





from ..utils import DummyObject, requires_backends

class 		UpperCamelCase__ (      metaclass=lowerCAmelCase_   ):



     '''simple docstring'''

     __snake_case    :	List[str]			=			["note_seq"]






     def __init__(							self						:    Dict						,*lowerCamelCase__						:    Tuple						,**lowerCamelCase__						:    Union[str, Any]       )     ->		Optional[int]:




           '''simple docstring'''


           requires_backends(self						,["""note_seq"""]       )






     @classmethod
     def 				SCREAMING_SNAKE_CASE__  (							cls						:    Union[str, Any]						,*lowerCamelCase__						:    List[Any]						,**lowerCamelCase__						:    Dict       )     ->		Optional[Any]:




           '''simple docstring'''


           requires_backends(cls						,["""note_seq"""]       )






     @classmethod
     def 				SCREAMING_SNAKE_CASE__  (							cls						:    int						,*lowerCamelCase__						:    str						,**lowerCamelCase__						:    str       )     ->		Optional[Any]:




           '''simple docstring'''


           requires_backends(cls						,["""note_seq"""]       )









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 		UpperCamelCase__ (      lowerCAmelCase_   ):



     '''simple docstring'''

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


