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  UpperCamelCase				( __lowercase ):

     '''simple docstring'''

     A_										=  'longformer'



     def __init__(					self				,				A_ = 5_12				,				A_ = 2				,				A_ = 1				,				A_ = 0				,				A_ = 2				,				A_ = 3_05_22				,				A_ = 7_68				,				A_ = 12				,				A_ = 12				,				A_ = 30_72				,				A_ = "gelu"				,				A_ = 0.1				,				A_ = 0.1				,				A_ = 5_12				,				A_ = 2				,				A_ = 0.02				,				A_ = 1E-1_2				,				A_ = False				,				**A_				,				) ->				int:






           """simple docstring"""
           super().__init__(pad_token_id=A_				,				**A_						)

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





class  UpperCamelCase				( __lowercase ):

     '''simple docstring'''

     def __init__(					self				,				A_				,				A_ = "default"				,				A_ = None						) ->				List[Any]:






           """simple docstring"""
           super().__init__(A_				,				A_				,				A_						)
           _lowerCamelCase			    =				True



     @property
     def 		UpperCamelCase_						(					self						) ->				Mapping[str, Mapping[int, str]]:






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



     @property
     def 		UpperCamelCase_						(					self						) ->				Mapping[str, Mapping[int, str]]:






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



     @property
     def 		UpperCamelCase_						(					self						) ->				float:






           """simple docstring"""
           return 1E-4



     @property
     def 		UpperCamelCase_						(					self						) ->				int:






           """simple docstring"""
           # needs to be >= 14 to support tril operator
           return max(super().default_onnx_opset				,				14						)





     def 		UpperCamelCase_						(					self				,				A_				,				A_ = -1				,				A_ = -1				,				A_ = False				,				A_ = None				,				) ->				Mapping[str, Any]:






           """simple docstring"""
           _lowerCamelCase			    =				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
           _lowerCamelCase			    =				torch.zeros_like(inputs['''input_ids''']						)
           # make every second token global
           _lowerCamelCase			    =				1

           return inputs
def       __magic_name__(  __UpperCAmelCase ,						__UpperCAmelCase		)						->    str:



      '''simple docstring'''

      _lowerCamelCase			    =				0
      while b > 0:
            if b & 1:
                  res += a

            a += a
            b >>= 1

      return res
def       __magic_name__(  __UpperCAmelCase ,						__UpperCAmelCase ,						__UpperCAmelCase		)						->    Optional[Any]:



      '''simple docstring'''

      _lowerCamelCase			    =				0
      while b > 0:
            if b & 1:
                  _lowerCamelCase			    =				((res % c) + (a % c)) % c

            a += a
            b >>= 1

      return res