





import argparse
import os
import re

import packaging.version


UpperCAmelCase_  							=				'examples/'
UpperCAmelCase_  							=				{
    'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
    'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__version__ = "VERSION"\n'),
    'setup': (re.compile(R'^(\s*)version\s*=\s*"[^"]+",', re.MULTILINE), R'\1version="VERSION",'),
    'doc': (re.compile(R'^(\s*)release\s*=\s*"[^"]+"$', re.MULTILINE), 'release = "VERSION"\n'),
}
UpperCAmelCase_  							=				{
    'init': 'src/diffusers/__init__.py',
    'setup': 'setup.py',
}
UpperCAmelCase_  							=				'README.md'




def 	lowerCAmelCase_					(						__UpperCAmelCase:    List[Any]	,     __UpperCAmelCase:    Union[str, Any]	,     __UpperCAmelCase:    Optional[Any]   )   ->			Dict:
    with open(__UpperCAmelCase	,     '''r'''	,     encoding='''utf-8'''	,     newline='''\n'''   ) as f:
        UpperCamelCase__							:       List[Any]      =   f.read()
    UpperCamelCase__     ,UpperCamelCase__							:       int      =   REPLACE_PATTERNS[pattern]
    UpperCamelCase__							:       Dict      =   replace.replace('''VERSION'''	,     __UpperCAmelCase   )
    UpperCamelCase__							:       int      =   re_pattern.sub(__UpperCAmelCase	,     __UpperCAmelCase   )
    with open(__UpperCAmelCase	,     '''w'''	,     encoding='''utf-8'''	,     newline='''\n'''   ) as f:
        f.write(__UpperCAmelCase   )




def 	lowerCAmelCase_					(						__UpperCAmelCase:    List[Any]   )   ->			Dict:
    for folder, directories, fnames in os.walk(__UpperCAmelCase   ):
        # Removing some of the folders with non-actively maintained examples from the walk
        if "research_projects" in directories:
            directories.remove('''research_projects'''   )
        if "legacy" in directories:
            directories.remove('''legacy'''   )
        for fname in fnames:
            if fname.endswith('''.py'''   ):
                update_version_in_file(os.path.join(__UpperCAmelCase	,     __UpperCAmelCase   )	,     __UpperCAmelCase	,     pattern='''examples'''   )




def 	lowerCAmelCase_					(						__UpperCAmelCase:    Optional[int]	,     __UpperCAmelCase:    int=False   )   ->			Tuple:
    for pattern, fname in REPLACE_FILES.items():
        update_version_in_file(__UpperCAmelCase	,     __UpperCAmelCase	,     __UpperCAmelCase   )
    if not patch:
        update_version_in_examples(__UpperCAmelCase   )




def 	lowerCAmelCase_					(						)   ->			Optional[Any]:
    UpperCamelCase__							:       int      =   '''🤗 Transformers currently provides the following architectures'''
    UpperCamelCase__							:       Any      =   '''1. Want to contribute a new model?'''
    with open(__UpperCAmelCase	,     '''r'''	,     encoding='''utf-8'''	,     newline='''\n'''   ) as f:
        UpperCamelCase__							:       List[Any]      =   f.readlines()

    # Find the start of the list.
    UpperCamelCase__							:       Optional[Any]      =   0
    while not lines[start_index].startswith(_start_prompt   ):
        start_index += 1
    start_index += 1

    UpperCamelCase__							:       Union[str, Any]      =   start_index
    # Update the lines in the model list.
    while not lines[index].startswith(_end_prompt   ):
        if lines[index].startswith('''1.'''   ):
            UpperCamelCase__							:       Union[str, Any]      =   lines[index].replace(
                '''https://huggingface.co/docs/diffusers/main/model_doc'''	,     '''https://huggingface.co/docs/diffusers/model_doc'''	,     )
        index += 1

    with open(__UpperCAmelCase	,     '''w'''	,     encoding='''utf-8'''	,     newline='''\n'''   ) as f:
        f.writelines(__UpperCAmelCase   )




def 	lowerCAmelCase_					(						)   ->			Optional[int]:
    with open(REPLACE_FILES['''init''']	,     '''r'''   ) as f:
        UpperCamelCase__							:       Optional[int]      =   f.read()
    UpperCamelCase__							:       Dict      =   REPLACE_PATTERNS['''init'''][0].search(__UpperCAmelCase   ).groups()[0]
    return packaging.version.parse(__UpperCAmelCase   )




def 	lowerCAmelCase_					(						__UpperCAmelCase:    Tuple=False   )   ->			int:
    UpperCamelCase__							:       List[str]      =   get_version()
    if patch and default_version.is_devrelease:
        raise ValueError('''Can\'t create a patch version from the dev branch, checkout a released version!'''   )
    if default_version.is_devrelease:
        UpperCamelCase__							:       int      =   default_version.base_version
    elif patch:
        UpperCamelCase__							:       int      =   f"{default_version.major}.{default_version.minor}.{default_version.micro + 1}"
    else:
        UpperCamelCase__							:       Tuple      =   f"{default_version.major}.{default_version.minor + 1}.0"

    # Now let's ask nicely if that's the right one.
    UpperCamelCase__							:       Optional[int]      =   input(f"Which version are you releasing? [{default_version}]"   )
    if len(__UpperCAmelCase   ) == 0:
        UpperCamelCase__							:       Optional[int]      =   default_version

    print(f"Updating version to {version}."   )
    global_version_update(__UpperCAmelCase	,     patch=__UpperCAmelCase   )




def 	lowerCAmelCase_					(						)   ->			Optional[Any]:
    UpperCamelCase__							:       Dict      =   get_version()
    UpperCamelCase__							:       Union[str, Any]      =   f"{current_version.major}.{current_version.minor + 1}.0.dev0"
    UpperCamelCase__							:       Optional[Any]      =   current_version.base_version

    # Check with the user we got that right.
    UpperCamelCase__							:       str      =   input(f"Which version are we developing now? [{dev_version}]"   )
    if len(__UpperCAmelCase   ) == 0:
        UpperCamelCase__							:       List[Any]      =   dev_version

    print(f"Updating version to {version}."   )
    global_version_update(__UpperCAmelCase   )


#    print("Cleaning main README, don't forget to run `make fix-copies`.")
#    clean_main_ref_in_model_list()


if __name__ == "__main__":
  UpperCAmelCase_  							=				argparse.ArgumentParser()
  parser.add_argument('--post_release', action='store_true', help='Whether this is pre or post release.')
  parser.add_argument('--patch', action='store_true', help='Whether or not this is a patch release.')
  UpperCAmelCase_  							=				parser.parse_args()
  if not args.post_release:
    pre_release_work(patch=args.patch)
  elif args.patch:
    print('Nothing to do after a patch :-)')
  else:
    post_release_work()








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


UpperCAmelCase_  							=				False






class 					lowercase__ (			unittest.TestCase       ):

   '''simple docstring'''


   pass






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

   '''simple docstring'''


   def    UpperCamelCase__						(					self							)				->   Optional[Any]:






       """simple docstring"""
       # clean up the VRAM after each test
       super().tearDown()
       gc.collect()
       torch.cuda.empty_cache()




   def    UpperCamelCase__						(					self							)				->   List[Any]:






       """simple docstring"""
       UpperCamelCase__							:       Dict      =   VersatileDiffusionTextToImagePipeline.from_pretrained('''shi-labs/versatile-diffusion'''							)
       # remove text_unet
       pipe.remove_unused_weights()
       pipe.to(__magic_name__							)
       pipe.set_progress_bar_config(disable=__magic_name__							)

       UpperCamelCase__							:       int      =   '''A painting of a squirrel eating a burger '''
       UpperCamelCase__							:       str      =   torch.manual_seed(0							)
       UpperCamelCase__							:       int      =   pipe(
           prompt=__magic_name__,	generator=__magic_name__,	guidance_scale=7.5,	num_inference_steps=2,	output_type='''numpy'''							).images

       with tempfile.TemporaryDirectory() as tmpdirname:
           pipe.save_pretrained(__magic_name__							)
           UpperCamelCase__							:       Union[str, Any]      =   VersatileDiffusionTextToImagePipeline.from_pretrained(__magic_name__							)
       pipe.to(__magic_name__							)
       pipe.set_progress_bar_config(disable=__magic_name__							)

       UpperCamelCase__							:       Optional[Any]      =   generator.manual_seed(0							)
       UpperCamelCase__							:       str      =   pipe(
           prompt=__magic_name__,	generator=__magic_name__,	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							)				->   Any:






       """simple docstring"""
       UpperCamelCase__							:       str      =   VersatileDiffusionTextToImagePipeline.from_pretrained(
           '''shi-labs/versatile-diffusion''',	torch_dtype=torch.floataa							)
       pipe.to(__magic_name__							)
       pipe.set_progress_bar_config(disable=__magic_name__							)

       UpperCamelCase__							:       Optional[int]      =   '''A painting of a squirrel eating a burger '''
       UpperCamelCase__							:       str      =   torch.manual_seed(0							)
       UpperCamelCase__							:       Optional[int]      =   pipe(
           prompt=__magic_name__,	generator=__magic_name__,	guidance_scale=7.5,	num_inference_steps=50,	output_type='''numpy'''							).images

       UpperCamelCase__							:       int      =   image[0, 253:256, 253:256, -1]

       assert image.shape == (1, 512, 512, 3)
       UpperCamelCase__							:       int      =   np.array([0.3367, 0.3169, 0.2656, 0.3870, 0.4790, 0.3796, 0.4009, 0.4878, 0.4778]							)

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

