


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        UpperCamelCase__   (	__magic_name__   ):
					__SCREAMING_SNAKE_CASE       :  Any						=   'longformer'

					def __init__(     self       :   Union[str, Any]							,					UpperCamelCase__       :   Union[List[int], int] = 512							,					UpperCamelCase__       :   int = 2							,					UpperCamelCase__       :   int = 1							,					UpperCamelCase__       :   int = 0							,					UpperCamelCase__       :   int = 2							,					UpperCamelCase__       :   int = 30_522							,					UpperCamelCase__       :   int = 768							,					UpperCamelCase__       :   int = 12							,					UpperCamelCase__       :   int = 12							,					UpperCamelCase__       :   int = 3_072							,					UpperCamelCase__       :   str = "gelu"							,					UpperCamelCase__       :   float = 0.1							,					UpperCamelCase__       :   float = 0.1							,					UpperCamelCase__       :   int = 512							,					UpperCamelCase__       :   int = 2							,					UpperCamelCase__       :   float = 0.02							,					UpperCamelCase__       :   float = 1e-12							,					UpperCamelCase__       :   bool = False							,					**UpperCamelCase__       :   Optional[int]							,					):






										'''simple docstring'''






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

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







class        UpperCamelCase__   (	__magic_name__   ):

					def __init__(     self       :   Optional[Any]							,					UpperCamelCase__       :   "PretrainedConfig"							,					UpperCamelCase__       :   str = "default"							,					UpperCamelCase__       :   "List[PatchingSpec]" = None       ):






										'''simple docstring'''






										super().__init__(UpperCamelCase__							,					UpperCamelCase__							,					UpperCamelCase__       )
										lowercase_  							=			True

					@property
					def   UpperCAmelCase__       (     self       :   Optional[Any]       ):






										'''simple docstring'''






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

					@property
					def   UpperCAmelCase__       (     self       :   Dict       ):






										'''simple docstring'''






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

					@property
					def   UpperCAmelCase__       (     self       :   List[Any]       ):






										'''simple docstring'''






										return 1e-4

					@property
					def   UpperCAmelCase__       (     self       :   Dict       ):






										'''simple docstring'''






										return max(super().default_onnx_opset							,					14       )







					def   UpperCAmelCase__       (     self       :   Union[str, Any]							,					UpperCamelCase__       :   "PreTrainedTokenizerBase"							,					UpperCamelCase__       :   int = -1							,					UpperCamelCase__       :   int = -1							,					UpperCamelCase__       :   bool = False							,					UpperCamelCase__       :   Optional[TensorType] = None							,					):






										'''simple docstring'''






										lowercase_  							=			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
										lowercase_  							=			torch.zeros_like(inputs["""input_ids"""]       )
										# make every second token global
										lowercase_  							=			1

										return inputs






def 			UpperCAmelCase_				(      UpperCAmelCase__  ):
					if not isinstance(UpperCAmelCase__						,							UpperCAmelCase__  ):
										raise TypeError("""Input value must be an 'int' type"""  )

					lowercase_  							=			0
					while number:
										position += 1
										number >>= 1

					return position


if __name__ == "__main__":
							import doctest

							doctest.testmod()


