






"""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


SCREAMING_SNAKE_CASE						:						Tuple					   =       logging.get_logger(__name__)

SCREAMING_SNAKE_CASE						:						Optional[int]					   =       {
    '''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       snake_case_       (    _lowerCamelCase       ):



 """simple docstring"""

 SCREAMING_SNAKE_CASE_:							Tuple   			=					"""longformer"""


 def __init__(      self  ,					__a = 512  ,					__a = 2  ,					__a = 1  ,					__a = 0  ,					__a = 2  ,					__a = 3_0522  ,					__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  ,					):


     """simple docstring"""

     super().__init__(pad_token_id=__a  ,					**__a						)

     A__							 =       attention_window
     A__							 =       sep_token_id
     A__							 =       bos_token_id
     A__							 =       eos_token_id
     A__							 =       vocab_size
     A__							 =       hidden_size
     A__							 =       num_hidden_layers
     A__							 =       num_attention_heads
     A__							 =       hidden_act
     A__							 =       intermediate_size
     A__							 =       hidden_dropout_prob
     A__							 =       attention_probs_dropout_prob
     A__							 =       max_position_embeddings
     A__							 =       type_vocab_size
     A__							 =       initializer_range
     A__							 =       layer_norm_eps
     A__							 =       onnx_export





class       snake_case_       (    _lowerCamelCase       ):



 """simple docstring"""

 def __init__(      self  ,					__a  ,					__a = "default"  ,					__a = None						):


     """simple docstring"""

     super().__init__(__a  ,					__a  ,					__a						)
     A__							 =       True


 @property
 def       _UpperCAmelCase						(      self						):


     """simple docstring"""

     if self.task == "multiple-choice":
         A__							 =       {0: 'batch', 1: 'choice', 2: 'sequence'}
     else:
         A__							 =       {0: 'batch', 1: 'sequence'}
     return OrderedDict(
         [
             ('input_ids', dynamic_axis),
             ('attention_mask', dynamic_axis),
             ('global_attention_mask', dynamic_axis),
         ]						)


 @property
 def       _UpperCAmelCase						(      self						):


     """simple docstring"""

     A__							 =       super().outputs
     if self.task == "default":
         A__							 =       {0: 'batch'}
     return outputs


 @property
 def       _UpperCAmelCase						(      self						):


     """simple docstring"""

     return 1E-4


 @property
 def       _UpperCAmelCase						(      self						):


     """simple docstring"""

     return max(super().default_onnx_opset  ,					14						)






 def       _UpperCAmelCase						(      self  ,					__a  ,					__a = -1  ,					__a = -1  ,					__a = False  ,					__a = None  ,					):


     """simple docstring"""

     A__							 =       super().generate_dummy_inputs(
         preprocessor=__a  ,					batch_size=__a  ,					seq_length=__a  ,					is_pair=__a  ,					framework=__a						)
     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__							 =       torch.zeros_like(inputs['input_ids']						)
     # make every second token global
     A__							 =       1

     return inputs










"""simple docstring"""






from math import factorial, pi



def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__ = 30				):

				if not isinstance(lowerCAmelCase__       ,(int, float)				):
								raise ValueError('maclaurin_sin() requires either an int or float for theta'				)

				if not isinstance(lowerCAmelCase__       ,lowerCAmelCase__				) or accuracy <= 0:
								raise ValueError('maclaurin_sin() requires a positive int for accuracy'				)

				A__							 =       float(lowerCAmelCase__				)
				A__							 =       theta // (2 * pi)
				theta -= 2 * div * pi
				return sum(
				    (-1) ** r * theta ** (2 * r + 1) / factorial(2 * r + 1				) for r in range(lowerCAmelCase__				)				)



def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__ = 30				):

				if not isinstance(lowerCAmelCase__       ,(int, float)				):
								raise ValueError('maclaurin_cos() requires either an int or float for theta'				)

				if not isinstance(lowerCAmelCase__       ,lowerCAmelCase__				) or accuracy <= 0:
								raise ValueError('maclaurin_cos() requires a positive int for accuracy'				)

				A__							 =       float(lowerCAmelCase__				)
				A__							 =       theta // (2 * pi)
				theta -= 2 * div * pi
				return sum((-1) ** r * theta ** (2 * r) / factorial(2 * r				) for r in range(lowerCAmelCase__				)				)


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					print(maclaurin_sin(10))
					print(maclaurin_sin(-10))
					print(maclaurin_sin(10, 15))
					print(maclaurin_sin(-10, 15))

					print(maclaurin_cos(5))
					print(maclaurin_cos(-5))
					print(maclaurin_cos(10, 15))
					print(maclaurin_cos(-10, 15))


