



import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey






class    SCREAMING_SNAKE_CASE			:





       def __init__(   self		:		Any      ,				__lowercase		:		Union[str, Any]      ,				__lowercase		:		Union[str, Any]      ,				__lowercase		:		str	):

           '''simple docstring'''
           if dst_width < 0 or dst_height < 0:
               raise ValueError("""Destination width/height should be > 0"""	)

           __a       =		img
           __a       =		img.shape[1]
           __a       =		img.shape[0]
           __a       =		dst_width
           __a       =		dst_height

           __a       =		self.src_w / self.dst_w
           __a       =		self.src_h / self.dst_h

           __a       =		__a       =		(
               np.ones((self.dst_h, self.dst_w, 3)      ,				np.uinta	) * 255
           )





       def 						UpperCamelCase_					(   self		:		List[Any]	):

           '''simple docstring'''
           for i in range(self.dst_h	):
               for j in range(self.dst_w	):
                   __a       =		self.img[self.get_y(__lowercase	)][self.get_x(__lowercase	)]





       def 						UpperCamelCase_					(   self		:		Union[str, Any]      ,				__lowercase		:		Tuple	):

           '''simple docstring'''
           return int(self.ratio_x * x	)







       def 						UpperCamelCase_					(   self		:		int      ,				__lowercase		:		int	):

           '''simple docstring'''
           return int(self.ratio_y * y	)


if __name__ == "__main__":
      lowerCamelCase__			,							lowerCamelCase__			= 800, 600
      lowerCamelCase__			= imread("""image_data/lena.jpg""", 1)
      lowerCamelCase__			= NearestNeighbour(im, dst_w, dst_h)
      n.process()

      imshow(
          F"""Image resized from: {im.shape[1]}x{im.shape[0]} to {dst_w}x{dst_h}""", n.output
      )
      waitKey(0)
      destroyAllWindows()





import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict






@dataclass
class    SCREAMING_SNAKE_CASE			(							lowerCamelCase__					):
							__lowerCamelCase	:	List[Any]    =ComputeEnvironment.AMAZON_SAGEMAKER
							__lowerCamelCase	:	Optional[int]    =True
							__lowerCamelCase	:	List[Any]    ='ml.p3.2xlarge'
							__lowerCamelCase	:	Optional[int]    ='accelerate_sagemaker_execution_role'
							__lowerCamelCase	:	Optional[Any]    ='hf-sm'
							__lowerCamelCase	:	Any    ='us-east-1'
							__lowerCamelCase	:	Any    =1
							__lowerCamelCase	:	List[str]    ='accelerate-sagemaker-1'
							__lowerCamelCase	:	Union[str, Any]    ='1.6'
							__lowerCamelCase	:	str    ='4.4'
							__lowerCamelCase	:	List[str]    ='train.py'
							__lowerCamelCase	:	List[Any]    =[
							    '--model_name_or_path',
							    'bert',
							    '--do_train',
							    'False',
							    '--epochs',
							    '3',
							    '--learning_rate',
							    '5e-5',
							    '--max_steps',
							    '50.5',
							]
							__lowerCamelCase	:	Tuple    =[
							    '--model_name_or_path',
							    'bert',
							    '--do_train',
							    '--do_test',
							    'False',
							    '--do_predict',
							    '--epochs',
							    '3',
							    '--learning_rate',
							    '5e-5',
							    '--max_steps',
							    '50.5',
							]






class    SCREAMING_SNAKE_CASE			(							unittest.TestCase					):





							def 						UpperCamelCase_					(   self		:		Union[str, Any]	):

											'''simple docstring'''
											# If no defaults are changed, `to_kwargs` returns an empty dict.
											__a       =		_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args	)
											assert isinstance(converted_args["""model_name_or_path"""]      ,				__lowercase	)
											assert isinstance(converted_args["""do_train"""]      ,				__lowercase	)
											assert isinstance(converted_args["""epochs"""]      ,				__lowercase	)
											assert isinstance(converted_args["""learning_rate"""]      ,				__lowercase	)
											assert isinstance(converted_args["""max_steps"""]      ,				__lowercase	)

											with pytest.raises(__lowercase	):
															_convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args	)
