"""simple docstring"""





import argparse
import os
import re

import packaging.version


lowerCAmelCase_     			=						'examples/'
lowerCAmelCase_     			=						{
    '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'),
}
lowerCAmelCase_     			=						{
    'init': 'src/diffusers/__init__.py',
    'setup': 'setup.py',
}
lowerCAmelCase_     			=						'README.md'



def   lowerCamelCase_(__SCREAMING_SNAKE_CASE  ,						__SCREAMING_SNAKE_CASE  ,						__SCREAMING_SNAKE_CASE	)->     Tuple:
							with open(UpperCamelCase__  ,						"""r"""  ,						encoding="""utf-8"""  ,						newline="""\n"""	) as f:
														_SCREAMING_SNAKE_CASE		:    Dict      	=     f.read()
							_SCREAMING_SNAKE_CASE	,					_SCREAMING_SNAKE_CASE		:    List[Any]      	=     REPLACE_PATTERNS[pattern]
							_SCREAMING_SNAKE_CASE		:    Dict      	=     replace.replace("""VERSION"""  ,						UpperCamelCase__	)
							_SCREAMING_SNAKE_CASE		:    Optional[int]      	=     re_pattern.sub(UpperCamelCase__  ,						UpperCamelCase__	)
							with open(UpperCamelCase__  ,						"""w"""  ,						encoding="""utf-8"""  ,						newline="""\n"""	) as f:
														f.write(UpperCamelCase__	)



def   lowerCamelCase_(__SCREAMING_SNAKE_CASE	)->     Optional[int]:
							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_(__SCREAMING_SNAKE_CASE  ,						__SCREAMING_SNAKE_CASE=False	)->     int:
							for pattern, fname in REPLACE_FILES.items():
														update_version_in_file(UpperCamelCase__  ,						UpperCamelCase__  ,						UpperCamelCase__	)
							if not patch:
														update_version_in_examples(UpperCamelCase__	)



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

							# Find the start of the list.
							_SCREAMING_SNAKE_CASE		:    List[str]      	=     0
							while not lines[start_index].startswith(_start_prompt	):
														start_index += 1
							start_index += 1

							_SCREAMING_SNAKE_CASE		:    List[Any]      	=     start_index
							# Update the lines in the model list.
							while not lines[index].startswith(_end_prompt	):
														if lines[index].startswith("""1."""	):
																					_SCREAMING_SNAKE_CASE		:    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_()->     Dict:
							with open(REPLACE_FILES["""init"""]  ,						"""r"""	) as f:
														_SCREAMING_SNAKE_CASE		:    Dict      	=     f.read()
							_SCREAMING_SNAKE_CASE		:    Tuple      	=     REPLACE_PATTERNS["""init"""][0].search(UpperCamelCase__	).groups()[0]
							return packaging.version.parse(UpperCamelCase__	)



def   lowerCamelCase_(__SCREAMING_SNAKE_CASE=False	)->     List[Any]:
							_SCREAMING_SNAKE_CASE		:    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:
														_SCREAMING_SNAKE_CASE		:    int      	=     default_version.base_version
							elif patch:
														_SCREAMING_SNAKE_CASE		:    List[Any]      	=     F"""{default_version.major}.{default_version.minor}.{default_version.micro + 1}"""
							else:
														_SCREAMING_SNAKE_CASE		:    List[str]      	=     F"""{default_version.major}.{default_version.minor + 1}.0"""

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

							print(F"""Updating version to {version}."""	)
							global_version_update(UpperCamelCase__  ,						patch=UpperCamelCase__	)



def   lowerCamelCase_()->     List[str]:
							_SCREAMING_SNAKE_CASE		:    Tuple      	=     get_version()
							_SCREAMING_SNAKE_CASE		:    int      	=     F"""{current_version.major}.{current_version.minor + 1}.0.dev0"""
							_SCREAMING_SNAKE_CASE		:    Any      	=     current_version.base_version

							# Check with the user we got that right.
							_SCREAMING_SNAKE_CASE		:    Optional[int]      	=     input(F"""Which version are we developing now? [{dev_version}]"""	)
							if len(UpperCamelCase__	) == 0:
														_SCREAMING_SNAKE_CASE		:    Optional[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__":
			lowerCAmelCase_     			=						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.''')
			lowerCAmelCase_     			=						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 unittest

from huggingface_hub import hf_hub_download

from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_decord,
    require_tf,
    require_torch,
    require_torch_or_tf,
    require_vision,
)

from .test_pipelines_common import ANY




@is_pipeline_test
@require_torch_or_tf
@require_vision
@require_decord
class        SCREAMING_SNAKE_CASE__					(		unittest.TestCase ):
 __SCREAMING_SNAKE_CASE							=      MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING



 def 							UpperCamelCase     (				self,__lowerCamelCase,__lowerCamelCase,__lowerCamelCase					):
        A__		   =		hf_hub_download(
            repo_id='''nateraw/video-demo''',filename='''archery.mp4''',repo_type='''dataset'''					)
        A__		   =		VideoClassificationPipeline(model=__lowerCamelCase,image_processor=__lowerCamelCase,top_k=2					)
        A__		   =		[
            example_video_filepath,
            '''https://huggingface.co/datasets/nateraw/video-demo/resolve/main/archery.mp4''',
        ]
        return video_classifier, examples



 def 							UpperCamelCase     (				self,__lowerCamelCase,__lowerCamelCase					):
        for example in examples:
               A__		   =		video_classifier(__lowerCamelCase					)

               self.assertEqual(
                   __lowerCamelCase,[
                       {'''score''': ANY(__lowerCamelCase					), '''label''': ANY(__lowerCamelCase					)},
                       {'''score''': ANY(__lowerCamelCase					), '''label''': ANY(__lowerCamelCase					)},
                   ],)



 @require_torch
 def 							UpperCamelCase     (				self					):
        A__		   =		'''hf-internal-testing/tiny-random-VideoMAEForVideoClassification'''
        A__		   =		VideoMAEFeatureExtractor(
            size={'''shortest_edge''': 10},crop_size={'''height''': 10, '''width''': 10}					)
        A__		   =		pipeline(
            '''video-classification''',model=__lowerCamelCase,feature_extractor=__lowerCamelCase,frame_sampling_rate=4					)

        A__		   =		hf_hub_download(repo_id='''nateraw/video-demo''',filename='''archery.mp4''',repo_type='''dataset'''					)
        A__		   =		video_classifier(__lowerCamelCase,top_k=2					)
        self.assertEqual(
            nested_simplify(__lowerCamelCase,decimals=4					),[{'''score''': 0.5199, '''label''': '''LABEL_0'''}, {'''score''': 0.4801, '''label''': '''LABEL_1'''}],)

        A__		   =		video_classifier(
            [
                video_file_path,
                video_file_path,
            ],top_k=2,)
        self.assertEqual(
            nested_simplify(__lowerCamelCase,decimals=4					),[
                [{'''score''': 0.5199, '''label''': '''LABEL_0'''}, {'''score''': 0.4801, '''label''': '''LABEL_1'''}],
                [{'''score''': 0.5199, '''label''': '''LABEL_0'''}, {'''score''': 0.4801, '''label''': '''LABEL_1'''}],
            ],)




 @require_tf
 def 							UpperCamelCase     (				self					):
        pass





