

'''simple docstring'''

import math
from collections import OrderedDict

import torch
from packaging import version
from torch import Tensor, nn

from .utils import logging


lowerCAmelCase_						   =			logging.get_logger(__name__)







class lowerCamelCase      (						nn.Module							):

				def __init__(					self   )						->       Optional[Any]:
					super().__init__()
					if version.parse(torch.__version__   ) < version.parse('1.12.0'   ):
						raise ImportError(
						    F'''You are using torch=={torch.__version__}, but torch>=1.12.0 is required to use '''
						    'PytorchGELUTanh. Please upgrade torch.'   )






				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Tensor:
					return nn.functional.gelu(lowercase_,	approximate='tanh'   )







class lowerCamelCase      (						nn.Module							):

				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Tensor:
					return 0.5 * input * (1.0 + torch.tanh(math.sqrt(2.0 / math.pi   ) * (input + 0.044_715 * torch.pow(lowercase_,	3.0   ))   ))







class lowerCamelCase      (						nn.Module							):

				def __init__(					self,	lowercase_ = False   )						->       str:
					super().__init__()
					if use_gelu_python:
						snake_case							 =				self._gelu_python
					else:
						snake_case							 =				nn.functional.gelu

				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Tensor:
					return input * 0.5 * (1.0 + torch.erf(input / math.sqrt(2.0   )   ))






				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Tensor:
					return self.act(lowercase_   )







class lowerCamelCase      (						nn.Module							):

				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Tensor:
					return 0.5 * input * (1.0 + torch.tanh(input * 0.7_978_845_608 * (1.0 + 0.044_715 * input * input)   ))







class lowerCamelCase      (						nn.Module							):

				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Tensor:
					return input * torch.sigmoid(1.702 * input   )







class lowerCamelCase      (						nn.Module							):

				def __init__(					self,	lowercase_,	lowercase_   )						->       List[str]:
					if min > max:
						raise ValueError(F'''min should be < max (got min: {min}, max: {max})'''   )

					super().__init__()
					snake_case							 =				min
					snake_case							 =				max






				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Tensor:
					return torch.clip(gelu(lowercase_   ),	self.min,	self.max   )







class lowerCamelCase      (						nn.Module							):

				def __init__(					self   )						->       Union[str, Any]:
					super().__init__()
					snake_case							 =				math.sqrt(2 / math.pi   )






				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Tensor:
					return 0.5 * input * (1 + torch.tanh(self.precomputed_constant * (input + 0.044_715 * torch.pow(lowercase_,	3   ))   ))







class lowerCamelCase      (						nn.Module							):

				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Tensor:
					return nn.functional.silu(lowercase_   )







class lowerCamelCase      (						nn.Module							):

				def __init__(					self   )						->       Optional[Any]:
					super().__init__()
					if version.parse(torch.__version__   ) < version.parse('1.9.0'   ):
						snake_case							 =				self._mish_python
					else:
						snake_case							 =				nn.functional.mish

				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Tensor:
					return input * torch.tanh(nn.functional.softplus(lowercase_   )   )






				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Tensor:
					return self.act(lowercase_   )







class lowerCamelCase      (						nn.Module							):

				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Tensor:
					return input







class lowerCamelCase      (						nn.Module							):

				def 				_lowerCamelCase						(					self,	lowercase_,	lowercase_=0.707_107,	lowercase_=0.282_095   )						->       str:
					snake_case							 =				(input - mu).div(sigma * math.sqrt(2.0   )   )
					return 0.5 * (1.0 + torch.erf(lowercase_   ))







class lowerCamelCase      (						nn.Module							):

				def 				_lowerCamelCase						(					self,	lowercase_   )						->       str:
					snake_case							 =				nn.functional.relu(lowercase_   )
					snake_case							 =				torch.square(lowercase_   )
					return squared







class lowerCamelCase      (						__lowerCAmelCase							):

				def __getitem__(					self,	lowercase_   )						->       int:
					snake_case							 =				super().__getitem__(lowercase_   )
					snake_case , snake_case							 =				content if isinstance(lowercase_,	lowercase_   ) else (content, {})
					return cls(**lowercase_   )
lowerCAmelCase_						   =			{
    "gelu": GELUActivation,
    "gelu_10": (ClippedGELUActivation, {"min": -1_0, "max": 1_0}),
    "gelu_fast": FastGELUActivation,
    "gelu_new": NewGELUActivation,
    "gelu_python": (GELUActivation, {"use_gelu_python": True}),
    "gelu_pytorch_tanh": PytorchGELUTanh,
    "gelu_accurate": AccurateGELUActivation,
    "laplace": LaplaceActivation,
    "linear": LinearActivation,
    "mish": MishActivation,
    "quick_gelu": QuickGELUActivation,
    "relu": nn.ReLU,
    "relu2": ReLUSquaredActivation,
    "relu6": nn.ReLUa,
    "sigmoid": nn.Sigmoid,
    "silu": SiLUActivation,
    "swish": SiLUActivation,
    "tanh": nn.Tanh,
}
lowerCAmelCase_						   =			ClassInstantier(ACTaCLS)

def     __magic_name__       ( A							)			->		int:
	if activation_string in ACTaFN:
		return ACTaFN[activation_string]
	else:
		raise KeyError(F'''function {activation_string} not found in ACT2FN mapping {list(ACTaFN.keys()							)}'''							)


# For backwards compatibility with: from activations import gelu_python
lowerCAmelCase_						   =			get_activation("gelu_python")
lowerCAmelCase_						   =			get_activation("gelu_new")
lowerCAmelCase_						   =			get_activation("gelu")
lowerCAmelCase_						   =			get_activation("gelu_fast")
lowerCAmelCase_						   =			get_activation("quick_gelu")
lowerCAmelCase_						   =			get_activation("silu")
lowerCAmelCase_						   =			get_activation("mish")


lowerCAmelCase_						   =			get_activation("linear")








'''simple docstring'''

import os

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

lowerCAmelCase_						   =			{"UserAgent": UserAgent().random}
lowerCAmelCase_						   =			"https://www.mywaifulist.moe/random"

def     __magic_name__       ( A					,   A							)			->		None:
	snake_case							 =				requests.get(A					,   headers=A							)
	with open(A					,   'wb'							) as file:
		file.write(image.content							)

def     __magic_name__       ( )			->		tuple[str, str, str]:
	snake_case							 =				BeautifulSoup(requests.get(A					,   headers=A							).text					,   'html.parser'							)
	snake_case							 =				soup.find('meta'					,   attrs={'property': 'og:title'}							).attrs['content']
	snake_case							 =				soup.find('meta'					,   attrs={'property': 'og:image'}							).attrs['content']
	snake_case							 =				soup.find('p'					,   id='description'							).get_text()
	snake_case , snake_case							 =				os.path.splitext(os.path.basename(A							)							)
	snake_case							 =				title.strip().replace(' '					,   '_'							)
	snake_case							 =				F'''{image_title}{image_extension}'''
	save_image(A					,   A							)
	return (title, description, image_title)


if __name__ == "__main__":
						lowerCAmelCase_   ,	lowerCAmelCase_   ,	lowerCAmelCase_						   =			random_anime_character()
						print(f"{title}\n\n{desc}\n\nImage saved : {image_title}")





