





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowerCamelCase :    int  							= logging.get_logger(__name__)

_lowerCamelCase :    str  							= {
    '''facebook/xmod-base''': '''https://huggingface.co/facebook/xmod-base/resolve/main/config.json''',
    '''facebook/xmod-large-prenorm''': '''https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json''',
    '''facebook/xmod-base-13-125k''': '''https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json''',
    '''facebook/xmod-base-30-125k''': '''https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json''',
    '''facebook/xmod-base-30-195k''': '''https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json''',
    '''facebook/xmod-base-60-125k''': '''https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json''',
    '''facebook/xmod-base-60-265k''': '''https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json''',
    '''facebook/xmod-base-75-125k''': '''https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json''',
    '''facebook/xmod-base-75-269k''': '''https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json''',
}


class 						lowerCamelCase       (__lowerCamelCase      ):







							"""simple docstring"""




							UpperCAmelCase_      						=   "xmod"






							def __init__( self     :					List[str],			_UpperCAmelCase     :					Dict=3_0_5_2_2,			_UpperCAmelCase     :					List[str]=7_6_8,			_UpperCAmelCase     :					Union[str, Any]=1_2,			_UpperCAmelCase     :					Tuple=1_2,			_UpperCAmelCase     :					List[Any]=3_0_7_2,			_UpperCAmelCase     :					List[str]="gelu",			_UpperCAmelCase     :					List[str]=0.1,			_UpperCAmelCase     :					Dict=0.1,			_UpperCAmelCase     :					Optional[Any]=5_1_2,			_UpperCAmelCase     :					List[Any]=2,			_UpperCAmelCase     :					Union[str, Any]=0.02,			_UpperCAmelCase     :					int=1E-12,			_UpperCAmelCase     :					str=1,			_UpperCAmelCase     :					Optional[int]=0,			_UpperCAmelCase     :					Optional[int]=2,			_UpperCAmelCase     :					Dict="absolute",			_UpperCAmelCase     :					int=True,			_UpperCAmelCase     :					Optional[int]=None,			_UpperCAmelCase     :					Tuple=False,			_UpperCAmelCase     :					Any=2,			_UpperCAmelCase     :					Tuple=False,			_UpperCAmelCase     :					int=True,			_UpperCAmelCase     :					List[Any]=True,			_UpperCAmelCase     :					Union[str, Any]=("en_XX",),			_UpperCAmelCase     :					List[str]=None,			**_UpperCAmelCase     :					List[Any],			)				->			List[str]:





														"""simple docstring"""
														super().__init__(pad_token_id=_UpperCAmelCase,			bos_token_id=_UpperCAmelCase,			eos_token_id=_UpperCAmelCase,			**_UpperCAmelCase						)

														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						vocab_size
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						hidden_size
														SCREAMING_SNAKE_CASE__       :      Any     =						num_hidden_layers
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						num_attention_heads
														SCREAMING_SNAKE_CASE__       :      List[str]     =						hidden_act
														SCREAMING_SNAKE_CASE__       :      Tuple     =						intermediate_size
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						hidden_dropout_prob
														SCREAMING_SNAKE_CASE__       :      Any     =						attention_probs_dropout_prob
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						max_position_embeddings
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						type_vocab_size
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						initializer_range
														SCREAMING_SNAKE_CASE__       :      Tuple     =						layer_norm_eps
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						position_embedding_type
														SCREAMING_SNAKE_CASE__       :      Tuple     =						use_cache
														SCREAMING_SNAKE_CASE__       :      str     =						classifier_dropout
														SCREAMING_SNAKE_CASE__       :      Any     =						pre_norm
														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						adapter_reduction_factor
														SCREAMING_SNAKE_CASE__       :      List[str]     =						adapter_layer_norm
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						adapter_reuse_layer_norm
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						ln_before_adapter
														SCREAMING_SNAKE_CASE__       :      List[str]     =						list(_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      Tuple     =						default_language


class 						lowerCamelCase       (__lowerCamelCase      ):







							"""simple docstring"""




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





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













def _a (  SCREAMING_SNAKE_CASE__      :  int       )	->    str:

							'''simple docstring'''






							if isinstance(SCREAMING_SNAKE_CASE__			,				SCREAMING_SNAKE_CASE__       ):
														raise TypeError("'float' object cannot be interpreted as an integer"       )
							if isinstance(SCREAMING_SNAKE_CASE__			,				SCREAMING_SNAKE_CASE__       ):
														raise TypeError("'str' object cannot be interpreted as an integer"       )

							if num == 0:
														return "0b0"

							SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						False

							if num < 0:
														SCREAMING_SNAKE_CASE__       :      Any     =						True
														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						-num

							SCREAMING_SNAKE_CASE__       :      list[int]     =						[]
							while num > 0:
														binary.insert(0			,				num % 2       )
														num >>= 1

							if negative:
														return "-0b" + "".join(str(SCREAMING_SNAKE_CASE__       ) for e in binary       )

							return "0b" + "".join(str(SCREAMING_SNAKE_CASE__       ) for e in binary       )


if __name__ == "__main__":
		import doctest

		doctest.testmod()






