


"""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


snake_case__						:   Optional[int]			 = logging.get_logger(__name__)

snake_case__						:   List[Any]			 = {
    '''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_(				a__	):
     __UpperCamelCase     =    '''longformer'''






     def __init__(		self     :    Optional[int]    , 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]    , ):
           super().__init__(pad_token_id=UpperCamelCase_    , **UpperCamelCase_ )

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



class 						snake_case_(				a__	):






     def __init__(		self     :    Union[str, Any]    , UpperCamelCase_     :    "PretrainedConfig"    , UpperCamelCase_     :    str = "default"    , UpperCamelCase_     :    "List[PatchingSpec]" = None ):
           super().__init__(UpperCamelCase_    , UpperCamelCase_    , UpperCamelCase_ )
           lowerCAmelCase    :		int				=      True






     @property
     def    lowerCamelCase__   (		self     :    Optional[Any] ):
           if self.task == "multiple-choice":
                 lowerCAmelCase    :		Tuple				=      {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
           else:
                 lowerCAmelCase    :		List[str]				=      {0: '''batch''', 1: '''sequence'''}
           return OrderedDict(
               [
                   ('''input_ids''', dynamic_axis),
                   ('''attention_mask''', dynamic_axis),
                   ('''global_attention_mask''', dynamic_axis),
               ] )






     @property
     def    lowerCamelCase__   (		self     :    str ):
           lowerCAmelCase    :		Optional[int]				=      super().outputs
           if self.task == "default":
                 lowerCAmelCase    :		List[str]				=      {0: '''batch'''}
           return outputs






     @property
     def    lowerCamelCase__   (		self     :    List[Any] ):
           return 1E-4






     @property
     def    lowerCamelCase__   (		self     :    Any ):
           # needs to be >= 14 to support tril operator
           return max(super().default_onnx_opset    , 1_4 )






     def    lowerCamelCase__   (		self     :    int    , UpperCamelCase_     :    "PreTrainedTokenizerBase"    , UpperCamelCase_     :    int = -1    , UpperCamelCase_     :    int = -1    , UpperCamelCase_     :    bool = False    , UpperCamelCase_     :    Optional[TensorType] = None    , ):
           lowerCAmelCase    :		Optional[int]				=      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    :		Optional[int]				=      torch.zeros_like(inputs['''input_ids'''] )
           # make every second token global
           lowerCAmelCase    :		Union[str, Any]				=      1

           return inputs








"""simple docstring"""






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







def      _snake_case			(				lowercase__							,    lowercase__							,    lowercase__		):
				_lowerCamelCase     :			List[Any]    =    from_type.lower().strip('s'		)
				_lowerCamelCase     :			List[Any]    =    to_type.lower().strip('s'		)

				_lowerCamelCase     :			Optional[int]    =    UNIT_SYMBOL.get(lowercase__							,    lowercase__		)
				_lowerCamelCase     :			Any    =    UNIT_SYMBOL.get(lowercase__							,    lowercase__		)

				if from_sanitized not in METRIC_CONVERSION:
								_lowerCamelCase     :			Tuple    =    (
								    f'''Invalid \'from_type\' value: {from_type!r}.\n'''
								    f'''Conversion abbreviations are: {', '.join(lowercase__		)}'''
								)
								raise ValueError(lowercase__		)
				if to_sanitized not in METRIC_CONVERSION:
								_lowerCamelCase     :			Any    =    (
								    f'''Invalid \'to_type\' value: {to_type!r}.\n'''
								    f'''Conversion abbreviations are: {', '.join(lowercase__		)}'''
								)
								raise ValueError(lowercase__		)
				_lowerCamelCase     :			List[Any]    =    METRIC_CONVERSION[from_sanitized]
				_lowerCamelCase     :			int    =    METRIC_CONVERSION[to_sanitized]
				_lowerCamelCase     :			List[str]    =    1

				if from_exponent > to_exponent:
								_lowerCamelCase     :			List[str]    =    from_exponent - to_exponent
				else:
								_lowerCamelCase     :			List[Any]    =    -(to_exponent - from_exponent)

				return value * pow(10							,    lowercase__		)


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

			testmod()