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   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     'longformer'







							def __init__(				self     :    Union[str, Any]	,					__snake_case     :    Union[List[int], int] = 512	,					__snake_case     :    int = 2	,					__snake_case     :    int = 1	,					__snake_case     :    int = 0	,					__snake_case     :    int = 2	,					__snake_case     :    int = 30522	,					__snake_case     :    int = 768	,					__snake_case     :    int = 12	,					__snake_case     :    int = 12	,					__snake_case     :    int = 3072	,					__snake_case     :    str = "gelu"	,					__snake_case     :    float = 0.1	,					__snake_case     :    float = 0.1	,					__snake_case     :    int = 512	,					__snake_case     :    int = 2	,					__snake_case     :    float = 0.0_2	,					__snake_case     :    float = 1e-1_2	,					__snake_case     :    bool = False	,					**__snake_case     :    int	,					):
										super().__init__(pad_token_id=__snake_case	,					**__snake_case		)

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


class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):







							def __init__(				self     :    List[Any]	,					__snake_case     :    "PretrainedConfig"	,					__snake_case     :    str = "default"	,					__snake_case     :    "List[PatchingSpec]" = None		):
										super().__init__(__snake_case	,					__snake_case	,					__snake_case		)
										lowerCamelCase						:Optional[Any]						  =     True







							@property
							def 				snake_case  (				self     :    Optional[int]		):
										if self.task == "multiple-choice":
													lowerCamelCase						:List[str]						  =     {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
										else:
													lowerCamelCase						: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]		):
										lowerCamelCase						:Dict						  =     super().outputs
										if self.task == "default":
													lowerCamelCase						:Optional[Any]						  =     {0: '''batch'''}
										return outputs







							@property
							def 				snake_case  (				self     :    List[Any]		):
										return 1e-4







							@property
							def 				snake_case  (				self     :    Union[str, Any]		):
										# needs to be >= 14 to support tril operator
										return max(super().default_onnx_opset	,					14		)







							def 				snake_case  (				self     :    Dict	,					__snake_case     :    "PreTrainedTokenizerBase"	,					__snake_case     :    int = -1	,					__snake_case     :    int = -1	,					__snake_case     :    bool = False	,					__snake_case     :    Optional[TensorType] = None	,					):
										lowerCamelCase						: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
										lowerCamelCase						:int						  =     torch.zeros_like(inputs['''input_ids''']		)
										# make every second token global
										lowerCamelCase						:Dict						  =     1

										return inputs




def  _lowerCamelCase					(   a_				: str						,			a_				: str):
			lowerCamelCase						:List[str]						  =     len(a_)
			lowerCamelCase						:List[str]						  =     len(a_)
			lowerCamelCase						:int						  =     [[False for _ in range(m + 1)] for _ in range(n + 1)]
			lowerCamelCase						:Optional[Any]						  =     True
			for i in range(a_):
						for j in range(m + 1):
									if dp[i][j]:
												if j < m and a[i].upper() == b[j]:
															lowerCamelCase						:Any						  =     True
												if a[i].islower():
															lowerCamelCase						:List[str]						  =     True
			return dp[n][m]


if __name__ == "__main__":
			import doctest

			doctest.testmod()



