





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

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


__lowerCamelCase       :     Optional[Any]   =     logging.getLogger(__name__)



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







from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCamelCase       :     Optional[int]   =     {"""configuration_mmbt""": ["""MMBTConfig"""]}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase       :     List[Any]   =     ["""MMBTForClassification""", """MMBTModel""", """ModalEmbeddings"""]


if TYPE_CHECKING:
    from .configuration_mmbt import MMBTConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mmbt import MMBTForClassification, MMBTModel, ModalEmbeddings

else:
    import sys

    __lowerCamelCase       :     int   =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
