
'''simple docstring'''







import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


lowercase					:							Tuple   =      get_tests_dir("fixtures/test_sentencepiece.model")

if is_torch_available():
					from transformers.models.mbart.modeling_mbart import shift_tokens_right

lowercase					:							Dict   =      25_0004
lowercase					:							Union[str, Any]   =      25_0020


@require_sentencepiece
@require_tokenizers
class 		__UpperCAmelCase   (      _a		,     unittest.TestCase		):
							__lowercase   	= MBartaaTokenizer
							__lowercase   	= MBartaaTokenizerFast
							__lowercase   	= True
							__lowercase   	= True


							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								super().setUp()

								# We have a SentencePiece fixture for testing
								_snake_case     		=	MBartaaTokenizer(_A					,     src_lang='en_XX'					,     tgt_lang='ro_RO'					,     keep_accents=_A						)
								tokenizer.save_pretrained(self.tmpdirname						)


							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								_snake_case     		=	'<s>'
								_snake_case     		=	0

								self.assertEqual(self.get_tokenizer()._convert_token_to_id(_A						)					,     _A						)
								self.assertEqual(self.get_tokenizer()._convert_id_to_token(_A						)					,     _A						)


							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								_snake_case     		=	list(self.get_tokenizer().get_vocab().keys()						)

								self.assertEqual(vocab_keys[0]					,     '<s>'						)
								self.assertEqual(vocab_keys[1]					,     '<pad>'						)
								self.assertEqual(vocab_keys[-1]					,     '<mask>'						)
								self.assertEqual(len(_A						)					,     10_54						)


							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								self.assertEqual(self.get_tokenizer().vocab_size					,     10_54						)


							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								_snake_case     		=	MBartaaTokenizer(_A					,     src_lang='en_XX'					,     tgt_lang='ro_RO'					,     keep_accents=_A						)

								_snake_case     		=	tokenizer.tokenize('This is a test'						)
								self.assertListEqual(_A					,     ['▁This', '▁is', '▁a', '▁t', 'est']						)

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(_A						)					,     [value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]					,     )

								_snake_case     		=	tokenizer.tokenize('I was born in 92000, and this is falsé.'						)
								self.assertListEqual(
								    _A					,     [SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '9', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', 'é', '.']					,     )
								_snake_case     		=	tokenizer.convert_tokens_to_ids(_A						)
								self.assertListEqual(
								    _A					,     [
								        value + tokenizer.fairseq_offset
								        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
								    ]					,     )

								_snake_case     		=	tokenizer.convert_ids_to_tokens(_A						)
								self.assertListEqual(
								    _A					,     [SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '<unk>', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', '<unk>', '.']					,     )


							@slow
							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								_snake_case     		=	{'input_ids': [[25_00_04, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [25_00_04, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [25_00_04, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
								# fmt: on

								self.tokenizer_integration_test_util(
								    expected_encoding=_A					,     model_name='facebook/mbart-large-50'					,     revision='d3913889c59cd5c9e456b269c376325eabad57e2'					,     )




							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								if not self.test_slow_tokenizer:
									# as we don't have a slow version, we can't compare the outputs between slow and fast versions
									return

								_snake_case     		=	(self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-mbart50', {})
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'						):
										_snake_case     		=	self.rust_tokenizer_class.from_pretrained(_A					,     **_A						)
										_snake_case     		=	self.tokenizer_class.from_pretrained(_A					,     **_A						)

										_snake_case     		=	tempfile.mkdtemp()

										_snake_case     		=	tokenizer_r.save_pretrained(_A						)
										_snake_case     		=	tokenizer_p.save_pretrained(_A						)

										# Checks it save with the same files + the tokenizer.json file for the fast one
										self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files						)						)
										_snake_case     		=	tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f						)
										self.assertSequenceEqual(_A					,     _A						)

										# Checks everything loads correctly in the same way
										_snake_case     		=	tokenizer_r.from_pretrained(_A						)
										_snake_case     		=	tokenizer_p.from_pretrained(_A						)

										# Check special tokens are set accordingly on Rust and Python
										for key in tokenizer_pp.special_tokens_map:
											self.assertTrue(hasattr(_A					,     _A						)						)
											# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
											# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

										shutil.rmtree(_A						)

										# Save tokenizer rust, legacy_format=True
										_snake_case     		=	tempfile.mkdtemp()

										_snake_case     		=	tokenizer_r.save_pretrained(_A					,     legacy_format=_A						)
										_snake_case     		=	tokenizer_p.save_pretrained(_A						)

										# Checks it save with the same files
										self.assertSequenceEqual(_A					,     _A						)

										# Checks everything loads correctly in the same way
										_snake_case     		=	tokenizer_r.from_pretrained(_A						)
										_snake_case     		=	tokenizer_p.from_pretrained(_A						)

										# Check special tokens are set accordingly on Rust and Python
										for key in tokenizer_pp.special_tokens_map:
											self.assertTrue(hasattr(_A					,     _A						)						)

										shutil.rmtree(_A						)

										# Save tokenizer rust, legacy_format=False
										_snake_case     		=	tempfile.mkdtemp()

										_snake_case     		=	tokenizer_r.save_pretrained(_A					,     legacy_format=_A						)
										_snake_case     		=	tokenizer_p.save_pretrained(_A						)

										# Checks it saved the tokenizer.json file
										self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files						)						)

										# Checks everything loads correctly in the same way
										_snake_case     		=	tokenizer_r.from_pretrained(_A						)
										_snake_case     		=	tokenizer_p.from_pretrained(_A						)

										# Check special tokens are set accordingly on Rust and Python
										for key in tokenizer_pp.special_tokens_map:
											self.assertTrue(hasattr(_A					,     _A						)						)

										shutil.rmtree(_A						)


@require_torch
@require_sentencepiece
@require_tokenizers
class 		__UpperCAmelCase   (      unittest.TestCase		):
							__lowercase   	= """facebook/mbart-large-50-one-to-many-mmt"""
							__lowercase   	= [
							    """ UN Chief Says There Is No Military Solution in Syria""",
							    """ Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.""",
							]
							__lowercase   	= [
							    """Şeful ONU declară că nu există o soluţie militară în Siria""",
							    """Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"""
							    """ pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"""
							    """ face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.""",
							]
							__lowercase   	= [EN_CODE, 82_74, 12_78_73, 2_59_16, 7, 86_22, 20_71, 4_38, 6_74_85, 53, 18_78_95, 23, 5_17_12, 2]


							@classmethod
							def 				lowerCamelCase       ( cls						):





								"""simple docstring"""






								_snake_case     		=	MBartaaTokenizer.from_pretrained(
								    cls.checkpoint_name					,     src_lang='en_XX'					,     tgt_lang='ro_RO'						)
								_snake_case     		=	1
								return cls


							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']					,     25_00_01						)
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']					,     25_00_04						)
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']					,     25_00_20						)
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']					,     25_00_38						)


							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								_snake_case     		=	self.tokenizer.batch_encode_plus(self.src_text						).input_ids[0]
								self.assertListEqual(self.expected_src_tokens					,     _A						)


							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								self.assertIn(_A					,     self.tokenizer.all_special_ids						)
								_snake_case     		=	[RO_CODE, 8_84, 90_19, 96, 9, 9_16, 8_67_92, 36, 1_87_43, 1_55_96, 5, 2]
								_snake_case     		=	self.tokenizer.decode(_A					,     skip_special_tokens=_A						)
								_snake_case     		=	self.tokenizer.decode(generated_ids[1:]					,     skip_special_tokens=_A						)
								self.assertEqual(_A					,     _A						)
								self.assertNotIn(self.tokenizer.eos_token					,     _A						)


							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								_snake_case     		=	['this is gunna be a long sentence ' * 20]
								assert isinstance(src_text[0]					,     _A						)
								_snake_case     		=	10
								_snake_case     		=	self.tokenizer(_A					,     max_length=_A					,     truncation=_A						).input_ids[0]
								self.assertEqual(ids[0]					,     _A						)
								self.assertEqual(ids[-1]					,     2						)
								self.assertEqual(len(_A						)					,     _A						)


							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']						)					,     [25_00_53, 25_00_01]						)


							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								_snake_case     		=	tempfile.mkdtemp()
								_snake_case     		=	self.tokenizer.fairseq_tokens_to_ids
								self.tokenizer.save_pretrained(_A						)
								_snake_case     		=	MBartaaTokenizer.from_pretrained(_A						)
								self.assertDictEqual(new_tok.fairseq_tokens_to_ids					,     _A						)


							@require_torch
							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								_snake_case     		=	self.tokenizer(self.src_text					,     text_target=self.tgt_text					,     padding=_A					,     return_tensors='pt'						)
								_snake_case     		=	shift_tokens_right(batch['labels']					,     self.tokenizer.pad_token_id						)

								# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
								assert batch.input_ids[1][0] == EN_CODE
								assert batch.input_ids[1][-1] == 2
								assert batch.labels[1][0] == RO_CODE
								assert batch.labels[1][-1] == 2
								assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]


							@require_torch
							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								_snake_case     		=	self.tokenizer(
								    self.src_text					,     text_target=self.tgt_text					,     padding=_A					,     truncation=_A					,     max_length=len(self.expected_src_tokens						)					,     return_tensors='pt'					,     )
								_snake_case     		=	shift_tokens_right(batch['labels']					,     self.tokenizer.pad_token_id						)

								self.assertIsInstance(_A					,     _A						)

								self.assertEqual((2, 14)					,     batch.input_ids.shape						)
								self.assertEqual((2, 14)					,     batch.attention_mask.shape						)
								_snake_case     		=	batch.input_ids.tolist()[0]
								self.assertListEqual(self.expected_src_tokens					,     _A						)
								self.assertEqual(2					,     batch.decoder_input_ids[0, 0]						)  # decoder_start_token_id
								# Test that special tokens are reset
								self.assertEqual(self.tokenizer.prefix_tokens					,     [EN_CODE]						)
								self.assertEqual(self.tokenizer.suffix_tokens					,     [self.tokenizer.eos_token_id]						)


							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								_snake_case     		=	self.tokenizer(self.src_text					,     padding=_A					,     truncation=_A					,     max_length=3					,     return_tensors='pt'						)
								_snake_case     		=	self.tokenizer(
								    text_target=self.tgt_text					,     padding=_A					,     truncation=_A					,     max_length=10					,     return_tensors='pt'						)
								_snake_case     		=	targets['input_ids']
								_snake_case     		=	shift_tokens_right(_A					,     self.tokenizer.pad_token_id						)

								self.assertEqual(batch.input_ids.shape[1]					,     3						)
								self.assertEqual(batch.decoder_input_ids.shape[1]					,     10						)




							@require_torch
							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								_snake_case     		=	self.tokenizer._build_translation_inputs(
								    'A test'					,     return_tensors='pt'					,     src_lang='en_XX'					,     tgt_lang='ar_AR'						)

								self.assertEqual(
								    nested_simplify(_A						)					,     {
								        # en_XX, A, test, EOS
								        'input_ids': [[25_00_04, 62, 30_34, 2]],
								        'attention_mask': [[1, 1, 1, 1]],
								        # ar_AR
								        'forced_bos_token_id': 25_00_01,
								    }					,     )



'''simple docstring'''







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

import cva
lowercase					:							int   =      ""
lowercase					:							Union[str, Any]   =      ""
lowercase					:							Tuple   =      ""
lowercase					:							Optional[int]   =      1  # (0 is vertical, 1 is horizontal)







def        SCREAMING_SNAKE_CASE__			(     ) ->			None:
	_snake_case		,				_snake_case     		=	get_dataset(__A    ,       __A			)
	print('Processing...'			)
	_snake_case		,				_snake_case		,				_snake_case     		=	update_image_and_anno(__A    ,       __A    ,       __A			)

	for index, image in enumerate(__A			):
		# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
		_snake_case     		=	random_chars(32			)
		_snake_case     		=	paths[index].split(os.sep			)[-1].rsplit('.'    ,       1			)[0]
		_snake_case     		=	F'{OUTPUT_DIR}/{file_name}_FLIP_{letter_code}'
		cva.imwrite(F'/{file_root}.jpg'    ,       __A    ,       [cva.IMWRITE_JPEG_QUALITY, 85]			)
		print(F'Success {index+1}/{len(__A			)} with {file_name}'			)
		_snake_case     		=	[]
		for anno in new_annos[index]:
			_snake_case     		=	F'{anno[0]} {anno[1]} {anno[2]} {anno[3]} {anno[4]}'
			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			) ->			tuple[list, list]:
	_snake_case     		=	[]
	_snake_case     		=	[]
	for label_file in glob.glob(os.path.join(__A    ,       '*.txt'			)			):
		_snake_case     		=	label_file.split(os.sep			)[-1].rsplit('.'    ,       1			)[0]
		with open(__A			) as in_file:
			_snake_case     		=	in_file.readlines()
		_snake_case     		=	os.path.join(__A    ,       F'{label_name}.jpg'			)

		_snake_case     		=	[]
		for obj_list in obj_lists:
			_snake_case     		=	obj_list.rstrip('\n'			).split(' '			)
			boxes.append(
			    [
			        int(obj[0]			),
			        float(obj[1]			),
			        float(obj[2]			),
			        float(obj[3]			),
			        float(obj[4]			),
			    ]			)
		if not boxes:
			continue
		img_paths.append(__A			)
		labels.append(__A			)
	return img_paths, labels







def        SCREAMING_SNAKE_CASE__			(     __A    ,       __A    ,       __A = 1			) ->			tuple[list, list, list]:
	_snake_case     		=	[]
	_snake_case     		=	[]
	_snake_case     		=	[]
	for idx in range(len(__A			)			):
		_snake_case     		=	[]
		_snake_case     		=	img_list[idx]
		path_list.append(__A			)
		_snake_case     		=	anno_list[idx]
		_snake_case     		=	cva.imread(__A			)
		if flip_type == 1:
			_snake_case     		=	cva.flip(__A    ,       __A			)
			for bbox in img_annos:
				_snake_case     		=	1 - bbox[1]
				new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]			)
		elif flip_type == 0:
			_snake_case     		=	cva.flip(__A    ,       __A			)
			for bbox in img_annos:
				_snake_case     		=	1 - bbox[2]
				new_annos.append([bbox[0], bbox[1], y_center_new, bbox[3], bbox[4]]			)
		new_annos_lists.append(__A			)
		new_imgs_list.append(__A			)
	return new_imgs_list, new_annos_lists, path_list







def        SCREAMING_SNAKE_CASE__			(     __A = 32			) ->			str:
	assert number_char > 1, "The number of character should greater than 1"
	_snake_case     		=	ascii_lowercase + digits
	return "".join(random.choice(__A			) for _ in range(__A			)			)


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

