


'''simple docstring'''
import os

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

__SCREAMING_SNAKE_CASE				:							Optional[Any]		       =		{'''UserAgent''': UserAgent().random}
__SCREAMING_SNAKE_CASE				:							List[Any]		       =		'''https://www.mywaifulist.moe/random'''







def 			a_							(  UpperCamelCase_	,     UpperCamelCase_   ):
							A_ 						=		requests.get(UpperCamelCase_	,     headers=UpperCamelCase_   )
							with open(UpperCamelCase_	,     "wb"   ) as file:
														file.write(image.content   )







def 			a_							(  ):
							A_ 						=		BeautifulSoup(requests.get(UpperCamelCase_	,     headers=UpperCamelCase_   ).text	,     "html.parser"   )
							A_ 						=		soup.find("meta"	,     attrs={"property": "og:title"}   ).attrs["content"]
							A_ 						=		soup.find("meta"	,     attrs={"property": "og:image"}   ).attrs["content"]
							A_ 						=		soup.find("p"	,     id="description"   ).get_text()
							A_						,				A_ 						=		os.path.splitext(os.path.basename(UpperCamelCase_   )   )
							A_ 						=		title.strip().replace(" "	,     "_"   )
							A_ 						=		f"{image_title}{image_extension}"
							save_image(UpperCamelCase_	,     UpperCamelCase_   )
							return (title, description, image_title)


if __name__ == "__main__":
							__SCREAMING_SNAKE_CASE       ,	__SCREAMING_SNAKE_CASE       ,	__SCREAMING_SNAKE_CASE				:							List[str]		       =		random_anime_character()
							print(F"{title}\n\n{desc}\n\nImage saved : {image_title}")









'''simple docstring'''
import unittest

import numpy as np

from transformers import is_tf_available
from transformers.testing_utils import require_tf


if is_tf_available():
							import tensorflow as tf

							from transformers.activations_tf import get_tf_activation






@require_tf
class 				__lowerCAmelCase      (      unittest.TestCase	):

						"""simple docstring"""






						def 							_UpperCAmelCase					(     self       :			List[Any]  ):
													A_ 						=		tf.constant([-1_00, -1.0, -0.1, 0, 0.1, 1.0, 1_0_0.0]  )
													A_ 						=		get_tf_activation("gelu"  )
													A_ 						=		get_tf_activation("gelu_10"  )

													A_ 						=		gelu(lowerCAmelCase  )
													A_ 						=		geluaa(lowerCAmelCase  )

													A_ 						=		tf.where(y_gelu_aa < 1_0.0   ,     1.0   ,     0.0  )

													self.assertEqual(tf.math.reduce_max(lowerCAmelCase  ).numpy().item()   ,     1_0.0  )
													self.assertTrue(np.allclose(y_gelu * clipped_mask   ,     y_gelu_aa * clipped_mask  )  )






						def 							_UpperCAmelCase					(     self       :			Union[str, Any]  ):
													get_tf_activation("gelu"  )
													get_tf_activation("gelu_10"  )
													get_tf_activation("gelu_fast"  )
													get_tf_activation("gelu_new"  )
													get_tf_activation("glu"  )
													get_tf_activation("mish"  )
													get_tf_activation("quick_gelu"  )
													get_tf_activation("relu"  )
													get_tf_activation("sigmoid"  )
													get_tf_activation("silu"  )
													get_tf_activation("swish"  )
													get_tf_activation("tanh"  )
													with self.assertRaises(lowerCAmelCase  ):
																				get_tf_activation("bogus"  )
													with self.assertRaises(lowerCAmelCase  ):
																				get_tf_activation(lowerCAmelCase  )





