
"""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


SCREAMING_SNAKE_CASE      =     logging.get_logger(__name__)

SCREAMING_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   __a  (      _lowerCAmelCase	):
       UpperCamelCase_		:					Tuple   =			'''longformer'''






       def __init__(  self :							Tuple       ,      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[Any]       ,      )->  Optional[int]:







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

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





class   __a  (      _lowerCAmelCase	):






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







              """simple docstring"""
              super().__init__(UpperCAmelCase_       ,      UpperCAmelCase_       ,      UpperCAmelCase_			)
              UpperCamelCase					 =		True






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







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






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







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






       @property
       def 	_SCREAMING_SNAKE_CASE       (  self :							int			)->  float:







              """simple docstring"""
              return 1e-4






       @property
       def 	_SCREAMING_SNAKE_CASE       (  self :							List[str]			)->  int:







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






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







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

              return inputs







"""simple docstring"""


SCREAMING_SNAKE_CASE      =     {
    """meter""": """m""",
    """kilometer""": """km""",
    """megametre""": """Mm""",
    """gigametre""": """Gm""",
    """terametre""": """Tm""",
    """petametre""": """Pm""",
    """exametre""": """Em""",
    """zettametre""": """Zm""",
    """yottametre""": """Ym""",
}
# Exponent of the factor(meter)
SCREAMING_SNAKE_CASE      =     {
    """m""": 0,
    """km""": 3,
    """Mm""": 6,
    """Gm""": 9,
    """Tm""": 12,
    """Pm""": 15,
    """Em""": 18,
    """Zm""": 21,
    """Ym""": 24,
}



def 	lowerCamelCase__			(							UpperCAmelCase_		,      UpperCAmelCase_		,      UpperCAmelCase_				)->							float:







       """simple docstring"""
       UpperCamelCase					 =		from_type.lower().strip("s"				)
       UpperCamelCase					 =		to_type.lower().strip("s"				)

       UpperCamelCase					 =		UNIT_SYMBOL.get(UpperCAmelCase_		,      UpperCAmelCase_				)
       UpperCamelCase					 =		UNIT_SYMBOL.get(UpperCAmelCase_		,      UpperCAmelCase_				)

       if from_sanitized not in METRIC_CONVERSION:
              UpperCamelCase					 =		(
                  F"Invalid 'from_type' value: {from_type!r}.\n"
                  F"Conversion abbreviations are: {', '.join(UpperCAmelCase_				)}"
              )
              raise ValueError(UpperCAmelCase_				)
       if to_sanitized not in METRIC_CONVERSION:
              UpperCamelCase					 =		(
                  F"Invalid 'to_type' value: {to_type!r}.\n"
                  F"Conversion abbreviations are: {', '.join(UpperCAmelCase_				)}"
              )
              raise ValueError(UpperCAmelCase_				)
       UpperCamelCase					 =		METRIC_CONVERSION[from_sanitized]
       UpperCamelCase					 =		METRIC_CONVERSION[to_sanitized]
       UpperCamelCase					 =		1

       if from_exponent > to_exponent:
              UpperCamelCase					 =		from_exponent - to_exponent
       else:
              UpperCamelCase					 =		-(to_exponent - from_exponent)

       return value * pow(10		,      UpperCAmelCase_				)


if __name__ == "__main__":
      from doctest import testmod

      testmod()





