
'''simple docstring'''







from typing import Optional, Tuple

import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule







def        SCREAMING_SNAKE_CASE__			(     __A    ,       __A    ,       __A=1e-12			) ->			Tuple:
	_snake_case     		=	jnp.divide(emb_a.T    ,       jnp.clip(jnp.linalg.norm(__A    ,       axis=1			)    ,       a_min=__A			)			).T
	_snake_case     		=	jnp.divide(emb_a.T    ,       jnp.clip(jnp.linalg.norm(__A    ,       axis=1			)    ,       a_min=__A			)			).T
	return jnp.matmul(__A    ,       norm_emb_a.T			)


class 		__UpperCAmelCase   (      nn.Module		):
							__lowercase   	= 42
							__lowercase   	= jnp.floataa


							def 				lowerCamelCase       ( self						):





								"""simple docstring"""






								_snake_case     		=	FlaxCLIPVisionModule(self.config.vision_config						)
								_snake_case     		=	nn.Dense(self.config.projection_dim					,     use_bias=lowerCAmelCase_					,     dtype=self.dtype						)

								_snake_case     		=	self.param('concept_embeds'					,     jax.nn.initializers.ones					,     (17, self.config.projection_dim)						)
								_snake_case     		=	self.param(
								    'special_care_embeds'					,     jax.nn.initializers.ones					,     (3, self.config.projection_dim)						)

								_snake_case     		=	self.param('concept_embeds_weights'					,     jax.nn.initializers.ones					,     (17,)						)
								_snake_case     		=	self.param('special_care_embeds_weights'					,     jax.nn.initializers.ones					,     (3,)						)




							def __call__( self					,     lowerCAmelCase_						):





								"""simple docstring"""






								_snake_case     		=	self.vision_model(lowerCAmelCase_						)[1]
								_snake_case     		=	self.visual_projection(lowerCAmelCase_						)

								_snake_case     		=	jax_cosine_distance(lowerCAmelCase_					,     self.special_care_embeds						)
								_snake_case     		=	jax_cosine_distance(lowerCAmelCase_					,     self.concept_embeds						)

								# increase this value to create a stronger `nfsw` filter
								# at the cost of increasing the possibility of filtering benign image inputs
								_snake_case     		=	0.0

								_snake_case     		=	special_cos_dist - self.special_care_embeds_weights[None, :] + adjustment
								_snake_case     		=	jnp.round(lowerCAmelCase_					,     3						)
								_snake_case     		=	jnp.any(special_scores > 0					,     axis=1					,     keepdims=lowerCAmelCase_						)
								# Use a lower threshold if an image has any special care concept
								_snake_case     		=	is_special_care * 0.01

								_snake_case     		=	cos_dist - self.concept_embeds_weights[None, :] + special_adjustment
								_snake_case     		=	jnp.round(lowerCAmelCase_					,     3						)
								_snake_case     		=	jnp.any(concept_scores > 0					,     axis=1						)

								return has_nsfw_concepts


class 		__UpperCAmelCase   (      _lowerCamelCase		):
							__lowercase   	= CLIPConfig
							__lowercase   	= """clip_input"""
							__lowercase   	= FlaxStableDiffusionSafetyCheckerModule


							def __init__( self					,     lowerCAmelCase_					,     lowerCAmelCase_ = None					,     lowerCAmelCase_ = 0					,     lowerCAmelCase_ = jnp.floataa					,     lowerCAmelCase_ = True					,     **lowerCAmelCase_					,     ):





								"""simple docstring"""






								if input_shape is None:
									_snake_case     		=	(1, 2_24, 2_24, 3)
								_snake_case     		=	self.module_class(config=lowerCAmelCase_					,     dtype=lowerCAmelCase_					,     **lowerCAmelCase_						)
								super().__init__(lowerCAmelCase_					,     lowerCAmelCase_					,     input_shape=lowerCAmelCase_					,     seed=lowerCAmelCase_					,     dtype=lowerCAmelCase_					,     _do_init=_do_init						)


							def 				lowerCamelCase       ( self					,     lowerCAmelCase_					,     lowerCAmelCase_					,     lowerCAmelCase_ = None						):





								"""simple docstring"""






								_snake_case     		=	jax.random.normal(lowerCAmelCase_					,     lowerCAmelCase_						)

								_snake_case		,				_snake_case     		=	jax.random.split(lowerCAmelCase_						)
								_snake_case     		=	{'params': params_rng, 'dropout': dropout_rng}

								_snake_case     		=	self.module.init(lowerCAmelCase_					,     lowerCAmelCase_						)['params']

								return random_params




							def __call__( self					,     lowerCAmelCase_					,     lowerCAmelCase_ = None					,     ):





								"""simple docstring"""






								_snake_case     		=	jnp.transpose(lowerCAmelCase_					,     (0, 2, 3, 1)						)

								return self.module.apply(
								    {'params': params or self.params}					,     jnp.array(lowerCAmelCase_					,     dtype=jnp.floataa						)					,     rngs={}					,     )



'''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 ✅")

