

import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union

from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings


lowercase_									=   logging.getLogger(__name__)





@dataclass
@add_start_docstrings(TrainingArguments.__doc__							)
class  __lowerCAmelCase     (					SCREAMING_SNAKE_CASE							):
  _a									=  field(default=SCREAMING_SNAKE_CASE			,			metadata={"""help""": """Whether to use SortishSampler or not."""}							)
  _a									=  field(
      default=SCREAMING_SNAKE_CASE			,			metadata={"""help""": """Whether to use generate to calculate generative metrics (ROUGE, BLEU)."""}							)
  _a									=  field(
      default=SCREAMING_SNAKE_CASE			,			metadata={
          """help""": (
              """The `max_length` to use on each evaluation loop when `predict_with_generate=True`. Will default """
              """to the `max_length` value of the model configuration."""
          )
      }			,			)
  _a									=  field(
      default=SCREAMING_SNAKE_CASE			,			metadata={
          """help""": (
              """The `num_beams` to use on each evaluation loop when `predict_with_generate=True`. Will default """
              """to the `num_beams` value of the model configuration."""
          )
      }			,			)
  _a									=  field(
      default=SCREAMING_SNAKE_CASE			,			metadata={
          """help""": """Model id, file path or url pointing to a GenerationConfig json file, to use during prediction."""
      }			,			)




  def   A__     (				self					)  -> Optional[int]:
        '''simple docstring'''






        _lowercase	       =super().to_dict()
        for k, v in d.items():
              if isinstance(lowerCAmelCase							,   lowerCAmelCase					):
                    _lowercase	       =v.to_dict()
        return d





from .imports import is_tqdm_available


if is_tqdm_available():
  from tqdm.auto import tqdm as _tqdm

from ..state import PartialState
def      a      (			A__	:   bool = True      ,   *A__	:   int      ,   **A__	:   Union[str, Any]     )    ->      List[str]:





      """simple docstring"""



      if not is_tqdm_available():
            raise ImportError('Accelerate\'s `tqdm` module requires `tqdm` to be installed. Please run `pip install tqdm`.'     )
      _lowercase	       =False
      if main_process_only:
            _lowercase	       =PartialState().local_process_index == 0
      return _tqdm(*A__      ,   **A__      ,   disable=A__     )


