

"""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    snake_case     (    __snake_case  ):
				SCREAMING_SNAKE_CASE_       :				str       				=  """longformer"""

				def __init__(     self							:    Union[str, Any]					,  UpperCamelCase__							:    Union[List[int], int] = 5_1_2					,  UpperCamelCase__							:    int = 2					,  UpperCamelCase__							:    int = 1					,  UpperCamelCase__							:    int = 0					,  UpperCamelCase__							:    int = 2					,  UpperCamelCase__							:    int = 3_0_5_2_2					,  UpperCamelCase__							:    int = 7_6_8					,  UpperCamelCase__							:    int = 1_2					,  UpperCamelCase__							:    int = 1_2					,  UpperCamelCase__							:    int = 3_0_7_2					,  UpperCamelCase__							:    str = "gelu"					,  UpperCamelCase__							:    float = 0.1					,  UpperCamelCase__							:    float = 0.1					,  UpperCamelCase__							:    int = 5_1_2					,  UpperCamelCase__							:    int = 2					,  UpperCamelCase__							:    float = 0.02					,  UpperCamelCase__							:    float = 1e-12					,  UpperCamelCase__							:    bool = False					,  **UpperCamelCase__							:    List[Any]					,  )->       List[str]:



						'''simple docstring'''


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

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





class    snake_case     (    __snake_case  ):

				def __init__(     self							:    int					,  UpperCamelCase__							:    "PretrainedConfig"					,  UpperCamelCase__							:    str = "default"					,  UpperCamelCase__							:    "List[PatchingSpec]" = None)->       Tuple:



						'''simple docstring'''


						super().__init__(UpperCamelCase__					,  UpperCamelCase__					,  UpperCamelCase__)
						__lowerCAmelCase:	Any   				=      True

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



						'''simple docstring'''


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

				@property
				def 							lowercase_					(     self							:    Union[str, Any])->       Mapping[str, Mapping[int, str]]:



						'''simple docstring'''


						__lowerCAmelCase:	Union[str, Any]   				=      super().outputs
						if self.task == "default":
								__lowerCAmelCase:	int   				=      {0: "batch"}
						return outputs

				@property
				def 							lowercase_					(     self							:    Any)->       float:



						'''simple docstring'''


						return 1e-4

				@property
				def 							lowercase_					(     self							:    str)->       int:



						'''simple docstring'''


						return max(super().default_onnx_opset					,  1_4)




				def 							lowercase_					(     self							:    Dict					,  UpperCamelCase__							:    "PreTrainedTokenizerBase"					,  UpperCamelCase__							:    int = -1					,  UpperCamelCase__							:    int = -1					,  UpperCamelCase__							:    bool = False					,  UpperCamelCase__							:    Optional[TensorType] = None					,  )->       Mapping[str, Any]:



						'''simple docstring'''


						__lowerCAmelCase:	Optional[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
						__lowerCAmelCase:	Tuple   				=      torch.zeros_like(inputs["input_ids"])
						# make every second token global
						__lowerCAmelCase:	Optional[int]   				=      1

						return inputs





"""simple docstring"""


import numpy as np






def    a__   (   __SCREAMING_SNAKE_CASE			)     ->     np.array:
		return (2 / (1 + np.exp(-2 * vector			))) - 1


if __name__ == "__main__":
			import doctest

			doctest.testmod()


