


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


snake_case__			 =						logging.get_logger(__name__)

snake_case__			 =						{
    '''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 					lowerCAmelCase_ (       __SCREAMING_SNAKE_CASE):
      lowerCamelCase_         =     'longformer'




      def __init__(	self						:   Union[str, Any]   ,     __A						:   Union[List[int], int] = 512   ,     __A						:   int = 2   ,     __A						:   int = 1   ,     __A						:   int = 0   ,     __A						:   int = 2   ,     __A						:   int = 30522   ,     __A						:   int = 768   ,     __A						:   int = 12   ,     __A						:   int = 12   ,     __A						:   int = 3072   ,     __A						:   str = "gelu"   ,     __A						:   float = 0.1   ,     __A						:   float = 0.1   ,     __A						:   int = 512   ,     __A						:   int = 2   ,     __A						:   float = 0.02   ,     __A						:   float = 1E-12   ,     __A						:   bool = False   ,     **__A						:   int   ,     )      ->Any:






         """simple docstring"""






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

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






class 					lowerCAmelCase_ (       __SCREAMING_SNAKE_CASE):




      def __init__(	self						:   List[Any]   ,     __A						:   "PretrainedConfig"   ,     __A						:   str = "default"   ,     __A						:   "List[PatchingSpec]" = None						)      ->List[Any]:






         """simple docstring"""






         super().__init__(__snake_case   ,     __snake_case   ,     __snake_case						)
         a__ :Optional[Any]						  =    True




      @property
      def  _snake_case					(	self						:   Optional[int]						)      ->Optional[int]:






         """simple docstring"""






         if self.task == "multiple-choice":
            a__ :List[str]						  =    {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
         else:
            a__ :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						:   Union[str, Any]						)      ->str:






         """simple docstring"""






         a__ :Dict						  =    super().outputs
         if self.task == "default":
            a__ :Optional[Any]						  =    {0: '''batch'''}
         return outputs




      @property
      def  _snake_case					(	self						:   List[Any]						)      ->List[str]:






         """simple docstring"""






         return 1E-4




      @property
      def  _snake_case					(	self						:   Union[str, Any]						)      ->Tuple:






         """simple docstring"""






         return max(super().default_onnx_opset   ,     14						)






      def  _snake_case					(	self						:   Dict   ,     __A						:   "PreTrainedTokenizerBase"   ,     __A						:   int = -1   ,     __A						:   int = -1   ,     __A						:   bool = False   ,     __A						:   Optional[TensorType] = None   ,     )      ->Tuple:






         """simple docstring"""






         a__ :Tuple						  =    super().generate_dummy_inputs(
             preprocessor=__snake_case   ,     batch_size=__snake_case   ,     seq_length=__snake_case   ,     is_pair=__snake_case   ,     framework=__snake_case						)
         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__ :int						  =    torch.zeros_like(inputs["input_ids"]						)
         # make every second token global
         a__ :Dict						  =    1

         return inputs






def 				lowerCamelCase__	(      a	:   int	,  a	:   int				)    ->	Any:





			"""simple docstring"""
			# "extended trapezoidal rule"
			# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
			a__ :Optional[int]						  =    (boundary[1] - boundary[0]) / steps
			a__ :str						  =    boundary[0]
			a__ :Optional[int]						  =    boundary[1]
			a__ :str						  =    make_points(a	,  a	,  a				)
			a__ :Any						  =    0.0
			y += (h / 2.0) * f(a				)
			for i in x_i:
						# print(i)
						y += h * f(a				)
			y += (h / 2.0) * f(a				)
			return y


def 				lowerCamelCase__	(      a	:   Any	,  a	:   str	,  a	:   Dict				)    ->	int:





			"""simple docstring"""
			a__ :Union[str, Any]						  =    a + h
			while x < (b - h):
						yield x
						a__ :str						  =    x + h


def 				lowerCamelCase__	(      a	:   Optional[int]				)    ->	List[Any]:  # enter your function here





			"""simple docstring"""
			a__ :Tuple						  =    (x - 0) * (x - 0)
			return y


def 				lowerCamelCase__	(      )    ->	List[str]:





			"""simple docstring"""
			a__ :Optional[Any]						  =    0.0  # Lower bound of integration
			a__ :Optional[Any]						  =    1.0  # Upper bound of integration
			a__ :List[str]						  =    1_0.0  # define number of steps or resolution
			a__ :int						  =    [a, b]  # define boundary of integration
			a__ :str						  =    method_a(a	,  a				)
			print(F'''y = {y}'''				)


if __name__ == "__main__":
		main()


