


'''simple docstring'''






from dataclasses import dataclass, field
from typing import Tuple

from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments


if is_torch_available():
							import torch

if is_torch_tpu_available(check_device=False):
							import torch_xla.core.xla_model as xm


__A	:	List[Any]     =     logging.get_logger(__name__)
@dataclass
class 						__UpperCamelCase	(						snake_case__							):
							lowercase			:		Any   		=  [
							    'no_inference',
							    'no_cuda',
							    'no_tpu',
							    'no_speed',
							    'no_memory',
							    'no_env_print',
							    'no_multi_process',
							]





							def __init__(  self		:Optional[Any]  ,**_UpperCamelCase		:str			):
									for deprecated_arg in self.deprecated_args:
											if deprecated_arg in kwargs:
													snake_case_		:							Optional[Any]			       =						deprecated_arg[3:]
													setattr(self  ,lowercase_  ,not kwargs.pop(lowercase_			)			)
													logger.warning(
													    F'''{deprecated_arg} is depreciated. Please use --no_{positive_arg} or'''
													    F''' {positive_arg}={kwargs[positive_arg]}'''			)

									snake_case_		:							List[str]			       =						kwargs.pop("""torchscript"""  ,self.torchscript			)
									snake_case_		:							List[str]			       =						kwargs.pop("""torch_xla_tpu_print_metrics"""  ,self.torch_xla_tpu_print_metrics			)
									snake_case_		:							Optional[int]			       =						kwargs.pop("""fp16_opt_level"""  ,self.fpaa_opt_level			)
									super().__init__(**lowercase_			)

							lowercase			:		str   		=  field(default=snake_case__						,  metadata={'help': 'Trace the models using torchscript'}							)
							lowercase			:		Dict   		=  field(default=snake_case__						,  metadata={'help': 'Print Xla/PyTorch tpu metrics'}							)
							lowercase			:		List[str]   		=  field(
							    default='O1'						,  metadata={
							        'help': (
							            'For fp16: Apex AMP optimization level selected in [\'O0\', \'O1\', \'O2\', and \'O3\']. '
							            'See details at https://nvidia.github.io/apex/amp.html'
							        )
							    }						,  )





							@cached_property
							def 		a__   (  self		:Optional[Any]			):
									requires_backends(self  ,["""torch"""]			)
									logger.info("""PyTorch: setting up devices"""			)
									if not self.cuda:
											snake_case_		:							int			       =						torch.device("""cpu"""			)
											snake_case_		:							Union[str, Any]			       =						0
									elif is_torch_tpu_available():
											snake_case_		:							List[str]			       =						xm.xla_device()
											snake_case_		:							Tuple			       =						0
									else:
											snake_case_		:							Tuple			       =						torch.device("""cuda""" if torch.cuda.is_available() else """cpu"""			)
											snake_case_		:							Optional[int]			       =						torch.cuda.device_count()
									return device, n_gpu





							@property
							def 		a__   (  self		:str			):
									return is_torch_tpu_available() and self.tpu





							@property
							def 		a__   (  self		:Union[str, Any]			):
									requires_backends(self  ,["""torch"""]			)
									# TODO(PVP): currently only single GPU is supported
									return torch.cuda.current_device()





							@property
							def 		a__   (  self		:Dict			):
									requires_backends(self  ,["""torch"""]			)
									return self._setup_devices[0]





							@property
							def 		a__   (  self		:List[Any]			):
									requires_backends(self  ,["""torch"""]			)
									return self._setup_devices[1]





							@property
							def 		a__   (  self		:List[Any]			):
									return self.n_gpu > 0




'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import logging


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

__A	:	List[Any]     =     {
    'studio-ousia/luke-base': 'https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json',
    'studio-ousia/luke-large': 'https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json',
}
class 						__UpperCamelCase	(						lowercase__							):
							lowercase			:		Union[str, Any]   		=  'luke'





							def __init__(  self		:List[str]  ,_UpperCamelCase		:Tuple=5_0_2_6_7  ,_UpperCamelCase		:Tuple=5_0_0_0_0_0  ,_UpperCamelCase		:str=7_6_8  ,_UpperCamelCase		:List[Any]=2_5_6  ,_UpperCamelCase		:List[str]=1_2  ,_UpperCamelCase		:str=1_2  ,_UpperCamelCase		:Union[str, Any]=3_0_7_2  ,_UpperCamelCase		:int="gelu"  ,_UpperCamelCase		:int=0.1  ,_UpperCamelCase		:Dict=0.1  ,_UpperCamelCase		:Dict=5_1_2  ,_UpperCamelCase		:Optional[Any]=2  ,_UpperCamelCase		:int=0.02  ,_UpperCamelCase		:Any=1E-1_2  ,_UpperCamelCase		:Tuple=True  ,_UpperCamelCase		:Any=None  ,_UpperCamelCase		:Any=1  ,_UpperCamelCase		:int=0  ,_UpperCamelCase		:List[Any]=2  ,**_UpperCamelCase		:str  ,):
									super().__init__(pad_token_id=_UpperCamelCase  ,bos_token_id=_UpperCamelCase  ,eos_token_id=_UpperCamelCase  ,**_UpperCamelCase			)

									snake_case_		:							Any			       =						vocab_size
									snake_case_		:							List[Any]			       =						entity_vocab_size
									snake_case_		:							Optional[Any]			       =						hidden_size
									snake_case_		:							List[Any]			       =						entity_emb_size
									snake_case_		:							Dict			       =						num_hidden_layers
									snake_case_		:							Union[str, Any]			       =						num_attention_heads
									snake_case_		:							Dict			       =						hidden_act
									snake_case_		:							Dict			       =						intermediate_size
									snake_case_		:							Any			       =						hidden_dropout_prob
									snake_case_		:							List[Any]			       =						attention_probs_dropout_prob
									snake_case_		:							Optional[Any]			       =						max_position_embeddings
									snake_case_		:							Any			       =						type_vocab_size
									snake_case_		:							int			       =						initializer_range
									snake_case_		:							Union[str, Any]			       =						layer_norm_eps
									snake_case_		:							Tuple			       =						use_entity_aware_attention
									snake_case_		:							Tuple			       =						classifier_dropout