


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


__a	 =      logging.get_logger(__name__)

__a	 =      {
    """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					(	__A	):
      UpperCamelCase										=							'''luke'''





      def __init__(		self    :       Any       ,							__lowerCamelCase    :       Union[str, Any]=5_0_2_6_7       ,							__lowerCamelCase    :       str=5_0_0_0_0_0       ,							__lowerCamelCase    :       str=7_6_8       ,							__lowerCamelCase    :       Any=2_5_6       ,							__lowerCamelCase    :       Optional[Any]=1_2       ,							__lowerCamelCase    :       Union[str, Any]=1_2       ,							__lowerCamelCase    :       Optional[Any]=3_0_7_2       ,							__lowerCamelCase    :       Optional[Any]="gelu"       ,							__lowerCamelCase    :       Optional[Any]=0.1       ,							__lowerCamelCase    :       Any=0.1       ,							__lowerCamelCase    :       List[Any]=5_1_2       ,							__lowerCamelCase    :       List[Any]=2       ,							__lowerCamelCase    :       Tuple=0.02       ,							__lowerCamelCase    :       Optional[Any]=1e-1_2       ,							__lowerCamelCase    :       Union[str, Any]=True       ,							__lowerCamelCase    :       str=None       ,							__lowerCamelCase    :       Tuple=1       ,							__lowerCamelCase    :       Optional[int]=0       ,							__lowerCamelCase    :       List[str]=2       ,							**__lowerCamelCase    :       Tuple       ,							)     -> List[Any]:






         """simple docstring"""







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

         UpperCAmelCase      					=  vocab_size
         UpperCAmelCase      					=  entity_vocab_size
         UpperCAmelCase      					=  hidden_size
         UpperCAmelCase      					=  entity_emb_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      					=  use_entity_aware_attention
         UpperCAmelCase      					=  classifier_dropout











'''simple docstring'''



import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class UpperCAmelCase_       (     __A					):




      """simple docstring"""




      UpperCamelCase_             =      ComputeEnvironment.AMAZON_SAGEMAKER
      UpperCamelCase_             =      True
      UpperCamelCase_             =      '''ml.p3.2xlarge'''
      UpperCamelCase_             =      '''accelerate_sagemaker_execution_role'''
      UpperCamelCase_             =      '''hf-sm'''
      UpperCamelCase_             =      '''us-east-1'''
      UpperCamelCase_             =      1
      UpperCamelCase_             =      '''accelerate-sagemaker-1'''
      UpperCamelCase_             =      '''1.6'''
      UpperCamelCase_             =      '''4.4'''
      UpperCamelCase_             =      '''train.py'''
      UpperCamelCase_             =      [
          '''--model_name_or_path''',
          '''bert''',
          '''--do_train''',
          '''False''',
          '''--epochs''',
          '''3''',
          '''--learning_rate''',
          '''5e-5''',
          '''--max_steps''',
          '''50.5''',
      ]
      UpperCamelCase_             =      [
          '''--model_name_or_path''',
          '''bert''',
          '''--do_train''',
          '''--do_test''',
          '''False''',
          '''--do_predict''',
          '''--epochs''',
          '''3''',
          '''--learning_rate''',
          '''5e-5''',
          '''--max_steps''',
          '''50.5''',
      ]





class UpperCAmelCase_       (     unittest.TestCase					):




      """simple docstring"""




      def 					A__   (			self      :		int		)	->	Dict:


       '''simple docstring'''

       lowercase       : str						=_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args		)
       assert isinstance(converted_args['''model_name_or_path''']  ,   UpperCAmelCase		)
       assert isinstance(converted_args['''do_train''']  ,   UpperCAmelCase		)
       assert isinstance(converted_args['''epochs''']  ,   UpperCAmelCase		)
       assert isinstance(converted_args['''learning_rate''']  ,   UpperCAmelCase		)
       assert isinstance(converted_args['''max_steps''']  ,   UpperCAmelCase		)

       with pytest.raises(UpperCAmelCase		):
        _convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args		)



