit + 1):
								if phi[i] == i - 1:
												for j in range(2 * i				,    limit + 1				,    a_):
																phi[j] -= phi[j] // i

				return sum(phi[2 : limit + 1])


if __name__ == "__main__":
		print(solution())