





"""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__						):
							lowerCamelCase   :					List[str]      					=ComputeEnvironment.AMAZON_SAGEMAKER
							lowerCamelCase   :					str      					=True
							lowerCamelCase   :					Union[str, Any]      					="""ml.p3.2xlarge"""
							lowerCamelCase   :					str      					="""accelerate_sagemaker_execution_role"""
							lowerCamelCase   :					int      					="""hf-sm"""
							lowerCamelCase   :					int      					="""us-east-1"""
							lowerCamelCase   :					Tuple      					=1
							lowerCamelCase   :					Any      					="""accelerate-sagemaker-1"""
							lowerCamelCase   :					str      					="""1.6"""
							lowerCamelCase   :					Tuple      					="""4.4"""
							lowerCamelCase   :					Optional[int]      					="""train.py"""
							lowerCamelCase   :					Optional[Any]      					=[
							    """--model_name_or_path""",
							    """bert""",
							    """--do_train""",
							    """False""",
							    """--epochs""",
							    """3""",
							    """--learning_rate""",
							    """5e-5""",
							    """--max_steps""",
							    """50.5""",
							]
							lowerCamelCase   :					Union[str, Any]      					=[
							    """--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						):






							def     __a   (   self      )	-> List[str]:
								# If no defaults are changed, `to_kwargs` returns an empty dict.
								a      :		str	=				_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args      )
								assert isinstance(converted_args["model_name_or_path"]      ,					lowerCAmelCase__      )
								assert isinstance(converted_args["do_train"]      ,					lowerCAmelCase__      )
								assert isinstance(converted_args["epochs"]      ,					lowerCAmelCase__      )
								assert isinstance(converted_args["learning_rate"]      ,					lowerCAmelCase__      )
								assert isinstance(converted_args["max_steps"]      ,					lowerCAmelCase__      )

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



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


_SCREAMING_SNAKE_CASE										=						logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE										=						{
    'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}



class 				a							(			__lowerCAmelCase       ):







 """simple docstring"""






 lowerCamelCase	:Any    			=		'''biogpt'''



 def __init__(					self		,				lowerCAmelCase_=4_23_84		,				lowerCAmelCase_=10_24		,				lowerCAmelCase_=24		,				lowerCAmelCase_=16		,				lowerCAmelCase_=40_96		,				lowerCAmelCase_="gelu"		,				lowerCAmelCase_=0.1		,				lowerCAmelCase_=0.1		,				lowerCAmelCase_=10_24		,				lowerCAmelCase_=0.02		,				lowerCAmelCase_=1E-12		,				lowerCAmelCase_=True		,				lowerCAmelCase_=True		,				lowerCAmelCase_=0.0		,				lowerCAmelCase_=0.0		,				lowerCAmelCase_=1		,				lowerCAmelCase_=0		,				lowerCAmelCase_=2		,				**lowerCAmelCase_		,				)  ->					Tuple:
        _A        =  vocab_size
        _A        =  max_position_embeddings
        _A        =  hidden_size
        _A        =  num_hidden_layers
        _A        =  num_attention_heads
        _A        =  intermediate_size
        _A        =  hidden_act
        _A        =  hidden_dropout_prob
        _A        =  attention_probs_dropout_prob
        _A        =  initializer_range
        _A        =  layer_norm_eps
        _A        =  scale_embedding
        _A        =  use_cache
        _A        =  layerdrop
        _A        =  activation_dropout
        super().__init__(pad_token_id=lowerCAmelCase_		,				bos_token_id=lowerCAmelCase_		,				eos_token_id=lowerCAmelCase_		,				**lowerCAmelCase_							)




