


import argparse
import os
import re

import packaging.version


_UpperCAmelCase       : int			     =       """examples/"""
_UpperCAmelCase       : List[str]			     =       {
    """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       : int			     =       {
    """init""": """src/diffusers/__init__.py""",
    """setup""": """setup.py""",
}
_UpperCAmelCase       : str			     =       """README.md"""


def  SCREAMING_SNAKE_CASE   ( _UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase				)    ->  Any:
    with open(_UpperCAmelCase		,			'r'		,			encoding='utf-8'		,			newline='\n'				) as f:
        lowerCamelCase__					:   Union[str, Any]      				=	f.read()
    lowerCamelCase__					:   Tuple      				=	REPLACE_PATTERNS[pattern]
    lowerCamelCase__					:   Any      				=	replace.replace('VERSION'		,			_UpperCAmelCase				)
    lowerCamelCase__					:   Union[str, Any]      				=	re_pattern.sub(_UpperCAmelCase		,			_UpperCAmelCase				)
    with open(_UpperCAmelCase		,			'w'		,			encoding='utf-8'		,			newline='\n'				) as f:
        f.write(_UpperCAmelCase				)


def  SCREAMING_SNAKE_CASE   ( _UpperCAmelCase				)    ->  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  SCREAMING_SNAKE_CASE   ( _UpperCAmelCase		,			_UpperCAmelCase=False				)    ->  Union[str, Any]:
    for pattern, fname in REPLACE_FILES.items():
        update_version_in_file(_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase				)
    if not patch:
        update_version_in_examples(_UpperCAmelCase				)


def  SCREAMING_SNAKE_CASE   ( )    ->  Any:
    lowerCamelCase__					:   Union[str, Any]      				=	'🤗 Transformers currently provides the following architectures'
    lowerCamelCase__					:   int      				=	'1. Want to contribute a new model?'
    with open(_UpperCAmelCase		,			'r'		,			encoding='utf-8'		,			newline='\n'				) as f:
        lowerCamelCase__					:   Tuple      				=	f.readlines()

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

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


def  SCREAMING_SNAKE_CASE   ( _UpperCAmelCase=False				)    ->  Union[str, Any]:
    lowerCamelCase__					:   List[Any]      				=	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:
        lowerCamelCase__					:   Dict      				=	default_version.base_version
    elif patch:
        lowerCamelCase__					:   List[str]      				=	F"""{default_version.major}.{default_version.minor}.{default_version.micro + 1}"""
    else:
        lowerCamelCase__					:   Optional[int]      				=	F"""{default_version.major}.{default_version.minor + 1}.0"""

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

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


def  SCREAMING_SNAKE_CASE   ( )    ->  int:
    lowerCamelCase__					:   str      				=	get_version()
    lowerCamelCase__					:   Any      				=	F"""{current_version.major}.{current_version.minor + 1}.0.dev0"""
    lowerCamelCase__					:   Union[str, Any]      				=	current_version.base_version

    # Check with the user we got that right.
    lowerCamelCase__					:   Dict      				=	input(F"""Which version are we developing now? [{dev_version}]"""				)
    if len(_UpperCAmelCase				) == 0:
        lowerCamelCase__					:   Tuple      				=	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       : int			     =       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       : List[Any]			     =       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 shutil
import tempfile
import unittest

from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio

from .test_feature_extraction_clap import floats_list

@require_torchaudio
@require_sentencepiece
class      lowerCAmelCase							(      unittest.TestCase    ):
 def   A_			(   self						:   str			)    ->			Union[str, Any]:
     lowerCamelCase__					:   Optional[int]      				=	'laion/clap-htsat-unfused'
     lowerCamelCase__					:   List[Any]      				=	tempfile.mkdtemp()
 def   A_			(   self						:   Optional[int]    ,  **UpperCAmelCase						:   int			)    ->			Optional[Any]:
     return RobertaTokenizer.from_pretrained(self.checkpoint    ,  **UpperCAmelCase			)
 def   A_			(   self						:   Union[str, Any]    ,  **UpperCAmelCase						:   Any			)    ->			List[str]:
     return ClapFeatureExtractor.from_pretrained(self.checkpoint    ,  **UpperCAmelCase			)
 def   A_			(   self						:   List[str]			)    ->			Dict:
     shutil.rmtree(self.tmpdirname			)
 def   A_			(   self						:   Optional[Any]			)    ->			Optional[Any]:
     lowerCamelCase__					:   Tuple      				=	self.get_tokenizer()
     lowerCamelCase__					:   Dict      				=	self.get_feature_extractor()

     lowerCamelCase__					:   Dict      				=	ClapProcessor(tokenizer=UpperCAmelCase    ,  feature_extractor=UpperCAmelCase			)

     processor.save_pretrained(self.tmpdirname			)
     lowerCamelCase__					:   List[Any]      				=	ClapProcessor.from_pretrained(self.tmpdirname			)

     self.assertEqual(processor.tokenizer.get_vocab()    ,  tokenizer.get_vocab()			)
     self.assertIsInstance(processor.tokenizer    ,  UpperCAmelCase			)

     self.assertEqual(processor.feature_extractor.to_json_string()    ,  feature_extractor.to_json_string()			)
     self.assertIsInstance(processor.feature_extractor    ,  UpperCAmelCase			)
 def   A_			(   self						:   str			)    ->			int:
     lowerCamelCase__					:   Optional[Any]      				=	ClapProcessor(tokenizer=self.get_tokenizer()    ,  feature_extractor=self.get_feature_extractor()			)
     processor.save_pretrained(self.tmpdirname			)

     lowerCamelCase__					:   Dict      				=	self.get_tokenizer(bos_token='(BOS)'    ,  eos_token='(EOS)'			)
     lowerCamelCase__					:   Dict      				=	self.get_feature_extractor(do_normalize=UpperCAmelCase    ,  padding_value=1.0			)

     lowerCamelCase__					:   str      				=	ClapProcessor.from_pretrained(
         self.tmpdirname    ,  bos_token='(BOS)'    ,  eos_token='(EOS)'    ,  do_normalize=UpperCAmelCase    ,  padding_value=1.0			)

     self.assertEqual(processor.tokenizer.get_vocab()    ,  tokenizer_add_kwargs.get_vocab()			)
     self.assertIsInstance(processor.tokenizer    ,  UpperCAmelCase			)

     self.assertEqual(processor.feature_extractor.to_json_string()    ,  feature_extractor_add_kwargs.to_json_string()			)
     self.assertIsInstance(processor.feature_extractor    ,  UpperCAmelCase			)
 def   A_			(   self						:   List[Any]			)    ->			int:
     lowerCamelCase__					:   Any      				=	self.get_feature_extractor()
     lowerCamelCase__					:   str      				=	self.get_tokenizer()

     lowerCamelCase__					:   Optional[Any]      				=	ClapProcessor(tokenizer=UpperCAmelCase    ,  feature_extractor=UpperCAmelCase			)

     lowerCamelCase__					:   Optional[Any]      				=	floats_list((3, 1000)			)

     lowerCamelCase__					:   Tuple      				=	feature_extractor(UpperCAmelCase    ,  return_tensors='np'			)
     lowerCamelCase__					:   Tuple      				=	processor(audios=UpperCAmelCase    ,  return_tensors='np'			)

     for key in input_feat_extract.keys():
         self.assertAlmostEqual(input_feat_extract[key].sum()    ,  input_processor[key].sum()    ,  delta=1e-2			)
 def   A_			(   self						:   List[str]			)    ->			Tuple:
     lowerCamelCase__					:   Dict      				=	self.get_feature_extractor()
     lowerCamelCase__					:   List[Any]      				=	self.get_tokenizer()

     lowerCamelCase__					:   Any      				=	ClapProcessor(tokenizer=UpperCAmelCase    ,  feature_extractor=UpperCAmelCase			)

     lowerCamelCase__					:   Union[str, Any]      				=	'This is a test string'

     lowerCamelCase__					:   Union[str, Any]      				=	processor(text=UpperCAmelCase			)

     lowerCamelCase__					:   Any      				=	tokenizer(UpperCAmelCase			)

     for key in encoded_tok.keys():
         self.assertListEqual(encoded_tok[key]    ,  encoded_processor[key]			)
 def   A_			(   self						:   Optional[int]			)    ->			Tuple:
     lowerCamelCase__					:   Tuple      				=	self.get_feature_extractor()
     lowerCamelCase__					:   List[str]      				=	self.get_tokenizer()

     lowerCamelCase__					:   Optional[int]      				=	ClapProcessor(tokenizer=UpperCAmelCase    ,  feature_extractor=UpperCAmelCase			)

     lowerCamelCase__					:   int      				=	[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

     lowerCamelCase__					:   List[Any]      				=	processor.batch_decode(UpperCAmelCase			)
     lowerCamelCase__					:   Tuple      				=	tokenizer.batch_decode(UpperCAmelCase			)

     self.assertListEqual(UpperCAmelCase    ,  UpperCAmelCase			)







 def   A_			(   self						:   Optional[Any]			)    ->			int:
     lowerCamelCase__					:   str      				=	self.get_feature_extractor()
     lowerCamelCase__					:   str      				=	self.get_tokenizer()

     lowerCamelCase__					:   Dict      				=	ClapProcessor(tokenizer=UpperCAmelCase    ,  feature_extractor=UpperCAmelCase			)

     self.assertListEqual(
         processor.model_input_names[2:]    ,  feature_extractor.model_input_names    ,  msg='`processor` and `feature_extractor` model input names do not match'    ,  )





