


import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer






def 							__lowercase   ( __lowerCAmelCase							:				str					,    __lowerCAmelCase							:				List[str]					,    __lowerCAmelCase							:				Any					,    __lowerCAmelCase							:				int=1_0_2_4   ):
							a__      ,					a__             =     [], []

							a__             =     list(zip(UpperCamelCase__					,    UpperCamelCase__   )   )
							a__      ,					a__             =     sorted_examples[0]

							def is_too_big(__lowerCAmelCase							:				Union[str, Any]   ):
														return tok(UpperCamelCase__					,    return_tensors='pt'   ).input_ids.shape[1] > max_tokens

							for src, tgt in tqdm(sorted_examples[1:]   ):
														a__             =     new_src + ' ' + src
														a__             =     new_tgt + ' ' + tgt
														if is_too_big(UpperCamelCase__   ) or is_too_big(UpperCamelCase__   ):  # cant fit, finalize example
																					finished_src.append(UpperCamelCase__   )
																					finished_tgt.append(UpperCamelCase__   )
																					a__      ,					a__             =     src, tgt
														else:  # can fit, keep adding
																					a__      ,					a__             =     cand_src, cand_tgt

    # cleanup
							if new_src:
														assert new_tgt
														finished_src.append(UpperCamelCase__   )
														finished_tgt.append(UpperCamelCase__   )
							return finished_src, finished_tgt






def 							__lowercase   ( __lowerCAmelCase							:				Union[str, Any]					,    __lowerCAmelCase							:				Optional[int]					,    __lowerCAmelCase							:				Tuple					,    __lowerCAmelCase							:				List[str]   ):
							a__             =     Path(UpperCamelCase__   )
							save_path.mkdir(exist_ok=UpperCamelCase__   )
							for split in ["train"]:
														a__      ,					a__             =     data_dir / F'{split}.source', data_dir / F'{split}.target'
														a__             =     [x.rstrip() for x in Path(UpperCamelCase__   ).open().readlines()]
														a__             =     [x.rstrip() for x in Path(UpperCamelCase__   ).open().readlines()]
														a__      ,					a__             =     pack_examples(UpperCamelCase__					,    UpperCamelCase__					,    UpperCamelCase__					,    UpperCamelCase__   )
														print(F'packed {split} split from {len(UpperCamelCase__   )} examples -> {len(UpperCamelCase__   )}.'   )
														Path(save_path / F'{split}.source'   ).open('w'   ).write('\n'.join(UpperCamelCase__   )   )
														Path(save_path / F'{split}.target'   ).open('w'   ).write('\n'.join(UpperCamelCase__   )   )
							for split in ["val", "test"]:
														a__      ,					a__             =     data_dir / F'{split}.source', data_dir / F'{split}.target'
														shutil.copyfile(UpperCamelCase__					,    save_path / F'{split}.source'   )
														shutil.copyfile(UpperCamelCase__					,    save_path / F'{split}.target'   )






def 							__lowercase   ( ):
							a__             =     argparse.ArgumentParser()
							parser.add_argument('--tok_name'					,    type=UpperCamelCase__					,    help='like facebook/bart-large-cnn,t5-base, etc.'   )
							parser.add_argument('--max_seq_len'					,    type=UpperCamelCase__					,    default=1_2_8   )
							parser.add_argument('--data_dir'					,    type=UpperCamelCase__   )
							parser.add_argument('--save_path'					,    type=UpperCamelCase__   )
							a__             =     parser.parse_args()
							a__             =     AutoTokenizer.from_pretrained(args.tok_name   )
							return pack_data_dir(UpperCamelCase__					,    Path(args.data_dir   )					,    args.max_seq_len					,    args.save_path   )


if __name__ == "__main__":
						packer_cli()











import cva
import numpy as np

class 	A_       :
	def __init__(    self							,					_A							,					_A		):






				'''simple docstring'''







				if k in (0.04, 0.06):
							UpperCAmelCase   		=				k
							UpperCAmelCase   		=				window_size
				else:
							raise ValueError('''invalid k value'''		)
	def __str__(    self		):






				'''simple docstring'''







				return str(self.k		)







	def      _lowercase				(    self							,					_A		):






				'''simple docstring'''







				UpperCAmelCase   		=				cva.imread(_A							,					0		)
				UpperCAmelCase		,			UpperCAmelCase   		=				img.shape
				UpperCAmelCase   		=				[]
				UpperCAmelCase   		=				img.copy()
				UpperCAmelCase   		=				cva.cvtColor(_A							,					cva.COLOR_GRAY2RGB		)
				UpperCAmelCase		,			UpperCAmelCase   		=				np.gradient(_A		)
				UpperCAmelCase   		=				dx**2
				UpperCAmelCase   		=				dy**2
				UpperCAmelCase   		=				dx * dy
				UpperCAmelCase   		=				0.04
				UpperCAmelCase   		=				self.window_size // 2
				for y in range(_A							,					h - offset		):
							for x in range(_A							,					w - offset		):
										UpperCAmelCase   		=				ixx[
										    y - offset : y + offset + 1, x - offset : x + offset + 1
										].sum()
										UpperCAmelCase   		=				iyy[
										    y - offset : y + offset + 1, x - offset : x + offset + 1
										].sum()
										UpperCAmelCase   		=				ixy[
										    y - offset : y + offset + 1, x - offset : x + offset + 1
										].sum()

										UpperCAmelCase   		=				(wxx * wyy) - (wxy**2)
										UpperCAmelCase   		=				wxx + wyy
										UpperCAmelCase   		=				det - k * (trace**2)
										# Can change the value
										if r > 0.5:
													corner_list.append([x, y, r]		)
													color_img.itemset((y, x, 0)							,					0		)
													color_img.itemset((y, x, 1)							,					0		)
													color_img.itemset((y, x, 2)							,					2_5_5		)
				return color_img, corner_list


if __name__ == "__main__":
				__A				:    Tuple       =   HarrisCorner(0.04, 3)
				__A    , __A				:    List[Any]       =   edge_detect.detect("path_to_image")
				cva.imwrite("detect.png", color_img)



