






'''simple docstring'''



import argparse
import glob
import importlib.util
import os
import re

import black
from doc_builder.style_doc import style_docstrings_in_code


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
SCREAMING_SNAKE_CASE						=	'src/diffusers'
SCREAMING_SNAKE_CASE						=	'.'


# This is to make sure the diffusers module imported is the one in the repo.
SCREAMING_SNAKE_CASE						=	importlib.util.spec_from_file_location(
    'diffusers',
    os.path.join(DIFFUSERS_PATH, '__init__.py'),
    submodule_search_locations=[DIFFUSERS_PATH],
)
SCREAMING_SNAKE_CASE						=	spec.loader.load_module()


def 							lowercase_				(    __A :       int					,      __A :       Dict			)       ->      Optional[int]:



 """simple docstring"""




 return line.startswith(__A			) or len(__A			) <= 1 or re.search(R'''^\s*\)(\s*->.*:|:)\s*$'''					,      __A			) is not None


def 							lowercase_				(    __A :       str			)       ->      str:



 """simple docstring"""




 lowercase					:   List[Any]				  =object_name.split('''.'''			)
 lowercase					:   Union[str, Any]				  =0

 # First let's find the module where our object lives.
 lowercase					:   Dict				  =parts[i]
 while i < len(__A			) and not os.path.isfile(os.path.join(__A					,      F'{module}.py'			)			):
  i += 1
  if i < len(__A			):
   lowercase					:   Dict				  =os.path.join(__A					,      parts[i]			)
 if i >= len(__A			):
  raise ValueError(F'`object_name` should begin with the name of a module of diffusers but got {object_name}.'			)

 with open(os.path.join(__A					,      F'{module}.py'			)					,      '''r'''					,      encoding='''utf-8'''					,      newline='''\n'''			) as f:
  lowercase					:   Tuple				  =f.readlines()

 # Now let's find the class / func in the code!
 lowercase					:   Union[str, Any]				  =''''''
 lowercase					:   Union[str, Any]				  =0
 for name in parts[i + 1 :]:
  while (
      line_index < len(__A			) and re.search(RF'^{indent}(class|def)\s+{name}(\(|\:)'					,      lines[line_index]			) is None
  ):
   line_index += 1
  indent += "    "
  line_index += 1

 if line_index >= len(__A			):
  raise ValueError(F' {object_name} does not match any function or class in {module}.'			)

 # We found the beginning of the class / func, now let's find the end (when the indent diminishes).
 lowercase					:   Any				  =line_index
 while line_index < len(__A			) and _should_continue(lines[line_index]					,      __A			):
  line_index += 1
 # Clean up empty lines at the end (if any).
 while len(lines[line_index - 1]			) <= 1:
  line_index -= 1

 lowercase					:   Union[str, Any]				  =lines[start_index:line_index]
 return "".join(__A			)


SCREAMING_SNAKE_CASE						=	re.compile(r'^(\s*)#\s*Copied from\s+diffusers\.(\S+\.\S+)\s*($|\S.*$)')
SCREAMING_SNAKE_CASE						=	re.compile(r'^\s*(\S+)->(\S+)(\s+.*|$)')
SCREAMING_SNAKE_CASE						=	re.compile(r'<FILL\s+[^>]*>')


def 							lowercase_				(    __A :       Optional[int]			)       ->      int:



 """simple docstring"""




 lowercase					:   int				  =code.split('''\n'''			)
 lowercase					:   Optional[int]				  =0
 while idx < len(__A			) and len(lines[idx]			) == 0:
  idx += 1
 if idx < len(__A			):
  return re.search(R'''^(\s*)\S'''					,      lines[idx]			).groups()[0]
 return ""


def 							lowercase_				(    __A :       Dict			)       ->      List[str]:



 """simple docstring"""




 lowercase					:   Union[str, Any]				  =len(get_indent(__A			)			) > 0
 if has_indent:
  lowercase					:   str				  =F'class Bla:\n{code}'
 lowercase					:   List[str]				  =black.Mode(target_versions={black.TargetVersion.PYaa}					,      line_length=1_1_9					,      preview=__A			)
 lowercase					:   int				  =black.format_str(__A					,      mode=__A			)
 lowercase  ,		lowercase					:   Dict				  =style_docstrings_in_code(__A			)
 return result[len('''class Bla:\n'''			) :] if has_indent else result


def 							lowercase_				(    __A :       Tuple					,      __A :       Dict=False			)       ->      Union[str, Any]:



 """simple docstring"""




 with open(__A					,      '''r'''					,      encoding='''utf-8'''					,      newline='''\n'''			) as f:
  lowercase					:   Optional[int]				  =f.readlines()
 lowercase					:   int				  =[]
 lowercase					:   Optional[Any]				  =0
 # Not a for loop cause `lines` is going to change (if `overwrite=True`).
 while line_index < len(__A			):
  lowercase					:   int				  =_re_copy_warning.search(lines[line_index]			)
  if search is None:
   line_index += 1
   continue

  # There is some copied code here, let's retrieve the original.
  lowercase  ,		lowercase  ,		lowercase					:   Dict				  =search.groups()
  lowercase					:   Dict				  =find_code_in_diffusers(__A			)
  lowercase					:   Dict				  =get_indent(__A			)

  lowercase					:   List[str]				  =line_index + 1 if indent == theoretical_indent else line_index + 2
  lowercase					:   Any				  =theoretical_indent
  lowercase					:   Dict				  =start_index

  # Loop to check the observed code, stop when indentation diminishes or if we see a End copy comment.
  lowercase					:   List[Any]				  =True
  while line_index < len(__A			) and should_continue:
   line_index += 1
   if line_index >= len(__A			):
    break
   lowercase					:   Tuple				  =lines[line_index]
   lowercase					:   Optional[Any]				  =_should_continue(__A					,      __A			) and re.search(F'^{indent}# End copy'					,      __A			) is None
  # Clean up empty lines at the end (if any).
  while len(lines[line_index - 1]			) <= 1:
   line_index -= 1

  lowercase					:   Any				  =lines[start_index:line_index]
  lowercase					:   List[str]				  =''''''.join(__A			)

  # Remove any nested `Copied from` comments to avoid circular copies
  lowercase					:   List[Any]				  =[line for line in theoretical_code.split('''\n'''			) if _re_copy_warning.search(__A			) is None]
  lowercase					:   Tuple				  ='''\n'''.join(__A			)

  # Before comparing, use the `replace_pattern` on the original code.
  if len(__A			) > 0:
   lowercase					:   List[str]				  =replace_pattern.replace('''with'''					,      ''''''			).split(''','''			)
   lowercase					:   List[Any]				  =[_re_replace_pattern.search(__A			) for p in patterns]
   for pattern in patterns:
    if pattern is None:
     continue
    lowercase  ,		lowercase  ,		lowercase					:   List[str]				  =pattern.groups()
    lowercase					:   Union[str, Any]				  =re.sub(__A					,      __A					,      __A			)
    if option.strip() == "all-casing":
     lowercase					:   str				  =re.sub(obja.lower()					,      obja.lower()					,      __A			)
     lowercase					:   Dict				  =re.sub(obja.upper()					,      obja.upper()					,      __A			)

            # Blackify after replacement. To be able to do that, we need the header (class or function definition)
            # from the previous line
   lowercase					:   str				  =blackify(lines[start_index - 1] + theoretical_code			)
   lowercase					:   Union[str, Any]				  =theoretical_code[len(lines[start_index - 1]			) :]

  # Test for a diff and act accordingly.
  if observed_code != theoretical_code:
   diffs.append([object_name, start_index]			)
   if overwrite:
    lowercase					:   Any				  =lines[:start_index] + [theoretical_code] + lines[line_index:]
    lowercase					:   int				  =start_index + 1

 if overwrite and len(__A			) > 0:
  # Warn the user a file has been modified.
  print(F'Detected changes, rewriting {filename}.'			)
  with open(__A					,      '''w'''					,      encoding='''utf-8'''					,      newline='''\n'''			) as f:
   f.writelines(__A			)
 return diffs


def 							lowercase_				(    __A :       bool = False			)       ->      Optional[Any]:



 """simple docstring"""




 lowercase					:   int				  =glob.glob(os.path.join(__A					,      '''**/*.py'''			)					,      recursive=__A			)
 lowercase					:   List[Any]				  =[]
 for filename in all_files:
  lowercase					:   Any				  =is_copy_consistent(__A					,      __A			)
  diffs += [F'- {filename}: copy does not match {d[0]} at line {d[1]}' for d in new_diffs]
 if not overwrite and len(__A			) > 0:
  lowercase					:   Optional[int]				  ='''\n'''.join(__A			)
  raise Exception(
      '''Found the following copy inconsistencies:\n'''
      + diff
      + '''\nRun `make fix-copies` or `python utils/check_copies.py --fix_and_overwrite` to fix them.'''			)


if __name__ == "__main__":
      SCREAMING_SNAKE_CASE						=	argparse.ArgumentParser()
      parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
      SCREAMING_SNAKE_CASE						=	parser.parse_args()

      check_copies(args.fix_and_overwrite)











'''simple docstring'''



import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    IMAGE_PROCESSOR_MAPPING,
    AutoConfig,
    AutoImageProcessor,
    CLIPConfig,
    CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER


sys.path.append(str(Path(__file__).parent.parent.parent.parent / 'utils'))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_image_processing import CustomImageProcessor  # noqa E402
class UpperCAmelCase_					(    unittest.TestCase				):




      """simple docstring"""




      def 				A__      ( self			:		int		)  ->  Any:


       '''simple docstring'''

       lowercase					:   Union[str, Any]				  =0






      def 				A__      ( self			:		str		)  ->  Union[str, Any]:


       '''simple docstring'''

       lowercase					:   Tuple				  =AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''		)
       self.assertIsInstance(UpperCAmelCase     ,      UpperCAmelCase		)






      def 				A__      ( self			:		Any		)  ->  int:


       '''simple docstring'''

       with tempfile.TemporaryDirectory() as tmpdirname:
        lowercase					:   int				  =Path(UpperCAmelCase		) / '''preprocessor_config.json'''
        lowercase					:   str				  =Path(UpperCAmelCase		) / '''config.json'''
        json.dump(
            {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}     ,      open(UpperCAmelCase     ,      '''w'''		)     ,      )
        json.dump({'''model_type''': '''clip'''}     ,      open(UpperCAmelCase     ,      '''w'''		)		)

        lowercase					:   str				  =AutoImageProcessor.from_pretrained(UpperCAmelCase		)
        self.assertIsInstance(UpperCAmelCase     ,      UpperCAmelCase		)






      def 				A__      ( self			:		Any		)  ->  Union[str, Any]:


       '''simple docstring'''

       with tempfile.TemporaryDirectory() as tmpdirname:
        lowercase					:   int				  =Path(UpperCAmelCase		) / '''preprocessor_config.json'''
        lowercase					:   int				  =Path(UpperCAmelCase		) / '''config.json'''
        json.dump(
            {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}     ,      open(UpperCAmelCase     ,      '''w'''		)     ,      )
        json.dump({'''model_type''': '''clip'''}     ,      open(UpperCAmelCase     ,      '''w'''		)		)

        lowercase					:   Optional[Any]				  =AutoImageProcessor.from_pretrained(UpperCAmelCase		)
        self.assertIsInstance(UpperCAmelCase     ,      UpperCAmelCase		)






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


       '''simple docstring'''

       with tempfile.TemporaryDirectory() as tmpdirname:
        lowercase					:   str				  =CLIPConfig()

        # Create a dummy config file with image_proceesor_type
        lowercase					:   Optional[int]				  =Path(UpperCAmelCase		) / '''preprocessor_config.json'''
        lowercase					:   Optional[Any]				  =Path(UpperCAmelCase		) / '''config.json'''
        json.dump(
            {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}     ,      open(UpperCAmelCase     ,      '''w'''		)     ,      )
        json.dump({'''model_type''': '''clip'''}     ,      open(UpperCAmelCase     ,      '''w'''		)		)

        # remove image_processor_type to make sure config.json alone is enough to load image processor locally
        lowercase					:   Dict				  =AutoImageProcessor.from_pretrained(UpperCAmelCase		).to_dict()

        config_dict.pop('''image_processor_type'''		)
        lowercase					:   str				  =CLIPImageProcessor(**UpperCAmelCase		)

        # save in new folder
        model_config.save_pretrained(UpperCAmelCase		)
        config.save_pretrained(UpperCAmelCase		)

        lowercase					:   Optional[int]				  =AutoImageProcessor.from_pretrained(UpperCAmelCase		)

        # make sure private variable is not incorrectly saved
        lowercase					:   int				  =json.loads(config.to_json_string()		)
        self.assertTrue('''_processor_class''' not in dict_as_saved		)

       self.assertIsInstance(UpperCAmelCase     ,      UpperCAmelCase		)






      def 				A__      ( self			:		str		)  ->  List[str]:


       '''simple docstring'''

       with tempfile.TemporaryDirectory() as tmpdirname:
        lowercase					:   Dict				  =Path(UpperCAmelCase		) / '''preprocessor_config.json'''
        json.dump(
            {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}     ,      open(UpperCAmelCase     ,      '''w'''		)     ,      )

        lowercase					:   Optional[Any]				  =AutoImageProcessor.from_pretrained(UpperCAmelCase		)
        self.assertIsInstance(UpperCAmelCase     ,      UpperCAmelCase		)






      def 				A__      ( self			:		int		)  ->  List[str]:


       '''simple docstring'''

       with self.assertRaisesRegex(
           UpperCAmelCase     ,      '''clip-base is not a local folder and is not a valid model identifier'''		):
        lowercase					:   Union[str, Any]				  =AutoImageProcessor.from_pretrained('''clip-base'''		)






      def 				A__      ( self			:		List[Any]		)  ->  List[str]:


       '''simple docstring'''

       with self.assertRaisesRegex(
           UpperCAmelCase     ,      R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''		):
        lowercase					:   Any				  =AutoImageProcessor.from_pretrained(UpperCAmelCase     ,      revision='''aaaaaa'''		)






      def 				A__      ( self			:		Tuple		)  ->  Optional[int]:


       '''simple docstring'''

       with self.assertRaisesRegex(
           UpperCAmelCase     ,      '''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'''     ,      ):
        lowercase					:   Optional[int]				  =AutoImageProcessor.from_pretrained('''hf-internal-testing/config-no-model'''		)






      def 				A__      ( self			:		List[str]		)  ->  str:


       '''simple docstring'''

       with self.assertRaises(UpperCAmelCase		):
        lowercase					:   Dict				  =AutoImageProcessor.from_pretrained('''hf-internal-testing/test_dynamic_image_processor'''		)
       # If remote code is disabled, we can't load this config.
       with self.assertRaises(UpperCAmelCase		):
        lowercase					:   List[str]				  =AutoImageProcessor.from_pretrained(
            '''hf-internal-testing/test_dynamic_image_processor'''     ,      trust_remote_code=UpperCAmelCase		)

       lowercase					:   Union[str, Any]				  =AutoImageProcessor.from_pretrained(
           '''hf-internal-testing/test_dynamic_image_processor'''     ,      trust_remote_code=UpperCAmelCase		)
       self.assertEqual(image_processor.__class__.__name__     ,      '''NewImageProcessor'''		)

       # Test image processor can be reloaded.
       with tempfile.TemporaryDirectory() as tmp_dir:
        image_processor.save_pretrained(UpperCAmelCase		)
        lowercase					:   Any				  =AutoImageProcessor.from_pretrained(UpperCAmelCase     ,      trust_remote_code=UpperCAmelCase		)
       self.assertEqual(reloaded_image_processor.__class__.__name__     ,      '''NewImageProcessor'''		)






      def 				A__      ( self			:		Union[str, Any]		)  ->  Dict:


       '''simple docstring'''

       try:
        AutoConfig.register('''custom'''     ,      UpperCAmelCase		)
        AutoImageProcessor.register(UpperCAmelCase     ,      UpperCAmelCase		)
        # Trying to register something existing in the Transformers library will raise an error
        with self.assertRaises(UpperCAmelCase		):
         AutoImageProcessor.register(UpperCAmelCase     ,      UpperCAmelCase		)

        with tempfile.TemporaryDirectory() as tmpdirname:
         lowercase					:   Any				  =Path(UpperCAmelCase		) / '''preprocessor_config.json'''
         lowercase					:   str				  =Path(UpperCAmelCase		) / '''config.json'''
         json.dump(
             {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}     ,      open(UpperCAmelCase     ,      '''w'''		)     ,      )
         json.dump({'''model_type''': '''clip'''}     ,      open(UpperCAmelCase     ,      '''w'''		)		)

         lowercase					:   Optional[int]				  =CustomImageProcessor.from_pretrained(UpperCAmelCase		)

        # Now that the config is registered, it can be used as any other config with the auto-API
        with tempfile.TemporaryDirectory() as tmp_dir:
         image_processor.save_pretrained(UpperCAmelCase		)
         lowercase					:   Dict				  =AutoImageProcessor.from_pretrained(UpperCAmelCase		)
         self.assertIsInstance(UpperCAmelCase     ,      UpperCAmelCase		)

       finally:
        if "custom" in CONFIG_MAPPING._extra_content:
         del CONFIG_MAPPING._extra_content["custom"]
        if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
         del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]






      def 				A__      ( self			:		Any		)  ->  Any:


       '''simple docstring'''

       class UpperCAmelCase_					(    __A				):




             """simple docstring"""




             UpperCamelCase_								=			True

       try:
        AutoConfig.register('''custom'''     ,      UpperCAmelCase		)
        AutoImageProcessor.register(UpperCAmelCase     ,      UpperCAmelCase		)
        # If remote code is not set, the default is to use local
        lowercase					:   List[str]				  =AutoImageProcessor.from_pretrained('''hf-internal-testing/test_dynamic_image_processor'''		)
        self.assertEqual(image_processor.__class__.__name__     ,      '''NewImageProcessor'''		)
        self.assertTrue(image_processor.is_local		)

        # If remote code is disabled, we load the local one.
        lowercase					:   Tuple				  =AutoImageProcessor.from_pretrained(
            '''hf-internal-testing/test_dynamic_image_processor'''     ,      trust_remote_code=UpperCAmelCase		)
        self.assertEqual(image_processor.__class__.__name__     ,      '''NewImageProcessor'''		)
        self.assertTrue(image_processor.is_local		)

        # If remote is enabled, we load from the Hub
        lowercase					:   Dict				  =AutoImageProcessor.from_pretrained(
            '''hf-internal-testing/test_dynamic_image_processor'''     ,      trust_remote_code=UpperCAmelCase		)
        self.assertEqual(image_processor.__class__.__name__     ,      '''NewImageProcessor'''		)
        self.assertTrue(not hasattr(UpperCAmelCase     ,      '''is_local'''		)		)

       finally:
        if "custom" in CONFIG_MAPPING._extra_content:
         del CONFIG_MAPPING._extra_content["custom"]
        if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
         del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]



