
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


SCREAMING_SNAKE_CASE_					     =	logging.getLogger(__name__)
@dataclass
class       lowerCAmelCase_		(				A__ ):



							'''simple docstring'''





							_snake_case						      =		field(
							    default=0.0				,				metadata={'''help''': '''The label smoothing epsilon to apply (if not zero).'''} )
							_snake_case						      =		field(default=A__				,				metadata={'''help''': '''Whether to SortishSamler or not.'''} )
							_snake_case						      =		field(
							    default=A__				,				metadata={'''help''': '''Whether to use generate to calculate generative metrics (ROUGE, BLEU).'''} )
							_snake_case						      =		field(default=A__				,				metadata={'''help''': '''whether to use adafactor'''} )
							_snake_case						      =		field(
							    default=A__				,				metadata={'''help''': '''Encoder layer dropout probability. Goes into model.config.'''} )
							_snake_case						      =		field(
							    default=A__				,				metadata={'''help''': '''Decoder layer dropout probability. Goes into model.config.'''} )
							_snake_case						      =		field(default=A__				,				metadata={'''help''': '''Dropout probability. Goes into model.config.'''} )
							_snake_case						      =		field(
							    default=A__				,				metadata={'''help''': '''Attention dropout probability. Goes into model.config.'''} )
							_snake_case						      =		field(
							    default='''linear'''				,				metadata={'''help''': F"""Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys() )}"""}				,				)


"""simple docstring"""
import warnings

from ..trainer import Trainer
from ..utils import logging


SCREAMING_SNAKE_CASE_					     =	logging.get_logger(__name__)
class       lowerCAmelCase_		(				A__ ):



							'''simple docstring'''





							def __init__( self    ,				snake_case_=None    ,				**snake_case_				)       ->  Optional[Any]:
													warnings.warn(
													    """`SageMakerTrainer` is deprecated and will be removed in v5 of Transformers. You can use `Trainer` """
													    """instead."""    ,				snake_case_    ,				)
													super().__init__(args=snake_case_    ,				**snake_case_				)
