





"""simple docstring"""
import argparse
import os
import re


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

# Matches is_xxx_available()
lowerCamelCase_								=		re.compile(r"is\_([a-z_]*)_available\(\)")
# Matches from xxx import bla
lowerCamelCase_								=		re.compile(r"\s+from\s+\S*\s+import\s+([^\(\s].*)\n")


lowerCamelCase_								=		"\n{0} = None\n"

lowerCamelCase_								=		"\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n"


lowerCamelCase_								=		"\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n"



def      __lowerCamelCase   (							a_     :		str							)			->      Optional[int]:
      __SCREAMING_SNAKE_CASE   :List[str]						=  _re_backend.findall(a_							)
      if len(a_							) == 0:
            return None

      return "_and_".join(a_							)



def      __lowerCamelCase   (							)			->      Dict:
      with open(os.path.join(a_ ,   '''__init__.py'''							) ,   '''r''' ,   encoding='''utf-8''' ,   newline='''\n'''							) as f:
            __SCREAMING_SNAKE_CASE   :Dict						=  f.readlines()

      # Get to the point we do the actual imports for type checking
      __SCREAMING_SNAKE_CASE   :Optional[int]						=  0
      __SCREAMING_SNAKE_CASE   :Optional[Any]						=  {}
      # Go through the end of the file
      while line_index < len(a_							):
            # If the line contains is_backend_available, we grab all objects associated with the `else` block
            __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  find_backend(lines[line_index]							)
            if backend is not None:
                  while not lines[line_index].startswith('''else:'''							):
                        line_index += 1
                  line_index += 1
                  __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  []
                  # Until we unindent, add backend objects to the list
                  while line_index < len(a_							) and len(lines[line_index]							) > 1:
                        __SCREAMING_SNAKE_CASE   :Optional[Any]						=  lines[line_index]
                        __SCREAMING_SNAKE_CASE   :Optional[Any]						=  _re_single_line_import.search(a_							)
                        if single_line_import_search is not None:
                              objects.extend(single_line_import_search.groups()[0].split(''', '''							)							)
                        elif line.startswith(''' ''' * 8							):
                              objects.append(line[8:-2]							)
                        line_index += 1

                  if len(a_							) > 0:
                        __SCREAMING_SNAKE_CASE   :str						=  objects
            else:
                  line_index += 1

      return backend_specific_objects



def      __lowerCamelCase   (							a_     :		Optional[int] ,   a_     :		int							)			->      Dict:
      if name.isupper():
            return DUMMY_CONSTANT.format(a_							)
      elif name.islower():
            return DUMMY_FUNCTION.format(a_ ,   a_							)
      else:
            return DUMMY_CLASS.format(a_ ,   a_							)



def      __lowerCamelCase   (							a_     :		Optional[int]=None							)			->      List[str]:
      if backend_specific_objects is None:
            __SCREAMING_SNAKE_CASE   :Dict						=  read_init()
      # For special correspondence backend to module name as used in the function requires_modulename
      __SCREAMING_SNAKE_CASE   :List[str]						=  {}

      for backend, objects in backend_specific_objects.items():
            __SCREAMING_SNAKE_CASE   :List[Any]						=  '''[''' + ''', '''.join(f'''"{b}"''' for b in backend.split('''_and_'''							)							) + ''']'''
            __SCREAMING_SNAKE_CASE   :Tuple						=  '''# This file is autogenerated by the command `make fix-copies`, do not edit.\n'''
            dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
            dummy_file += "\n".join([create_dummy_object(a_ ,   a_							) for o in objects]							)
            __SCREAMING_SNAKE_CASE   :Optional[int]						=  dummy_file

      return dummy_files



def      __lowerCamelCase   (							a_     :		Dict=False							)			->      List[str]:
      __SCREAMING_SNAKE_CASE   :List[Any]						=  create_dummy_files()
      # For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
      __SCREAMING_SNAKE_CASE   :Optional[Any]						=  {'''torch''': '''pt'''}

      # Locate actual dummy modules and read their content.
      __SCREAMING_SNAKE_CASE   :Tuple						=  os.path.join(a_ ,   '''utils'''							)
      __SCREAMING_SNAKE_CASE   :Dict						=  {
          backend: os.path.join(a_ ,   f'''dummy_{short_names.get(a_ ,   a_							)}_objects.py'''							)
          for backend in dummy_files.keys()
      }

      __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  {}
      for backend, file_path in dummy_file_paths.items():
            if os.path.isfile(a_							):
                  with open(a_ ,   '''r''' ,   encoding='''utf-8''' ,   newline='''\n'''							) as f:
                        __SCREAMING_SNAKE_CASE   :str						=  f.read()
            else:
                  __SCREAMING_SNAKE_CASE   :str						=  ''''''

      for backend in dummy_files.keys():
            if dummy_files[backend] != actual_dummies[backend]:
                  if overwrite:
                        print(
                            f'''Updating diffusers.utils.dummy_{short_names.get(a_ ,   a_							)}_objects.py as the main '''
                            '''__init__ has new objects.'''							)
                        with open(dummy_file_paths[backend] ,   '''w''' ,   encoding='''utf-8''' ,   newline='''\n'''							) as f:
                              f.write(dummy_files[backend]							)
                  else:
                        raise ValueError(
                            '''The main __init__ has objects that are not present in '''
                            f'''diffusers.utils.dummy_{short_names.get(a_ ,   a_							)}_objects.py. Run `make fix-copies` '''
                            '''to fix this.'''							)


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

  check_dummies(args.fix_and_overwrite)






"""simple docstring"""
import argparse
import os

import torch

from transformers import FlavaImageCodebook, FlavaImageCodebookConfig



def      __lowerCamelCase   (							a_     :		str ,   a_     :		Dict ,   a_     :		Any ,   a_     :		str							)			->      str:
      __SCREAMING_SNAKE_CASE   :int						=  s.rsplit(a_ ,   a_							)
      return new.join(a_							)



def      __lowerCamelCase   (							a_     :		List[str]							)			->      Dict:
      # encoder.embeddings are double copied in original FLAVA
      return sum(param.float().sum() if '''encoder.embeddings''' not in key else 0 for key, param in state_dict.items()							)



def      __lowerCamelCase   (							a_     :		Optional[int]							)			->      Any:
      __SCREAMING_SNAKE_CASE   :Optional[int]						=  {}

      __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  ['''group_1''', '''group_2''', '''group_3''', '''group_4''']
      for key, value in state_dict.items():
            for group_key in group_keys:
                  if group_key in key:
                        __SCREAMING_SNAKE_CASE   :Optional[Any]						=  key.replace(f'''{group_key}.''' ,   f'''{group_key}.group.'''							)

            if "res_path" in key:
                  __SCREAMING_SNAKE_CASE   :str						=  key.replace('''res_path.''' ,   '''res_path.path.'''							)

            if key.endswith('''.w'''							):
                  __SCREAMING_SNAKE_CASE   :List[Any]						=  rreplace(a_ ,   '''.w''' ,   '''.weight''' ,   1							)
            if key.endswith('''.b'''							):
                  __SCREAMING_SNAKE_CASE   :List[Any]						=  rreplace(a_ ,   '''.b''' ,   '''.bias''' ,   1							)

            __SCREAMING_SNAKE_CASE   :Optional[Any]						=  value.float()

      return upgrade



@torch.no_grad()
def      __lowerCamelCase   (							a_     :		List[Any] ,   a_     :		Optional[int] ,   a_     :		Optional[int]=None ,   a_     :		Dict=True							)			->      Union[str, Any]:
      from dall_e import Encoder

      __SCREAMING_SNAKE_CASE   :int						=  Encoder()
      if os.path.exists(a_							):
            __SCREAMING_SNAKE_CASE   :Dict						=  torch.load(a_							)
      else:
            __SCREAMING_SNAKE_CASE   :List[str]						=  torch.hub.load_state_dict_from_url(a_							)

      if isinstance(a_ ,   a_							):
            __SCREAMING_SNAKE_CASE   :List[str]						=  ckpt.state_dict()
      encoder.load_state_dict(a_							)

      if config_path is not None:
            __SCREAMING_SNAKE_CASE   :Any						=  FlavaImageCodebookConfig.from_pretrained(a_							)
      else:
            __SCREAMING_SNAKE_CASE   :Optional[int]						=  FlavaImageCodebookConfig()

      __SCREAMING_SNAKE_CASE   :Tuple						=  FlavaImageCodebook(a_							).eval()
      __SCREAMING_SNAKE_CASE   :List[str]						=  encoder.state_dict()

      __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  upgrade_state_dict(a_							)
      hf_model.load_state_dict(a_							)
      __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  hf_model.state_dict()
      __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  count_parameters(a_							)
      __SCREAMING_SNAKE_CASE   :Any						=  count_parameters(a_							)

      assert torch.allclose(a_ ,   a_ ,   atol=1e-3							)

      if save_checkpoint:
            hf_model.save_pretrained(a_							)
      else:
            return hf_state_dict


if __name__ == "__main__":
  lowerCamelCase_								=		argparse.ArgumentParser()
  parser.add_argument("--pytorch_dump_folder_path", default=None, type=str, help="Path to the output PyTorch model.")
  parser.add_argument("--checkpoint_path", default=None, type=str, help="Path to flava checkpoint")
  parser.add_argument("--config_path", default=None, type=str, help="Path to hf config.json of model to convert")
  lowerCamelCase_								=		parser.parse_args()

  convert_dalle_checkpoint(args.checkpoint_path, args.pytorch_dump_folder_path, args.config_path)