



import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin

class 		UpperCAmelCase__			(			__UpperCamelCase						,unittest.TestCase   ):




			'''simple docstring'''






			UpperCamelCase									=       BioGptTokenizer
			UpperCamelCase									=       False




			def  snake_case__     (   self							: Dict ):
					'''simple docstring'''





					super().setUp()

					# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
					__UpperCAmelCase    :     Any													=	[
					    '''l''',
					    '''o''',
					    '''w''',
					    '''e''',
					    '''r''',
					    '''s''',
					    '''t''',
					    '''i''',
					    '''d''',
					    '''n''',
					    '''w</w>''',
					    '''r</w>''',
					    '''t</w>''',
					    '''lo''',
					    '''low''',
					    '''er</w>''',
					    '''low</w>''',
					    '''lowest</w>''',
					    '''newer</w>''',
					    '''wider</w>''',
					    '''<unk>''',
					]
					__UpperCAmelCase    :     Tuple													=	dict(zip(a_       ,       range(len(a_ ) ) ) )
					__UpperCAmelCase    :     Any													=	['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

					__UpperCAmelCase    :     str													=	os.path.join(self.tmpdirname       ,       VOCAB_FILES_NAMES['''vocab_file'''] )
					__UpperCAmelCase    :     List[str]													=	os.path.join(self.tmpdirname       ,       VOCAB_FILES_NAMES['''merges_file'''] )
					with open(self.vocab_file       ,       '''w''' ) as fp:
							fp.write(json.dumps(a_ ) )
					with open(self.merges_file       ,       '''w''' ) as fp:
							fp.write('''\n'''.join(a_ ) )




			def  snake_case__     (   self							: int       ,       a_							: Tuple ):
					'''simple docstring'''





					__UpperCAmelCase    :     Union[str, Any]													=	'''lower newer'''
					__UpperCAmelCase    :     str													=	'''lower newer'''
					return input_text, output_text




			def  snake_case__     (   self							: Union[str, Any] ):
					'''simple docstring'''





					__UpperCAmelCase    :     List[Any]													=	BioGptTokenizer(self.vocab_file       ,       self.merges_file )

					__UpperCAmelCase    :     Optional[Any]													=	'''lower'''
					__UpperCAmelCase    :     int													=	['''low''', '''er</w>''']
					__UpperCAmelCase    :     int													=	tokenizer.tokenize(a_ )
					self.assertListEqual(a_       ,       a_ )

					__UpperCAmelCase    :     int													=	tokens + ['''<unk>''']
					__UpperCAmelCase    :     int													=	[14, 15, 20]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(a_ )       ,       a_ )




			@slow
			def  snake_case__     (   self							: int ):
					'''simple docstring'''





					__UpperCAmelCase    :     Tuple													=	BioGptTokenizer.from_pretrained('''microsoft/biogpt''' )

					__UpperCAmelCase    :     Union[str, Any]													=	tokenizer.encode('''sequence builders'''       ,       add_special_tokens=a_ )
					__UpperCAmelCase    :     Any													=	tokenizer.encode('''multi-sequence build'''       ,       add_special_tokens=a_ )

					__UpperCAmelCase    :     Dict													=	tokenizer.build_inputs_with_special_tokens(a_ )
					__UpperCAmelCase    :     List[str]													=	tokenizer.build_inputs_with_special_tokens(a_       ,       a_ )

					self.assertTrue(encoded_sentence == [2] + text )
					self.assertTrue(encoded_pair == [2] + text + [2] + text_a )










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

import cva
__A   			=""
__A   			=""
__A   			=""
__A   			=1  # (0 is vertical, 1 is horizontal)

def        a						(      ):







		'''simple docstring'''





		__UpperCAmelCase							,					__UpperCAmelCase    :     Union[str, Any]													=	get_dataset(_UpperCAmelCase ,   _UpperCAmelCase						)
		print('''Processing...'''						)
		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase    :     List[Any]													=	update_image_and_anno(_UpperCAmelCase ,   _UpperCAmelCase ,   _UpperCAmelCase						)

		for index, image in enumerate(_UpperCAmelCase						):
				# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
				__UpperCAmelCase    :     Any													=	random_chars(32						)
				__UpperCAmelCase    :     List[str]													=	paths[index].split(os.sep						)[-1].rsplit('''.''' ,   1						)[0]
				__UpperCAmelCase    :     Optional[Any]													=	f'{OUTPUT_DIR}/{file_name}_FLIP_{letter_code}'
				cva.imwrite(f'/{file_root}.jpg' ,   _UpperCAmelCase ,   [cva.IMWRITE_JPEG_QUALITY, 85]						)
				print(f'Success {index+1}/{len(_UpperCAmelCase						)} with {file_name}'						)
				__UpperCAmelCase    :     Optional[Any]													=	[]
				for anno in new_annos[index]:
						__UpperCAmelCase    :     Union[str, Any]													=	f'{anno[0]} {anno[1]} {anno[2]} {anno[3]} {anno[4]}'
						annos_list.append(_UpperCAmelCase						)
				with open(f'/{file_root}.txt' ,   '''w'''						) as outfile:
						outfile.write('''\n'''.join(line for line in annos_list						)						)

def        a						(      _UpperCAmelCase							:					str ,   _UpperCAmelCase							:					str						):







		'''simple docstring'''





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

				__UpperCAmelCase    :     str													=	[]
				for obj_list in obj_lists:
						__UpperCAmelCase    :     str													=	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(_UpperCAmelCase						)
				labels.append(_UpperCAmelCase						)
		return img_paths, labels

def        a						(      _UpperCAmelCase							:					list ,   _UpperCAmelCase							:					list ,   _UpperCAmelCase							:					int = 1						):







		'''simple docstring'''





		__UpperCAmelCase    :     Dict													=	[]
		__UpperCAmelCase    :     Optional[Any]													=	[]
		__UpperCAmelCase    :     Any													=	[]
		for idx in range(len(_UpperCAmelCase						)						):
				__UpperCAmelCase    :     Tuple													=	[]
				__UpperCAmelCase    :     List[Any]													=	img_list[idx]
				path_list.append(_UpperCAmelCase						)
				__UpperCAmelCase    :     str													=	anno_list[idx]
				__UpperCAmelCase    :     str													=	cva.imread(_UpperCAmelCase						)
				if flip_type == 1:
						__UpperCAmelCase    :     Any													=	cva.flip(_UpperCAmelCase ,   _UpperCAmelCase						)
						for bbox in img_annos:
								__UpperCAmelCase    :     List[str]													=	1 - bbox[1]
								new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]						)
				elif flip_type == 0:
						__UpperCAmelCase    :     Any													=	cva.flip(_UpperCAmelCase ,   _UpperCAmelCase						)
						for bbox in img_annos:
								__UpperCAmelCase    :     Union[str, Any]													=	1 - bbox[2]
								new_annos.append([bbox[0], bbox[1], y_center_new, bbox[3], bbox[4]]						)
				new_annos_lists.append(_UpperCAmelCase						)
				new_imgs_list.append(_UpperCAmelCase						)
		return new_imgs_list, new_annos_lists, path_list

def        a						(      _UpperCAmelCase							:					int = 32						):







		'''simple docstring'''





		assert number_char > 1, "The number of character should greater than 1"
		__UpperCAmelCase    :     Union[str, Any]													=	ascii_lowercase + digits
		return "".join(random.choice(_UpperCAmelCase						) for _ in range(_UpperCAmelCase						)						)


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





