
'''simple docstring'''
from pathlib import Path

import fire
from tqdm import tqdm






def  __SCREAMING_SNAKE_CASE				(  _SCREAMING_SNAKE_CASE="ro"							, _SCREAMING_SNAKE_CASE="en"							, _SCREAMING_SNAKE_CASE="wmt16"							, _SCREAMING_SNAKE_CASE=None				):
							try:
														import datasets
							except (ModuleNotFoundError, ImportError):
														raise ImportError("""run pip install datasets"""				)
							_snake_case       =  f"""{src_lang}-{tgt_lang}"""
							print(f"""Converting {dataset}-{pair}"""				)
							_snake_case       =  datasets.load_dataset(__lowerCAmelCase							, __lowerCAmelCase				)
							if save_dir is None:
														_snake_case       =  f"""{dataset}-{pair}"""
							_snake_case       =  Path(__lowerCAmelCase				)
							save_dir.mkdir(exist_ok=__lowerCAmelCase				)

							for split in ds.keys():
														print(f"""Splitting {split} with {ds[split].num_rows} records"""				)

														# to save to val.source, val.target like summary datasets
														_snake_case       =  """val""" if split == """validation""" else split
														_snake_case       =  save_dir.joinpath(f"""{fn}.source"""				)
														_snake_case       =  save_dir.joinpath(f"""{fn}.target"""				)
														_snake_case       =  src_path.open("""w+"""				)
														_snake_case       =  tgt_path.open("""w+"""				)

														# reader is the bottleneck so writing one record at a time doesn't slow things down
														for x in tqdm(ds[split]				):
																					_snake_case       =  x["""translation"""]
																					src_fp.write(ex[src_lang] + """\n"""				)
																					tgt_fp.write(ex[tgt_lang] + """\n"""				)

							print(f"""Saved {dataset} dataset to {save_dir}"""				)


if __name__ == "__main__":
				fire.Fire(download_wmt_dataset)

'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey


class       _lowerCAmelCase   :







							'''simple docstring'''

							def __init__(self  ,  UpperCAmelCase  ,  UpperCAmelCase  ,  UpperCAmelCase  )					->       List[str]:
														if dst_width < 0 or dst_height < 0:
																					raise ValueError("""Destination width/height should be > 0"""  )

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

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

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

							def 	lowercase							(self  )					->       List[Any]:
														for i in range(self.dst_h  ):
																					for j in range(self.dst_w  ):
																												_snake_case       =  self.img[self.get_y(UpperCAmelCase  )][self.get_x(UpperCAmelCase  )]

							def 	lowercase							(self  ,  UpperCAmelCase  )					->       int:
														return int(self.ratio_x * x  )





							def 	lowercase							(self  ,  UpperCAmelCase  )					->       int:
														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()