

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
__snake_case							:			Optional[int]      		= """src/transformers"""

# Matches is_xxx_available()
__snake_case							:			Dict      		= re.compile(r"""is\_([a-z_]*)_available()""")
# Matches from xxx import bla
__snake_case							:			str      		= re.compile(r"""\s+from\s+\S*\s+import\s+([^\(\s].*)\n""")
__snake_case							:			Any      		= re.compile(r"""^\s+if\s+not\s+\(?is\_[a-z_]*\_available\(\)""")


__snake_case							:			Dict      		= """
{0} = None
"""

__snake_case							:			List[Any]      		= """
class {0}(metaclass=DummyObject):
    _backends = {1}

    def __init__(self, *args, **kwargs):
        requires_backends(self, {1})
"""


__snake_case							:			Tuple      		= """
def {0}(*args, **kwargs):
    requires_backends({0}, {1})
"""


def 				_UpperCAmelCase							(	a__):

			'''simple docstring'''



			if _re_test_backend.search(a__) is None:
						return None
			a_	:	Optional[Any]          =   [b[0] for b in _re_backend.findall(a__)]
			backends.sort()
			return "_and_".join(a__)


def 				_UpperCAmelCase							(	):

			'''simple docstring'''



			with open(os.path.join(a__     ,  """__init__.py""")     ,  """r"""     ,  encoding="""utf-8"""     ,  newline="""\n""") as f:
						a_	:	List[Any]          =   f.readlines()

			# Get to the point we do the actual imports for type checking
			a_	:	Dict          =   0
			while not lines[line_index].startswith("""if TYPE_CHECKING"""):
						line_index += 1

			a_	:	List[str]          =   {}
			# Go through the end of the file
			while line_index < len(a__):
						# If the line is an if is_backend_available, we grab all objects associated.
						a_	:	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

									a_	:	str          =   []
									# Until we unindent, add backend objects to the list
									while len(lines[line_index]) <= 1 or lines[line_index].startswith(""" """ * 8):
												a_	:	Optional[int]          =   lines[line_index]
												a_	:	Tuple          =   _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(""" """ * 1_2):
															objects.append(line[1_2:-2])
												line_index += 1

									a_	:	List[Any]          =   objects
						else:
									line_index += 1

			return backend_specific_objects


def 				_UpperCAmelCase							(	a__     ,  a__):

			'''simple docstring'''



			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 				_UpperCAmelCase							(	a__=None):

			'''simple docstring'''



			if backend_specific_objects is None:
						a_	:	Tuple          =   read_init()
			# For special correspondence backend to module name as used in the function requires_modulename
			a_	:	List[Any]          =   {}

			for backend, objects in backend_specific_objects.items():
						a_	:	Dict          =   """[""" + """, """.join(f'''"{b}"''' for b in backend.split("""_and_""")) + """]"""
						a_	:	int          =   """# 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])
						a_	:	int          =   dummy_file

			return dummy_files


def 				_UpperCAmelCase							(	a__=False):

			'''simple docstring'''



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

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

			a_	:	str          =   {}
			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:
												a_	:	int          =   f.read()
						else:
									a_	:	Optional[int]          =   """"""

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


if __name__ == "__main__":
	__snake_case							:			Union[str, Any]      		= argparse.ArgumentParser()
	parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
	__snake_case							:			Union[str, Any]      		= parser.parse_args()

	check_dummies(args.fix_and_overwrite)





import copy
from typing import Dict

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
from ..bit import BitConfig


__snake_case							:			int      		= logging.get_logger(__name__)

__snake_case							:			Dict      		= {
    """google/vit-hybrid-base-bit-384""": """https://huggingface.co/vit-hybrid-base-bit-384/resolve/main/config.json""",
    # See all ViT hybrid models at https://huggingface.co/models?filter=vit
}



class 					A__(a_       ):
						"""simple docstring"""






						_A						:							Dict									= '''vit-hybrid'''





						def __init__(						self     ,			_lowercase=None     ,			_lowercase=768     ,			_lowercase=12     ,			_lowercase=12     ,			_lowercase=3_072     ,			_lowercase="gelu"     ,			_lowercase=0.0     ,			_lowercase=0.0     ,			_lowercase=0.0_2     ,			_lowercase=1e-12     ,			_lowercase=224     ,			_lowercase=1     ,			_lowercase=3     ,			_lowercase=[1, 1_024, 24, 24]     ,			_lowercase=True     ,			**_lowercase     ,			)    ->   Tuple:
									super().__init__(**_lowercase						)

									if backbone_config is None:
												logger.info("""`backbone_config` is `None`. Initializing the config with a `BiT` backbone."""						)
												a_	:	Union[str, Any]          =   {
												    """global_padding""": """same""",
												    """layer_type""": """bottleneck""",
												    """depths""": [3, 4, 9],
												    """out_features""": ["""stage3"""],
												    """embedding_dynamic_padding""": True,
												}

									if isinstance(_lowercase     ,			_lowercase						):
												if "model_type" in backbone_config:
															a_	:	Any          =   CONFIG_MAPPING[backbone_config["""model_type"""]]
												else:
															logger.info(
															    """`model_type` is not found in `backbone_config`. Use `Bit` as the backbone configuration class."""						)
															a_	:	Optional[int]          =   BitConfig
												a_	:	Dict          =   backbone_config_class(**_lowercase						)

									a_	:	List[str]          =   backbone_featmap_shape
									a_	:	int          =   backbone_config
									a_	:	Union[str, Any]          =   hidden_size
									a_	:	Optional[int]          =   num_hidden_layers
									a_	:	Dict          =   num_attention_heads
									a_	:	Optional[int]          =   intermediate_size
									a_	:	Dict          =   hidden_act
									a_	:	Optional[Any]          =   hidden_dropout_prob
									a_	:	List[str]          =   attention_probs_dropout_prob
									a_	:	Tuple          =   initializer_range
									a_	:	Any          =   layer_norm_eps
									a_	:	List[Any]          =   image_size
									a_	:	Optional[Any]          =   patch_size
									a_	:	Optional[Any]          =   num_channels
									a_	:	str          =   qkv_bias





						def  UpperCamelCase__				(						self						)    ->   Dict[str, any]:
									a_	:	List[str]          =   copy.deepcopy(self.__dict__						)
									a_	:	Optional[int]          =   self.backbone_config.to_dict()
									a_	:	List[str]          =   self.__class__.model_type
									return output


