
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						      =				logging.getLogger(__name__)







@dataclass
@add_start_docstrings(TrainingArguments.__doc__						)
class   lowerCamelCase	(						__A						):
     UpperCAmelCase__       :							Optional[int]     =	field(default=__A							,				metadata={"help": "Whether to use SortishSampler or not."}						)
     UpperCAmelCase__       :							Dict     =	field(
         default=__A							,				metadata={"help": "Whether to use generate to calculate generative metrics (ROUGE, BLEU)."}						)
     UpperCAmelCase__       :							Dict     =	field(
         default=__A							,				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."
             )
         }							,				)
     UpperCAmelCase__       :							List[Any]     =	field(
         default=__A							,				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."
             )
         }							,				)
     UpperCAmelCase__       :							Tuple     =	field(
         default=__A							,				metadata={
             "help": "Model id, file path or url pointing to a GenerationConfig json file, to use during prediction."
         }							,				)





     def 	UpperCAmelCase(self   :					Union[str, Any]     )		->		Dict:
         snake_case				  =      super().to_dict()
         for k, v in d.items():
             if isinstance(_A       ,					_A     ):
                 snake_case				  =      v.to_dict()
         return d



def 		lowercase_    (     A__ = 1000	)							->							int:
    """simple docstring"""

    snake_case				  =      -1
    snake_case				  =      0
    for a in range(1				,	n // 3	):
        # Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
        snake_case				  =      (n * n - 2 * a * n) // (2 * n - 2 * a)
        snake_case				  =      n - a - b
        if c * c == (a * a + b * b):
            snake_case				  =      a * b * c
            if candidate >= product:
                snake_case				  =      candidate
    return product


if __name__ == "__main__":
   print(f"{solution() = }")

