




"""simple docstring"""

import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment

@require_huggingface_suite
class        lowercase      (    unittest.TestCase):







				def 					a_  (							self   :					Optional[int]       ):



					"""simple docstring"""

					A_  :				Union[str, Any]	   =		inspect.getfile(accelerate.test_utils       )
					A_  :				int	   =		os.path.sep.join(
					    mod_file.split(os.path.sep       )[:-1] + ['''scripts''', '''external_deps''', '''test_metrics.py''']       )

					from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

					A_  :				List[str]	   =		test_metrics







				@require_cpu
				def 					a_  (							self   :					Tuple       ):



					"""simple docstring"""

					debug_launcher(self.test_metrics.main      ,     num_processes=1       )







				@require_cpu
				def 					a_  (							self   :					Optional[int]       ):



					"""simple docstring"""

					debug_launcher(self.test_metrics.main       )







				@require_single_gpu
				def 					a_  (							self   :					Tuple       ):



					"""simple docstring"""

					self.test_metrics.main()







				@require_multi_gpu
				def 					a_  (							self   :					int       ):



					"""simple docstring"""

					print(F"""Found {torch.cuda.device_count()} devices."""       )
					A_  :				Union[str, Any]	   =		['''torchrun''', F"""--nproc_per_node={torch.cuda.device_count()}""", self.test_file_path]
					with patch_environment(omp_num_threads=1       ):
						execute_subprocess_async(_lowerCamelCase      ,     env=os.environ.copy()       )










"""simple docstring"""

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


_lowerCamelCase  :			Optional[Any]        =       logging.get_logger(__name__)

_lowerCamelCase  :			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        lowercase      (    __UpperCAmelCase):
				__lowerCAmelCase    :    Any         =   """luke"""







				def __init__(							self   :					List[str]      ,     _lowerCamelCase   :					Union[str, Any]=5_02_67      ,     _lowerCamelCase   :					Tuple=50_00_00      ,     _lowerCamelCase   :					int=7_68      ,     _lowerCamelCase   :					Union[str, Any]=2_56      ,     _lowerCamelCase   :					Dict=12      ,     _lowerCamelCase   :					str=12      ,     _lowerCamelCase   :					Dict=30_72      ,     _lowerCamelCase   :					Union[str, Any]="gelu"      ,     _lowerCamelCase   :					Optional[int]=0.1      ,     _lowerCamelCase   :					str=0.1      ,     _lowerCamelCase   :					Union[str, Any]=5_12      ,     _lowerCamelCase   :					int=2      ,     _lowerCamelCase   :					Optional[int]=0.02      ,     _lowerCamelCase   :					int=1E-12      ,     _lowerCamelCase   :					List[str]=True      ,     _lowerCamelCase   :					str=None      ,     _lowerCamelCase   :					Union[str, Any]=1      ,     _lowerCamelCase   :					str=0      ,     _lowerCamelCase   :					Dict=2      ,     **_lowerCamelCase   :					Optional[int]      ,     ):



					"""simple docstring"""

					super().__init__(pad_token_id=_lowerCamelCase      ,     bos_token_id=_lowerCamelCase      ,     eos_token_id=_lowerCamelCase      ,     **_lowerCamelCase       )

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





