


"""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
UpperCAmelCase    :     Optional[Any]   						=		'src/diffusers'

# Matches is_xxx_available()
UpperCAmelCase    :     int   						=		re.compile(R'is\_([a-z_]*)_available\(\)')
# Matches from xxx import bla
UpperCAmelCase    :     Union[str, Any]   						=		re.compile(R'\s+from\s+\S*\s+import\s+([^\(\s].*)\n')


UpperCAmelCase    :     Union[str, Any]   						=		'\n{0} = None\n'

UpperCAmelCase    :     Any   						=		'\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'


UpperCAmelCase    :     int   						=		'\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n'
def      lowerCamelCase       (     _UpperCamelCase		:      int							)		->       str:

							'''simple docstring'''



							__UpperCAmelCase   :						Any      							=					_re_backend.findall(_UpperCamelCase							)
							if len(_UpperCamelCase							) == 0:
														return None

							return "_and_".join(_UpperCamelCase							)
def      lowerCamelCase       (     )		->       Tuple:

							'''simple docstring'''



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

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

							return backend_specific_objects
def      lowerCamelCase       (     _UpperCamelCase		:      List[str]       ,			_UpperCamelCase		:      List[Any]							)		->       Tuple:

							'''simple docstring'''



							if name.isupper():
														return DUMMY_CONSTANT.format(_UpperCamelCase							)
							elif name.islower():
														return DUMMY_FUNCTION.format(_UpperCamelCase       ,			_UpperCamelCase							)
							else:
														return DUMMY_CLASS.format(_UpperCamelCase       ,			_UpperCamelCase							)
def      lowerCamelCase       (     _UpperCamelCase		:      List[Any]=None							)		->       Optional[Any]:

							'''simple docstring'''



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

							for backend, objects in backend_specific_objects.items():
														__UpperCAmelCase   :						Optional[Any]      							=					"""[""" + """, """.join(f'''"{b}"''' for b in backend.split("""_and_"""							)							) + """]"""
														__UpperCAmelCase   :						List[Any]      							=					"""# 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(_UpperCamelCase       ,			_UpperCamelCase							) for o in objects]							)
														__UpperCAmelCase   :						Any      							=					dummy_file

							return dummy_files
def      lowerCamelCase       (     _UpperCamelCase		:      Any=False							)		->       str:

							'''simple docstring'''



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

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

							__UpperCAmelCase   :						Any      							=					{}
							for backend, file_path in dummy_file_paths.items():
														if os.path.isfile(_UpperCamelCase							):
																					with open(_UpperCamelCase       ,			"""r"""       ,			encoding="""utf-8"""       ,			newline="""\n"""							) as f:
																												__UpperCAmelCase   :						Any      							=					f.read()
														else:
																					__UpperCAmelCase   :						Tuple      							=					""""""

							for backend in dummy_files.keys():
														if dummy_files[backend] != actual_dummies[backend]:
																					if overwrite:
																												print(
																												    f'''Updating diffusers.utils.dummy_{short_names.get(_UpperCamelCase       ,			_UpperCamelCase							)}_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(_UpperCamelCase       ,			_UpperCamelCase							)}_objects.py. Run `make fix-copies` '''
																												    """to fix this."""							)


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

							check_dummies(args.fix_and_overwrite)




"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase    :     Any   						=		{
    'configuration_blenderbot': [
        'BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BlenderbotConfig',
        'BlenderbotOnnxConfig',
    ],
    'tokenization_blenderbot': ['BlenderbotTokenizer'],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase    :     Optional[int]   						=		['BlenderbotTokenizerFast']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase    :     Optional[Any]   						=		[
							    'BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'BlenderbotForCausalLM',
							    'BlenderbotForConditionalGeneration',
							    'BlenderbotModel',
							    'BlenderbotPreTrainedModel',
							]


try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase    :     Optional[int]   						=		[
							    'TFBlenderbotForConditionalGeneration',
							    'TFBlenderbotModel',
							    'TFBlenderbotPreTrainedModel',
							]


try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase    :     Optional[int]   						=		[
							    'FlaxBlenderbotForConditionalGeneration',
							    'FlaxBlenderbotModel',
							    'FlaxBlenderbotPreTrainedModel',
							]


if TYPE_CHECKING:
							from .configuration_blenderbot import (
							    BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    BlenderbotConfig,
							    BlenderbotOnnxConfig,
							)
							from .tokenization_blenderbot import BlenderbotTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_blenderbot import (
														    BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BlenderbotForCausalLM,
														    BlenderbotForConditionalGeneration,
														    BlenderbotModel,
														    BlenderbotPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_blenderbot import (
														    TFBlenderbotForConditionalGeneration,
														    TFBlenderbotModel,
														    TFBlenderbotPreTrainedModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_blenderbot import (
														    FlaxBlenderbotForConditionalGeneration,
														    FlaxBlenderbotModel,
														    FlaxBlenderbotPreTrainedModel,
														)

else:
							import sys

							UpperCAmelCase    :     Any   						=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
