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

import cva
__lowerCAmelCase					   =       ''
__lowerCAmelCase					   =       ''
__lowerCAmelCase					   =       ''
__lowerCAmelCase					   =       1  # (0 is vertical, 1 is horizontal)


def    a      ( )     ->None:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE     						= get_dataset(a		,						a	)
			print('''Processing...'''	)
			SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE     						= update_image_and_anno(a		,						a		,						a	)

			for index, image in enumerate(a	):
						# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
						SCREAMING_SNAKE_CASE     						= random_chars(32	)
						SCREAMING_SNAKE_CASE     						= paths[index].split(os.sep	)[-1].rsplit('''.'''		,						1	)[0]
						SCREAMING_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}"""	)
						SCREAMING_SNAKE_CASE     						= []
						for anno in new_annos[index]:
									SCREAMING_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    a      ( a		,						a	)     ->tuple[list, list]:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE     						= []
			SCREAMING_SNAKE_CASE     						= []
			for label_file in glob.glob(os.path.join(a		,						'''*.txt'''	)	):
						SCREAMING_SNAKE_CASE     						= label_file.split(os.sep	)[-1].rsplit('''.'''		,						1	)[0]
						with open(a	) as in_file:
									SCREAMING_SNAKE_CASE     						= in_file.readlines()
						SCREAMING_SNAKE_CASE     						= os.path.join(a		,						F"""{label_name}.jpg"""	)

						SCREAMING_SNAKE_CASE     						= []
						for obj_list in obj_lists:
									SCREAMING_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    a      ( a		,						a		,						a = 1	)     ->tuple[list, list, list]:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE     						= []
			SCREAMING_SNAKE_CASE     						= []
			SCREAMING_SNAKE_CASE     						= []
			for idx in range(len(a	)	):
						SCREAMING_SNAKE_CASE     						= []
						SCREAMING_SNAKE_CASE     						= img_list[idx]
						path_list.append(a	)
						SCREAMING_SNAKE_CASE     						= anno_list[idx]
						SCREAMING_SNAKE_CASE     						= cva.imread(a	)
						if flip_type == 1:
									SCREAMING_SNAKE_CASE     						= cva.flip(a		,						a	)
									for bbox in img_annos:
												SCREAMING_SNAKE_CASE     						= 1 - bbox[1]
												new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]	)
						elif flip_type == 0:
									SCREAMING_SNAKE_CASE     						= cva.flip(a		,						a	)
									for bbox in img_annos:
												SCREAMING_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    a      ( a = 32	)     ->str:




			'''simple docstring'''


			assert number_char > 1, "The number of character should greater than 1"
			SCREAMING_SNAKE_CASE     						= ascii_lowercase + digits
			return "".join(random.choice(a	) for _ in range(a	)	)


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

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCAmelCase					   =       logging.get_logger(__name__)

__lowerCAmelCase					   =       {
    'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}





class     lowerCamelCase      (       __lowerCamelCase					):
	UpperCamelCase_  :					Union[str, Any]    		=	'biogpt'







	def __init__(     self      :Tuple   ,     lowercase      :Union[str, Any]=4_2_3_8_4   ,     lowercase      :str=1_0_2_4   ,     lowercase      :Any=2_4   ,     lowercase      :List[str]=1_6   ,     lowercase      :List[str]=4_0_9_6   ,     lowercase      :int="gelu"   ,     lowercase      :List[Any]=0.1   ,     lowercase      :int=0.1   ,     lowercase      :int=1_0_2_4   ,     lowercase      :Optional[Any]=0.02   ,     lowercase      :Union[str, Any]=1e-12   ,     lowercase      :Tuple=True   ,     lowercase      :int=True   ,     lowercase      :Optional[int]=0.0   ,     lowercase      :Any=0.0   ,     lowercase      :str=1   ,     lowercase      :Any=0   ,     lowercase      :int=2   ,     **lowercase      :Tuple   ,     )		->      Optional[int]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= vocab_size
				SCREAMING_SNAKE_CASE     						= max_position_embeddings
				SCREAMING_SNAKE_CASE     						= hidden_size
				SCREAMING_SNAKE_CASE     						= num_hidden_layers
				SCREAMING_SNAKE_CASE     						= num_attention_heads
				SCREAMING_SNAKE_CASE     						= intermediate_size
				SCREAMING_SNAKE_CASE     						= hidden_act
				SCREAMING_SNAKE_CASE     						= hidden_dropout_prob
				SCREAMING_SNAKE_CASE     						= attention_probs_dropout_prob
				SCREAMING_SNAKE_CASE     						= initializer_range
				SCREAMING_SNAKE_CASE     						= layer_norm_eps
				SCREAMING_SNAKE_CASE     						= scale_embedding
				SCREAMING_SNAKE_CASE     						= use_cache
				SCREAMING_SNAKE_CASE     						= layerdrop
				SCREAMING_SNAKE_CASE     						= activation_dropout
				super().__init__(pad_token_id=lowercase   ,     bos_token_id=lowercase   ,     eos_token_id=lowercase   ,     **lowercase			)