

import numpy as np
import torch
from imwatermark import WatermarkEncoder


# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowercase_             = 0B10_11_00_11_11_10_11_00_10_01_00_00_01_11_10_11_10_11_00_01_10_01_11_10
# bin(x)[2:] gives bits of x as str, use int to convert them to 0/1
lowercase_             = [int(bit) for bit in bin(WATERMARK_MESSAGE)[2:]]





class 				__lowerCAmelCase  :




  def __init__(       self      )						->				List[Any]:
        '''simple docstring'''






        _lowercase			 =WATERMARK_BITS
        _lowercase			 =WatermarkEncoder()

        self.encoder.set_watermark('bits'							,     self.watermark      )




  def 						A__  (       self							,     lowerCAmelCase      )						->				int:
        '''simple docstring'''






        if images.shape[-1] < 256:
              return images

        _lowercase			 =(255 * (images / 2 + 0.5)).cpu().permute(0							,     2							,     3							,     1      ).float().numpy()

        _lowercase			 =[self.encoder.encode(_UpperCAmelCase							,     'dwtDct'      ) for image in images]

        _lowercase			 =torch.from_numpy(np.array(_UpperCAmelCase      )      ).permute(0							,     3							,     1							,     2      )

        _lowercase			 =torch.clamp(2 * (images / 255 - 0.5)							,     min=-1.0							,     max=1.0      )
        return images





import requests

lowercase_             =     'YOUR API KEY'
def   a   (    A__			:     str   ,     A__			:     str = giphy_api_key  )					->   list:





      """simple docstring"""



      _lowercase			 ='+'.join(query.split()  )
      _lowercase			 =F'''https://api.giphy.com/v1/gifs/search?q={formatted_query}&api_key={api_key}'''
      _lowercase			 =requests.get(A__  ).json()['data']
      return [gif["url"] for gif in gifs]


if __name__ == "__main__":
  print('\n'.join(get_gifs('space ship')))


