




"""simple docstring"""

# Function to print upper half of diamond (pyramid)






def 						_snake_case					( _snake_case							: Union[str, Any]							)   -> Optional[int]:






      '''simple docstring'''


      for i in range(0    ,  _snake_case							):
            for _ in range(0    ,  n - i - 1							):  # printing spaces
                  print(' '    ,  end=''							)
            for _ in range(0    ,  i + 1							):  # printing stars
                  print('* '    ,  end=''							)
            print()






def 						_snake_case					( _snake_case							: Union[str, Any]							)   -> Union[str, Any]:






      '''simple docstring'''


      for i in range(_snake_case    ,  0    ,  -1							):
            for _ in range(_snake_case    ,  0    ,  -1							):  # printing stars
                  print('* '    ,  end=''							)
            print()
            for _ in range(n - i + 1    ,  0    ,  -1							):  # printing spaces
                  print(' '    ,  end=''							)






def 						_snake_case					( _snake_case							: Optional[Any]							)   -> Union[str, Any]:






      '''simple docstring'''


      if n <= 0:
            print('       ...       ....        nothing printing :('							)
            return
      floyd(_snake_case							)  # upper half
      reverse_floyd(_snake_case							)  # lower half


if __name__ == "__main__":
       print(r'''| /\ | |- |  |-  |--| |\  /| |-''')
       print(r'''|/  \| |- |_ |_  |__| | \/ | |_''')
       a         =      1
       while K:
              a         =      int(input('''enter the number and , and see the magic : '''))
              print()
              pretty_print(user_number)
              a         =      int(input('''press 0 to exit... and 1 to continue...'''))

       print('''Good Bye...''')







"""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         =      logging.getLogger(__name__)





@dataclass
@add_start_docstrings(TrainingArguments.__doc__							)
class     lowercase_	(					__lowerCAmelCase							):



 '''simple docstring'''
 UpperCAmelCase   :					bool				  =     field(default=__lowerCAmelCase      ,     metadata={'''help''': '''Whether to use SortishSampler or not.'''}							)
 UpperCAmelCase   :					bool				  =     field(
     default=__lowerCAmelCase      ,     metadata={'''help''': '''Whether to use generate to calculate generative metrics (ROUGE, BLEU).'''}							)
 UpperCAmelCase   :					Optional[int]				  =     field(
     default=__lowerCAmelCase      ,     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   :					Optional[int]				  =     field(
     default=__lowerCAmelCase      ,     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   :					Optional[Union[str, Path, GenerationConfig]]				  =     field(
     default=__lowerCAmelCase      ,     metadata={
         '''help''': '''Model id, file path or url pointing to a GenerationConfig json file, to use during prediction.'''
     }      ,     )

 def       lowerCAmelCase_							(			self	:	int		):
       _A        =       super().to_dict()
       for k, v in d.items():
             if isinstance(_UpperCAmelCase   ,							_UpperCAmelCase		):
                   _A        =       v.to_dict()
       return d

