



'''simple docstring'''





import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


_lowerCAmelCase      						=	logging.getLogger(__name__)






@dataclass
class        lowerCAmelCase_(				SCREAMING_SNAKE_CASE_     ):
  '''simple docstring'''




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







'''simple docstring'''


import warnings

from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor


_lowerCamelCase	:       str      	=	logging.get_logger(__name__)

class  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""





    def __init__(  self      :					Dict  ,						*UpperCamelCase__      :					List[Any]  ,						**UpperCamelCase__      :					List[Any] ):


       """simple docstring"""







       warnings.warn(
           'The class ChineseCLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
           ' Please use ChineseCLIPImageProcessor instead.'  ,						UpperCamelCase__  ,						)
       super().__init__(*UpperCamelCase__  ,						**UpperCamelCase__ )

