'''simple docstring'''

import gc
import tempfile
import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device


A_     :						Optional[Any]    							=False


class     __UpperCAmelCase       ( unittest.TestCase		):
  pass






@nightly
@require_torch_gpu
class     __UpperCAmelCase       ( unittest.TestCase		):





  def 						UpperCAmelCase_	(	self ):
     # clean up the VRAM after each test
     super().tearDown()
     gc.collect()
     torch.cuda.empty_cache()





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      VersatileDiffusionTextToImagePipeline.from_pretrained('''shi-labs/versatile-diffusion''' )
     # remove text_unet
     pipe.remove_unused_weights()
     pipe.to(_lowerCamelCase )
     pipe.set_progress_bar_config(disable=_lowerCamelCase )

     lowerCAmelCase_			=      '''A painting of a squirrel eating a burger '''
     lowerCAmelCase_			=      torch.manual_seed(0 )
     lowerCAmelCase_			=      pipe(
         prompt=_lowerCamelCase    ,     generator=_lowerCamelCase    ,     guidance_scale=7.5    ,     num_inference_steps=2    ,     output_type='''numpy''' ).images

     with tempfile.TemporaryDirectory() as tmpdirname:
        pipe.save_pretrained(_lowerCamelCase )
        lowerCAmelCase_			=      VersatileDiffusionTextToImagePipeline.from_pretrained(_lowerCamelCase )
     pipe.to(_lowerCamelCase )
     pipe.set_progress_bar_config(disable=_lowerCamelCase )

     lowerCAmelCase_			=      generator.manual_seed(0 )
     lowerCAmelCase_			=      pipe(
         prompt=_lowerCamelCase    ,     generator=_lowerCamelCase    ,     guidance_scale=7.5    ,     num_inference_steps=2    ,     output_type='''numpy''' ).images

     assert np.abs(image - new_image ).sum() < 1E-5, "Models don't have the same forward pass"







  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      VersatileDiffusionTextToImagePipeline.from_pretrained(
         '''shi-labs/versatile-diffusion'''    ,     torch_dtype=torch.floataa )
     pipe.to(_lowerCamelCase )
     pipe.set_progress_bar_config(disable=_lowerCamelCase )

     lowerCAmelCase_			=      '''A painting of a squirrel eating a burger '''
     lowerCAmelCase_			=      torch.manual_seed(0 )
     lowerCAmelCase_			=      pipe(
         prompt=_lowerCamelCase    ,     generator=_lowerCamelCase    ,     guidance_scale=7.5    ,     num_inference_steps=50    ,     output_type='''numpy''' ).images

     lowerCAmelCase_			=      image[0, 253:256, 253:256, -1]

     assert image.shape == (1, 512, 512, 3)
     lowerCAmelCase_			=      np.array([0.33_67, 0.31_69, 0.26_56, 0.38_70, 0.47_90, 0.37_96, 0.40_09, 0.48_78, 0.47_78] )

     assert np.abs(image_slice.flatten() - expected_slice ).max() < 1E-2






'''simple docstring'''

import math
import sys



def snake_case_      (					__snake_case  :							str)			->					str:
   lowerCAmelCase_			=      ''''''
   try:
      with open(__snake_case	,   '''rb''') as binary_file:
         lowerCAmelCase_			=      binary_file.read()
      for dat in data:
         lowerCAmelCase_			=      F'''{dat:08b}'''
         result += curr_byte
      return result
   except OSError:
      print('''File not accessible''')
      sys.exit()



def snake_case_      (					__snake_case  :							str)			->					str:
   lowerCAmelCase_			=      {'''0''': '''0''', '''1''': '''1'''}
   lowerCAmelCase_	,lowerCAmelCase_			=      '''''', ''''''
   lowerCAmelCase_			=      len(__snake_case)

   for i in range(len(__snake_case)):
      curr_string += data_bits[i]
      if curr_string not in lexicon:
         continue

      lowerCAmelCase_			=      lexicon[curr_string]
      result += last_match_id
      lowerCAmelCase_			=      last_match_id + '''0'''

      if math.loga(__snake_case).is_integer():
         lowerCAmelCase_			=      {}
         for curr_key in list(__snake_case):
            lowerCAmelCase_			=      lexicon.pop(__snake_case)
         lowerCAmelCase_			=      new_lex

      lowerCAmelCase_			=      last_match_id + '''1'''
      index += 1
      lowerCAmelCase_			=      ''''''
   return result



def snake_case_      (					__snake_case  :							str	,   __snake_case  :							str)			->					None:
   lowerCAmelCase_			=      8
   try:
      with open(__snake_case	,   '''wb''') as opened_file:
         lowerCAmelCase_			=      [
             to_write[i : i + byte_length]
             for i in range(0	,   len(__snake_case)	,   __snake_case)
         ]

         if len(result_byte_array[-1]) % byte_length == 0:
            result_byte_array.append('''10000000''')
         else:
            result_byte_array[-1] += "1" + "0" * (
                byte_length - len(result_byte_array[-1]) - 1
            )

         for elem in result_byte_array[:-1]:
            opened_file.write(int(__snake_case	,   2).to_bytes(1	,   byteorder='''big'''))
   except OSError:
      print('''File not accessible''')
      sys.exit()



def snake_case_      (					__snake_case  :							str)			->					str:
   lowerCAmelCase_			=      0
   for letter in data_bits:
      if letter == "1":
         break
      counter += 1

   lowerCAmelCase_			=      data_bits[counter:]
   lowerCAmelCase_			=      data_bits[counter + 1 :]
   return data_bits



def snake_case_      (					__snake_case  :							str	,   __snake_case  :							str)			->					None:
   lowerCAmelCase_			=      read_file_binary(__snake_case)
   lowerCAmelCase_			=      remove_prefix(__snake_case)
   lowerCAmelCase_			=      decompress_data(__snake_case)
   write_file_binary(__snake_case	,   __snake_case)


if __name__ == "__main__":
 compress(sys.argv[1], sys.argv[2])





