





import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_SCREAMING_SNAKE_CASE      	=		logging.get_logger(__name__)


_SCREAMING_SNAKE_CASE      	=		{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

# See all BART models at https://huggingface.co/models?filter=bart
_SCREAMING_SNAKE_CASE      	=		{
    """vocab_file""": {
        """facebook/bart-base""": """https://huggingface.co/facebook/bart-base/resolve/main/vocab.json""",
        """facebook/bart-large""": """https://huggingface.co/facebook/bart-large/resolve/main/vocab.json""",
        """facebook/bart-large-mnli""": """https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json""",
        """facebook/bart-large-cnn""": """https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json""",
        """facebook/bart-large-xsum""": """https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json""",
        """yjernite/bart_eli5""": """https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """facebook/bart-base""": """https://huggingface.co/facebook/bart-base/resolve/main/merges.txt""",
        """facebook/bart-large""": """https://huggingface.co/facebook/bart-large/resolve/main/merges.txt""",
        """facebook/bart-large-mnli""": """https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt""",
        """facebook/bart-large-cnn""": """https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt""",
        """facebook/bart-large-xsum""": """https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt""",
        """yjernite/bart_eli5""": """https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt""",
    },
}

_SCREAMING_SNAKE_CASE      	=		{
    """facebook/bart-base""": 10_24,
    """facebook/bart-large""": 10_24,
    """facebook/bart-large-mnli""": 10_24,
    """facebook/bart-large-cnn""": 10_24,
    """facebook/bart-large-xsum""": 10_24,
    """yjernite/bart_eli5""": 10_24,
}


@lru_cache()
def 							SCREAMING_SNAKE_CASE__						(    ):
	snake_case_		:			Optional[Any]											=	(
	    list(range(ord('!'   )   , ord('~'   ) + 1   )   ) + list(range(ord('¡'   )   , ord('¬'   ) + 1   )   ) + list(range(ord('®'   )   , ord('ÿ'   ) + 1   )   )
	)
	snake_case_		:			List[Any]											=	bs[:]
	snake_case_		:			Dict											=	0
	for b in range(2**8   ):
		if b not in bs:
			bs.append(__a   )
			cs.append(2**8 + n   )
			n += 1
	snake_case_		:			str											=	[chr(__a   ) for n in cs]
	return dict(zip(__a   , __a   )   )


def 							SCREAMING_SNAKE_CASE__						(    __a   ):
	snake_case_		:			List[Any]											=	set()
	snake_case_		:			List[str]											=	word[0]
	for char in word[1:]:
		pairs.add((prev_char, char)   )
		snake_case_		:			Any											=	char
	return pairs


class SCREAMING_SNAKE_CASE_						(					snake_case_					):
						__magic_name__:			Any       =       VOCAB_FILES_NAMES
						__magic_name__:			Tuple       =       PRETRAINED_VOCAB_FILES_MAP
						__magic_name__:			str       =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						__magic_name__:			List[Any]       =       ["input_ids", "attention_mask"]






						def __init__(      self      :      Dict		,   _A      :      List[Any]		,   _A      :      Optional[int]		,   _A      :      List[Any]="replace"		,   _A      :      List[str]="<s>"		,   _A      :      Tuple="</s>"		,   _A      :      Optional[int]="</s>"		,   _A      :      Optional[Any]="<s>"		,   _A      :      Tuple="<unk>"		,   _A      :      Any="<pad>"		,   _A      :      List[Any]="<mask>"		,   _A      :      int=False		,   **_A      :      int		,   )							->    int:







							"""simple docstring"""


							snake_case_		:			Any											=	AddedToken(_A		,   lstrip=_A		,   rstrip=_A	) if isinstance(_A		,   _A	) else bos_token
							snake_case_		:			Any											=	AddedToken(_A		,   lstrip=_A		,   rstrip=_A	) if isinstance(_A		,   _A	) else eos_token
							snake_case_		:			Dict											=	AddedToken(_A		,   lstrip=_A		,   rstrip=_A	) if isinstance(_A		,   _A	) else sep_token
							snake_case_		:			str											=	AddedToken(_A		,   lstrip=_A		,   rstrip=_A	) if isinstance(_A		,   _A	) else cls_token
							snake_case_		:			Dict											=	AddedToken(_A		,   lstrip=_A		,   rstrip=_A	) if isinstance(_A		,   _A	) else unk_token
							snake_case_		:			Tuple											=	AddedToken(_A		,   lstrip=_A		,   rstrip=_A	) if isinstance(_A		,   _A	) else pad_token

							# Mask token behave like a normal word, i.e. include the space before it
							snake_case_		:			Optional[Any]											=	AddedToken(_A		,   lstrip=_A		,   rstrip=_A	) if isinstance(_A		,   _A	) else mask_token

							super().__init__(
							    errors=_A		,   bos_token=_A		,   eos_token=_A		,   unk_token=_A		,   sep_token=_A		,   cls_token=_A		,   pad_token=_A		,   mask_token=_A		,   add_prefix_space=_A		,   **_A		,   )

							with open(_A		,   encoding='utf-8'	) as vocab_handle:
								snake_case_		:			Optional[Any]											=	json.load(_A	)
							snake_case_		:			str											=	{v: k for k, v in self.encoder.items()}
							snake_case_		:			str											=	errors  # how to handle errors in decoding
							snake_case_		:			str											=	bytes_to_unicode()
							snake_case_		:			Tuple											=	{v: k for k, v in self.byte_encoder.items()}
							with open(_A		,   encoding='utf-8'	) as merges_handle:
								snake_case_		:			Optional[int]											=	merges_handle.read().split('\n'	)[1:-1]
							snake_case_		:			Optional[Any]											=	[tuple(merge.split()	) for merge in bpe_merges]
							snake_case_		:			List[Any]											=	dict(zip(_A		,   range(len(_A	)	)	)	)
							snake_case_		:			str											=	{}
							snake_case_		:			List[Any]											=	add_prefix_space

							# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
							snake_case_		:			List[Any]											=	re.compile(R'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'	)






						@property
						def UpperCAmelCase_				(      self      :      Optional[Any]	)							->    str:







							"""simple docstring"""


							return len(self.encoder	)






						def UpperCAmelCase_				(      self      :      Dict	)							->    str:







							"""simple docstring"""


							return dict(self.encoder		,   **self.added_tokens_encoder	)






						def UpperCAmelCase_				(      self      :      Union[str, Any]		,   _A      :      Optional[int]	)							->    Any:







							"""simple docstring"""


							if token in self.cache:
								return self.cache[token]
							snake_case_		:			Any											=	tuple(_A	)
							snake_case_		:			str											=	get_pairs(_A	)

							if not pairs:
								return token

							while True:
								snake_case_		:			Tuple											=	min(_A		,   key=lambda _A	: self.bpe_ranks.get(_A		,   float('inf'	)	)	)
								if bigram not in self.bpe_ranks:
									break
								snake_case_						,snake_case_		:			Optional[int]											=	bigram
								snake_case_		:			List[str]											=	[]
								snake_case_		:			Optional[int]											=	0
								while i < len(_A	):
									try:
										snake_case_		:			Tuple											=	word.index(_A		,   _A	)
									except ValueError:
										new_word.extend(word[i:]	)
										break
									else:
										new_word.extend(word[i:j]	)
										snake_case_		:			int											=	j

									if word[i] == first and i < len(_A	) - 1 and word[i + 1] == second:
										new_word.append(first + second	)
										i += 2
									else:
										new_word.append(word[i]	)
										i += 1
								snake_case_		:			str											=	tuple(_A	)
								snake_case_		:			Optional[int]											=	new_word
								if len(_A	) == 1:
									break
								else:
									snake_case_		:			Any											=	get_pairs(_A	)
							snake_case_		:			Dict											=	' '.join(_A	)
							snake_case_		:			Dict											=	word
							return word






						def UpperCAmelCase_				(      self      :      List[Any]		,   _A      :      Dict	)							->    Tuple:







							"""simple docstring"""


							snake_case_		:			Union[str, Any]											=	[]
							for token in re.findall(self.pat		,   _A	):
								snake_case_		:			Union[str, Any]											=	''.join(
								    self.byte_encoder[b] for b in token.encode('utf-8'	)	)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
								bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_A	).split(' '	)	)
							return bpe_tokens






						def UpperCAmelCase_				(      self      :      List[str]		,   _A      :      Optional[int]	)							->    Union[str, Any]:







							"""simple docstring"""


							return self.encoder.get(_A		,   self.encoder.get(self.unk_token	)	)






						def UpperCAmelCase_				(      self      :      Any		,   _A      :      str	)							->    Union[str, Any]:







							"""simple docstring"""


							return self.decoder.get(_A	)






						def UpperCAmelCase_				(      self      :      str		,   _A      :      int	)							->    Dict:







							"""simple docstring"""


							snake_case_		:			Union[str, Any]											=	''.join(_A	)
							snake_case_		:			Any											=	bytearray([self.byte_decoder[c] for c in text]	).decode('utf-8'		,   errors=self.errors	)
							return text






						def UpperCAmelCase_				(      self      :      Dict		,   _A      :      str		,   _A      :      Optional[str] = None	)							->    Tuple[str]:







							"""simple docstring"""


							if not os.path.isdir(_A	):
								logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""	)
								return
							snake_case_		:			List[Any]											=	os.path.join(
							    _A		,   (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)
							snake_case_		:			Tuple											=	os.path.join(
							    _A		,   (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']	)

							with open(_A		,   'w'		,   encoding='utf-8'	) as f:
								f.write(json.dumps(self.encoder		,   indent=2		,   sort_keys=_A		,   ensure_ascii=_A	) + '\n'	)

							snake_case_		:			Dict											=	0
							with open(_A		,   'w'		,   encoding='utf-8'	) as writer:
								writer.write('#version: 0.2\n'	)
								for bpe_tokens, token_index in sorted(self.bpe_ranks.items()		,   key=lambda _A	: kv[1]	):
									if index != token_index:
										logger.warning(
										    F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
										    ' Please check that the tokenizer is not corrupted!'	)
										snake_case_		:			Optional[Any]											=	token_index
									writer.write(' '.join(_A	) + '\n'	)
									index += 1

							return vocab_file, merge_file






						def UpperCAmelCase_				(      self      :      Tuple		,   _A      :      List[int]		,   _A      :      Optional[List[int]] = None	)							->    List[int]:







							"""simple docstring"""


							if token_ids_a is None:
								return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							snake_case_		:			Any											=	[self.cls_token_id]
							snake_case_		:			List[Any]											=	[self.sep_token_id]
							return cls + token_ids_a + sep + sep + token_ids_a + sep






						def UpperCAmelCase_				(      self      :      List[Any]		,   _A      :      List[int]		,   _A      :      Optional[List[int]] = None		,   _A      :      bool = False	)							->    List[int]:







							"""simple docstring"""


							if already_has_special_tokens:
								return super().get_special_tokens_mask(
								    token_ids_a=_A		,   token_ids_a=_A		,   already_has_special_tokens=_A	)

							if token_ids_a is None:
								return [1] + ([0] * len(_A	)) + [1]
							return [1] + ([0] * len(_A	)) + [1, 1] + ([0] * len(_A	)) + [1]






						def UpperCAmelCase_				(      self      :      Union[str, Any]		,   _A      :      List[int]		,   _A      :      Optional[List[int]] = None	)							->    List[int]:







							"""simple docstring"""


							snake_case_		:			Union[str, Any]											=	[self.sep_token_id]
							snake_case_		:			Optional[Any]											=	[self.cls_token_id]

							if token_ids_a is None:
								return len(cls + token_ids_a + sep	) * [0]
							return len(cls + token_ids_a + sep + sep + token_ids_a + sep	) * [0]






						def UpperCAmelCase_				(      self      :      List[str]		,   _A      :      Optional[int]		,   _A      :      Dict=False		,   **_A      :      Optional[Any]	)							->    Tuple:







							"""simple docstring"""


							snake_case_		:			int											=	kwargs.pop('add_prefix_space'		,   self.add_prefix_space	)
							if (is_split_into_words or add_prefix_space) and (len(_A	) > 0 and not text[0].isspace()):
								snake_case_		:			Optional[int]											=	' ' + text
							return (text, kwargs)








import glob
import os
import random
from string import ascii_lowercase, digits

import cva
import numpy as np

# Parrameters
_SCREAMING_SNAKE_CASE      	=		(7_20, 12_80)  # Height, Width
_SCREAMING_SNAKE_CASE      	=		(0.4, 0.6)  # if height or width lower than this scale, drop it.
_SCREAMING_SNAKE_CASE      	=		1 / 1_00
_SCREAMING_SNAKE_CASE      	=		""""""
_SCREAMING_SNAKE_CASE      	=		""""""
_SCREAMING_SNAKE_CASE      	=		""""""
_SCREAMING_SNAKE_CASE      	=		2_50


def 							SCREAMING_SNAKE_CASE__						(    ):
	snake_case_						,snake_case_		:			Any											=	get_dataset(__a   , __a   )
	for index in range(__a   ):
		snake_case_		:			Dict											=	random.sample(range(len(__a   )   )   , 4   )
		snake_case_						,snake_case_						,snake_case_		:			Optional[int]											=	update_image_and_anno(
		    __a   , __a   , __a   , __a   , __a   , filter_scale=__a   , )

		# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
		snake_case_		:			List[str]											=	random_chars(32   )
		snake_case_		:			Dict											=	path.split(os.sep   )[-1].rsplit('.'   , 1   )[0]
		snake_case_		:			Any											=	f"""{OUTPUT_DIR}/{file_name}_MOSAIC_{letter_code}"""
		cva.imwrite(f"""{file_root}.jpg"""   , __a   , [cva.IMWRITE_JPEG_QUALITY, 85]   )
		print(f"""Succeeded {index+1}/{NUMBER_IMAGES} with {file_name}"""   )
		snake_case_		:			Dict											=	[]
		for anno in new_annos:
			snake_case_		:			int											=	anno[3] - anno[1]
			snake_case_		:			Dict											=	anno[4] - anno[2]
			snake_case_		:			int											=	anno[1] + width / 2
			snake_case_		:			str											=	anno[2] + height / 2
			snake_case_		:			Union[str, Any]											=	f"""{anno[0]} {x_center} {y_center} {width} {height}"""
			annos_list.append(__a   )
		with open(f"""{file_root}.txt"""   , 'w'   ) as outfile:
			outfile.write('\n'.join(line for line in annos_list   )   )


def 							SCREAMING_SNAKE_CASE__						(    __a   , __a   ):
	snake_case_		:			List[Any]											=	[]
	snake_case_		:			Optional[int]											=	[]
	for label_file in glob.glob(os.path.join(__a   , '*.txt'   )   ):
		snake_case_		:			List[str]											=	label_file.split(os.sep   )[-1].rsplit('.'   , 1   )[0]
		with open(__a   ) as in_file:
			snake_case_		:			Dict											=	in_file.readlines()
		snake_case_		:			int											=	os.path.join(__a   , f"""{label_name}.jpg"""   )

		snake_case_		:			int											=	[]
		for obj_list in obj_lists:
			snake_case_		:			str											=	obj_list.rstrip('\n'   ).split(' '   )
			snake_case_		:			Tuple											=	float(obj[1]   ) - float(obj[3]   ) / 2
			snake_case_		:			str											=	float(obj[2]   ) - float(obj[4]   ) / 2
			snake_case_		:			Optional[Any]											=	float(obj[1]   ) + float(obj[3]   ) / 2
			snake_case_		:			List[Any]											=	float(obj[2]   ) + float(obj[4]   ) / 2

			boxes.append([int(obj[0]   ), xmin, ymin, xmax, ymax]   )
		if not boxes:
			continue
		img_paths.append(__a   )
		labels.append(__a   )
	return img_paths, labels


def 							SCREAMING_SNAKE_CASE__						(    __a   , __a   , __a   , __a   , __a   , __a = 0.0   , ):
	snake_case_		:			str											=	np.zeros([output_size[0], output_size[1], 3]   , dtype=np.uinta   )
	snake_case_		:			Tuple											=	scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
	snake_case_		:			int											=	scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
	snake_case_		:			Optional[Any]											=	int(scale_x * output_size[1]   )
	snake_case_		:			int											=	int(scale_y * output_size[0]   )

	snake_case_		:			str											=	[]
	snake_case_		:			Dict											=	[]
	for i, index in enumerate(__a   ):
		snake_case_		:			Any											=	all_img_list[index]
		path_list.append(__a   )
		snake_case_		:			List[str]											=	all_annos[index]
		snake_case_		:			Any											=	cva.imread(__a   )
		if i == 0:  # top-left
			snake_case_		:			Optional[Any]											=	cva.resize(__a   , (divid_point_x, divid_point_y)   )
			snake_case_		:			Dict											=	img
			for bbox in img_annos:
				snake_case_		:			Dict											=	bbox[1] * scale_x
				snake_case_		:			Tuple											=	bbox[2] * scale_y
				snake_case_		:			Optional[Any]											=	bbox[3] * scale_x
				snake_case_		:			str											=	bbox[4] * scale_y
				new_anno.append([bbox[0], xmin, ymin, xmax, ymax]   )
		elif i == 1:  # top-right
			snake_case_		:			Tuple											=	cva.resize(__a   , (output_size[1] - divid_point_x, divid_point_y)   )
			snake_case_		:			Optional[Any]											=	img
			for bbox in img_annos:
				snake_case_		:			int											=	scale_x + bbox[1] * (1 - scale_x)
				snake_case_		:			Dict											=	bbox[2] * scale_y
				snake_case_		:			Union[str, Any]											=	scale_x + bbox[3] * (1 - scale_x)
				snake_case_		:			Union[str, Any]											=	bbox[4] * scale_y
				new_anno.append([bbox[0], xmin, ymin, xmax, ymax]   )
		elif i == 2:  # bottom-left
			snake_case_		:			Optional[Any]											=	cva.resize(__a   , (divid_point_x, output_size[0] - divid_point_y)   )
			snake_case_		:			int											=	img
			for bbox in img_annos:
				snake_case_		:			int											=	bbox[1] * scale_x
				snake_case_		:			List[str]											=	scale_y + bbox[2] * (1 - scale_y)
				snake_case_		:			List[str]											=	bbox[3] * scale_x
				snake_case_		:			Union[str, Any]											=	scale_y + bbox[4] * (1 - scale_y)
				new_anno.append([bbox[0], xmin, ymin, xmax, ymax]   )
		else:  # bottom-right
			snake_case_		:			str											=	cva.resize(
			    __a   , (output_size[1] - divid_point_x, output_size[0] - divid_point_y)   )
			snake_case_		:			Dict											=	img
			for bbox in img_annos:
				snake_case_		:			Dict											=	scale_x + bbox[1] * (1 - scale_x)
				snake_case_		:			Tuple											=	scale_y + bbox[2] * (1 - scale_y)
				snake_case_		:			Union[str, Any]											=	scale_x + bbox[3] * (1 - scale_x)
				snake_case_		:			List[Any]											=	scale_y + bbox[4] * (1 - scale_y)
				new_anno.append([bbox[0], xmin, ymin, xmax, ymax]   )

    # Remove bounding box small than scale of filter
	if filter_scale > 0:
		snake_case_		:			Dict											=	[
		    anno
		    for anno in new_anno
		    if filter_scale < (anno[3] - anno[1]) and filter_scale < (anno[4] - anno[2])
		]

	return output_img, new_anno, path_list[0]


def 							SCREAMING_SNAKE_CASE__						(    __a   ):
	assert number_char > 1, "The number of character should greater than 1"
	snake_case_		:			Tuple											=	ascii_lowercase + digits
	return "".join(random.choice(__a   ) for _ in range(__a   )   )


if __name__ == "__main__":
						main()
						print("""DONE ✅""")

