'''simple docstring'''




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


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






@dataclass
@add_start_docstrings(TrainingArguments.__doc__   )
class 		__A       (__magic_name__   ):
       snake_case       :bool				    =					field(default=__magic_name__ ,					metadata={"help": "Whether to use SortishSampler or not."}   )
       snake_case       :bool				    =					field(
           default=__magic_name__ ,					metadata={"help": "Whether to use generate to calculate generative metrics (ROUGE, BLEU)."}   )
       snake_case       :Optional[int]				    =					field(
           default=__magic_name__ ,					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."
               )
           } ,					)
       snake_case       :Optional[int]				    =					field(
           default=__magic_name__ ,					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."
               )
           } ,					)
       snake_case       :Optional[Union[str, Path, GenerationConfig]]				    =					field(
           default=__magic_name__ ,					metadata={
               "help": "Model id, file path or url pointing to a GenerationConfig json file, to use during prediction."
           } ,					)






       def 			_snake_case						(      self      ):
              __UpperCAmelCase  :				Any       				=		super().to_dict()
              for k, v in d.items():
                     if isinstance(UpperCamelCase_				,     UpperCamelCase_      ):
                            __UpperCAmelCase  :				Tuple       				=		v.to_dict()
              return d







'''simple docstring'''




def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__						)					->       bool:





       """simple docstring"""


       return not any(
           neighbour == 1 and colored_vertices[i] == color
           for i, neighbour in enumerate(lowerCamelCase__						)						)

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__						)					->       bool:





       """simple docstring"""


       if index == len(lowerCamelCase__						):
              return True

       # Recursive Step
       for i in range(lowerCamelCase__						):
              if valid_coloring(graph[index]							,    lowerCamelCase__							,    lowerCamelCase__						):
                     # Color current vertex
                     __UpperCAmelCase  :				List[str]       				=		i
                     # Validate coloring
                     if util_color(lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    index + 1						):
                            return True
                     # Backtrack
                     __UpperCAmelCase  :				Any       				=		-1
       return False


def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__						)					->       list[int]:





       """simple docstring"""


       __UpperCAmelCase  :				Optional[Any]       				=		[-1] * len(lowerCamelCase__						)

       if util_color(lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    0						):
              return colored_vertices

       return []






