





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
__A							   =							'src/diffusers'

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


__A							   =							'\n{0} = None\n'

__A							   =							'\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'


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





def 	lowerCAmelCase_					(			__a						)	->						List[str]:







  """simple docstring"""





  lowerCamelCase__: int         =_re_backend.findall(lowerCAmelCase__						)
  if len(lowerCAmelCase__						) == 0:
    return None

  return "_and_".join(lowerCAmelCase__						)





def 	lowerCAmelCase_					(			)	->						Tuple:







  """simple docstring"""





  with open(os.path.join(lowerCAmelCase__      ,       "__init__.py"						)      ,       "r"      ,       encoding="utf-8"      ,       newline="\n"						) as f:
    lowerCamelCase__: str         =f.readlines()

  # Get to the point we do the actual imports for type checking
  lowerCamelCase__: Dict         =0
  lowerCamelCase__: int         ={}
  # Go through the end of the file
  while line_index < len(lowerCAmelCase__						):
    # If the line contains is_backend_available, we grab all objects associated with the `else` block
    lowerCamelCase__: List[Any]         =find_backend(lines[line_index]						)
    if backend is not None:
      while not lines[line_index].startswith("else:"						):
        line_index += 1
      line_index += 1
      lowerCamelCase__: Tuple         =[]
      # Until we unindent, add backend objects to the list
      while line_index < len(lowerCAmelCase__						) and len(lines[line_index]						) > 1:
        lowerCamelCase__: int         =lines[line_index]
        lowerCamelCase__: List[str]         =_re_single_line_import.search(lowerCAmelCase__						)
        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(lowerCAmelCase__						) > 0:
        lowerCamelCase__: Optional[Any]         =objects
    else:
      line_index += 1

  return backend_specific_objects





def 	lowerCAmelCase_					(			__a      ,       __a						)	->						Dict:







  """simple docstring"""





  if name.isupper():
    return DUMMY_CONSTANT.format(lowerCAmelCase__						)
  elif name.islower():
    return DUMMY_FUNCTION.format(lowerCAmelCase__      ,       lowerCAmelCase__						)
  else:
    return DUMMY_CLASS.format(lowerCAmelCase__      ,       lowerCAmelCase__						)





def 	lowerCAmelCase_					(			__a=None						)	->						int:







  """simple docstring"""





  if backend_specific_objects is None:
    lowerCamelCase__: Dict         =read_init()
  # For special correspondence backend to module name as used in the function requires_modulename
  lowerCamelCase__: int         ={}

  for backend, objects in backend_specific_objects.items():
    lowerCamelCase__: List[str]         ="[" + ", ".join(F"""\"{b}\"""" for b in backend.split("_and_"						)						) + "]"
    lowerCamelCase__: Dict         ="# 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(lowerCAmelCase__      ,       lowerCAmelCase__						) for o in objects]						)
    lowerCamelCase__: Tuple         =dummy_file

  return dummy_files





def 	lowerCAmelCase_					(			__a=False						)	->						Any:







  """simple docstring"""





  lowerCamelCase__: Optional[Any]         =create_dummy_files()
  # For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
  lowerCamelCase__: Optional[Any]         ={"torch": "pt"}

  # Locate actual dummy modules and read their content.
  lowerCamelCase__: Optional[Any]         =os.path.join(lowerCAmelCase__      ,       "utils"						)
  lowerCamelCase__: Any         ={
      backend: os.path.join(lowerCAmelCase__      ,       F"""dummy_{short_names.get(lowerCAmelCase__      ,       lowerCAmelCase__						)}_objects.py"""						)
      for backend in dummy_files.keys()
  }

  lowerCamelCase__: Optional[int]         ={}
  for backend, file_path in dummy_file_paths.items():
    if os.path.isfile(lowerCAmelCase__						):
      with open(lowerCAmelCase__      ,       "r"      ,       encoding="utf-8"      ,       newline="\n"						) as f:
        lowerCamelCase__: Union[str, Any]         =f.read()
    else:
      lowerCamelCase__: List[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(lowerCAmelCase__      ,       lowerCAmelCase__						)}_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(lowerCAmelCase__      ,       lowerCAmelCase__						)}_objects.py. Run `make fix-copies` """
            "to fix this."						)


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

     check_dummies(args.fix_and_overwrite)






from typing import List

import numpy as np






def  lowerCamelCase_	(      lowerCAmelCase__	:	dict				)       ->							int:

							'''simple docstring'''






							A      						=    {key: len(lowerCAmelCase__				) for key, value in gen_kwargs.items() if isinstance(lowerCAmelCase__			,	lowerCAmelCase__				)}
							if len(set(lists_lengths.values()				)				) > 1:
														raise RuntimeError(
														    (
														        'Sharding is ambiguous for this dataset: '
														        + 'we found several data sources lists of different lengths, and we don\'t know over which list we should parallelize:\n'
														        + '\n'.join(F'''\t- key {key} has length {length}''' for key, length in lists_lengths.items()				)
														        + '\nTo fix this, check the \'gen_kwargs\' and make sure to use lists only for data sources, '
														        + 'and use tuples otherwise. In the end there should only be one single list, or several lists with the same length.'
														    )				)
							A      						=    max(lists_lengths.values()			,	default=0				)
							return max(1			,	lowerCAmelCase__				)






def  lowerCamelCase_	(      lowerCAmelCase__	:	int			,	lowerCAmelCase__	:	int				)       ->							List[range]:

							'''simple docstring'''






							A      						=    []
							for group_idx in range(lowerCAmelCase__				):
														A      						=    num_shards // max_num_jobs + (group_idx < (num_shards % max_num_jobs))
														if num_shards_to_add == 0:
																					break
														A      						=    shards_indices_per_group[-1].stop if shards_indices_per_group else 0
														A      						=    range(lowerCAmelCase__			,	start + num_shards_to_add				)
														shards_indices_per_group.append(lowerCAmelCase__				)
							return shards_indices_per_group






def  lowerCamelCase_	(      lowerCAmelCase__	:	dict			,	lowerCAmelCase__	:	int				)       ->							List[dict]:

							'''simple docstring'''






							A      						=    _number_of_shards_in_gen_kwargs(lowerCAmelCase__				)
							if num_shards == 1:
														return [dict(lowerCAmelCase__				)]
							else:
														A      						=    _distribute_shards(num_shards=lowerCAmelCase__			,	max_num_jobs=lowerCAmelCase__				)
														return [
														    {
														        key: [value[shard_idx] for shard_idx in shard_indices_per_group[group_idx]]
														        if isinstance(lowerCAmelCase__			,	lowerCAmelCase__				)
														        else value
														        for key, value in gen_kwargs.items()
														    }
														    for group_idx in range(len(lowerCAmelCase__				)				)
														]






def  lowerCamelCase_	(      lowerCAmelCase__	:	List[dict]				)       ->							dict:

							'''simple docstring'''






							return {
							    key: [value for gen_kwargs in gen_kwargs_list for value in gen_kwargs[key]]
							    if isinstance(gen_kwargs_list[0][key]			,	lowerCAmelCase__				)
							    else gen_kwargs_list[0][key]
							    for key in gen_kwargs_list[0]
							}






def  lowerCamelCase_	(      lowerCAmelCase__	:	np.random.Generator			,	lowerCAmelCase__	:	dict				)       ->							dict:

							'''simple docstring'''






							A      						=    {len(lowerCAmelCase__				) for value in gen_kwargs.values() if isinstance(lowerCAmelCase__			,	lowerCAmelCase__				)}
							A      						=    {}
							for size in list_sizes:
														A      						=    list(range(lowerCAmelCase__				)				)
														rng.shuffle(indices_per_size[size]				)
							# Now let's copy the gen_kwargs and shuffle the lists based on their sizes
							A      						=    dict(lowerCAmelCase__				)
							for key, value in shuffled_kwargs.items():
														if isinstance(lowerCAmelCase__			,	lowerCAmelCase__				):
																					A      						=    [value[i] for i in indices_per_size[len(lowerCAmelCase__				)]]
							return shuffled_kwargs