

import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple

import numpy as np

from .import_utils import is_flax_available, is_tf_available, is_torch_available, is_torch_fx_proxy


if is_flax_available():
	import jax.numpy as jnp



class     _a						(__magic_name__				):


					'''simple docstring'''






					def __get__( self    ,       A__    ,       A__=None			):
						# See docs.python.org/3/howto/descriptor.html#properties
						if obj is None:
							return self
						if self.fget is None:
							raise AttributeError("""unreadable attribute"""			)
						A__							:    List[str]        =		"""__cached_""" + self.fget.__name__
						A__							:    List[Any]        =		getattr(A__    ,       A__    ,       A__			)
						if cached is None:
							A__							:    Optional[int]        =		self.fget(A__			)
							setattr(A__    ,       A__    ,       A__			)
						return cached



def 						UpperCamelCase					(lowercase_: Any					)     ->      List[Any]:
	A__							:    List[Any]        =		val.lower()
	if val in {"y", "yes", "t", "true", "on", "1"}:
		return 1
	if val in {"n", "no", "f", "false", "off", "0"}:
		return 0
	raise ValueError(f"""invalid truth value {val!r}"""					)

def 						UpperCamelCase					(lowercase_: Optional[int]					)     ->      Dict:
	if is_torch_fx_proxy(lowercase_					):
		return True
	if is_torch_available():
		import torch

		if isinstance(lowercase_    ,      torch.Tensor					):
			return True
	if is_tf_available():
		import tensorflow as tf

		if isinstance(lowercase_    ,      tf.Tensor					):
			return True

	if is_flax_available():
		import jax.numpy as jnp
		from jax.core import Tracer

		if isinstance(lowercase_    ,      (jnp.ndarray, Tracer)					):
			return True

	return isinstance(lowercase_    ,      np.ndarray					)

def 						UpperCamelCase					(lowercase_: Dict					)     ->      Tuple:
	return isinstance(lowercase_    ,      np.ndarray					)

def 						UpperCamelCase					(lowercase_: Tuple					)     ->      Optional[int]:
	return _is_numpy(lowercase_					)

def 						UpperCamelCase					(lowercase_: Union[str, Any]					)     ->      Any:
	import torch

	return isinstance(lowercase_    ,      torch.Tensor					)

def 						UpperCamelCase					(lowercase_: List[str]					)     ->      List[Any]:
	return False if not is_torch_available() else _is_torch(lowercase_					)

def 						UpperCamelCase					(lowercase_: List[str]					)     ->      List[str]:
	import torch

	return isinstance(lowercase_    ,      torch.device					)

def 						UpperCamelCase					(lowercase_: Optional[Any]					)     ->      int:
	return False if not is_torch_available() else _is_torch_device(lowercase_					)

def 						UpperCamelCase					(lowercase_: Tuple					)     ->      Any:
	import torch

	if isinstance(lowercase_    ,      lowercase_					):
		if hasattr(lowercase_    ,      lowercase_					):
			A__							:    Union[str, Any]        =		getattr(lowercase_    ,      lowercase_					)
		else:
			return False
	return isinstance(lowercase_    ,      torch.dtype					)

def 						UpperCamelCase					(lowercase_: Union[str, Any]					)     ->      int:
	return False if not is_torch_available() else _is_torch_dtype(lowercase_					)

def 						UpperCamelCase					(lowercase_: Union[str, Any]					)     ->      Any:
	import tensorflow as tf

	return isinstance(lowercase_    ,      tf.Tensor					)

def 						UpperCamelCase					(lowercase_: List[str]					)     ->      Optional[Any]:
	return False if not is_tf_available() else _is_tensorflow(lowercase_					)

def 						UpperCamelCase					(lowercase_: Any					)     ->      int:
	import tensorflow as tf

	# the `is_symbolic_tensor` predicate is only available starting with TF 2.14
	if hasattr(lowercase_    ,      """is_symbolic_tensor"""					):
		return tf.is_symbolic_tensor(lowercase_					)
	return type(lowercase_					) == tf.Tensor

def 						UpperCamelCase					(lowercase_: Any					)     ->      int:
	return False if not is_tf_available() else _is_tf_symbolic_tensor(lowercase_					)

def 						UpperCamelCase					(lowercase_: Dict					)     ->      Any:
	import jax.numpy as jnp  # noqa: F811

	return isinstance(lowercase_    ,      jnp.ndarray					)

def 						UpperCamelCase					(lowercase_: Any					)     ->      Optional[Any]:
	return False if not is_flax_available() else _is_jax(lowercase_					)

def 						UpperCamelCase					(lowercase_: Optional[int]					)     ->      int:
	if isinstance(lowercase_    ,      (dict, UserDict)					):
		return {k: to_py_obj(lowercase_					) for k, v in obj.items()}
	elif isinstance(lowercase_    ,      (list, tuple)					):
		return [to_py_obj(lowercase_					) for o in obj]
	elif is_tf_tensor(lowercase_					):
		return obj.numpy().tolist()
	elif is_torch_tensor(lowercase_					):
		return obj.detach().cpu().tolist()
	elif is_jax_tensor(lowercase_					):
		return np.asarray(lowercase_					).tolist()
	elif isinstance(lowercase_    ,      (np.ndarray, np.number)					):  # tolist also works on 0d np arrays
		return obj.tolist()
	else:
		return obj

def 						UpperCamelCase					(lowercase_: Any					)     ->      Any:
	if isinstance(lowercase_    ,      (dict, UserDict)					):
		return {k: to_numpy(lowercase_					) for k, v in obj.items()}
	elif isinstance(lowercase_    ,      (list, tuple)					):
		return np.array(lowercase_					)
	elif is_tf_tensor(lowercase_					):
		return obj.numpy()
	elif is_torch_tensor(lowercase_					):
		return obj.detach().cpu().numpy()
	elif is_jax_tensor(lowercase_					):
		return np.asarray(lowercase_					)
	else:
		return obj



class     _a						(__magic_name__				):


					'''simple docstring'''






					def   __A			( self			):
						A__							:    Optional[int]        =		fields(self			)

						# Safety and consistency checks
						if not len(A__			):
							raise ValueError(F"""{self.__class__.__name__} has no fields."""			)
						if not all(field.default is None for field in class_fields[1:]			):
							raise ValueError(F"""{self.__class__.__name__} should not have more than one required field."""			)

						A__							:    Optional[Any]        =		getattr(self    ,       class_fields[0].name			)
						A__							:    Dict        =		all(getattr(self    ,       field.name			) is None for field in class_fields[1:]			)

						if other_fields_are_none and not is_tensor(A__			):
							if isinstance(A__    ,       A__			):
								A__							:    Dict        =		first_field.items()
								A__							:    Union[str, Any]        =		True
							else:
								try:
									A__							:    Union[str, Any]        =		iter(A__			)
									A__							:    int        =		True
								except TypeError:
									A__							:    Any        =		False

            # if we provided an iterator as first field and the iterator is a (key, value) iterator
            # set the associated fields
							if first_field_iterator:
								for idx, element in enumerate(A__			):
									if (
									    not isinstance(A__    ,       (list, tuple)			)
									    or not len(A__			) == 2
									    or not isinstance(element[0]    ,       A__			)
									):
										if idx == 0:
											# If we do not have an iterator of key/values, set it as attribute
											A__							:    Union[str, Any]        =		first_field
										else:
											# If we have a mixed iterator, raise an error
											raise ValueError(
											    F"""Cannot set key/value for {element}. It needs to be a tuple (key, value)."""			)
										break
									setattr(self    ,       element[0]    ,       element[1]			)
									if element[1] is not None:
										A__							:    int        =		element[1]
							elif first_field is not None:
								A__							:    Union[str, Any]        =		first_field
						else:
							for field in class_fields:
								A__							:    Tuple        =		getattr(self    ,       field.name			)
								if v is not None:
									A__							:    str        =		v






					def __delitem__( self    ,       *A__    ,       **A__			):
						raise Exception(F"""You cannot use ``__delitem__`` on a {self.__class__.__name__} instance."""			)






					def   __A			( self    ,       *A__    ,       **A__			):
						raise Exception(F"""You cannot use ``setdefault`` on a {self.__class__.__name__} instance."""			)






					def   __A			( self    ,       *A__    ,       **A__			):
						raise Exception(F"""You cannot use ``pop`` on a {self.__class__.__name__} instance."""			)






					def   __A			( self    ,       *A__    ,       **A__			):
						raise Exception(F"""You cannot use ``update`` on a {self.__class__.__name__} instance."""			)






					def __getitem__( self    ,       A__			):
						if isinstance(A__    ,       A__			):
							A__							:    Union[str, Any]        =		dict(self.items()			)
							return inner_dict[k]
						else:
							return self.to_tuple()[k]






					def __setattr__( self    ,       A__    ,       A__			):
						if name in self.keys() and value is not None:
							# Don't call self.__setitem__ to avoid recursion errors
							super().__setitem__(A__    ,       A__			)
						super().__setattr__(A__    ,       A__			)






					def __setitem__( self    ,       A__    ,       A__			):
						# Will raise a KeyException if needed
						super().__setitem__(A__    ,       A__			)
						# Don't call self.__setattr__ to avoid recursion errors
						super().__setattr__(A__    ,       A__			)






					def   __A			( self			):
						return tuple(self[k] for k in self.keys()			)



class     _a						(__magic_name__		,   __magic_name__				):


					'''simple docstring'''






					@classmethod
					def   __A			( cls    ,       A__			):
						raise ValueError(
						    F"""{value} is not a valid {cls.__name__}, please select one of {list(cls._valueamember_map_.keys()			)}"""			)



class     _a						(__magic_name__				):


					'''simple docstring'''






					UpperCAmelCase__:   List[str]  							=       '''longest'''
					UpperCAmelCase__:   Optional[int]  							=       '''max_length'''
					UpperCAmelCase__:   List[str]  							=       '''do_not_pad'''



class     _a						(__magic_name__				):


					'''simple docstring'''






					UpperCAmelCase__:   List[Any]  							=       '''pt'''
					UpperCAmelCase__:   Dict  							=       '''tf'''
					UpperCAmelCase__:   Tuple  							=       '''np'''
					UpperCAmelCase__:   List[Any]  							=       '''jax'''



class     _a						:


					'''simple docstring'''






					def __init__( self    ,       A__			):
						A__							:    Any        =		context_managers
						A__							:    Any        =		ExitStack()






					def __enter__( self			):
						for context_manager in self.context_managers:
							self.stack.enter_context(A__			)






					def __exit__( self    ,       *A__    ,       **A__			):
						self.stack.__exit__(*A__    ,       **A__			)



def 						UpperCamelCase					(lowercase_: Dict					)     ->      Dict:
	A__							:    str        =		infer_framework(lowercase_					)
	if framework == "tf":
		A__							:    str        =		inspect.signature(model_class.call					)  # TensorFlow models
	elif framework == "pt":
		A__							:    int        =		inspect.signature(model_class.forward					)  # PyTorch models
	else:
		A__							:    Union[str, Any]        =		inspect.signature(model_class.__call__					)  # Flax models

	for p in signature.parameters:
		if p == "return_loss" and signature.parameters[p].default is True:
			return True

	return False

def 						UpperCamelCase					(lowercase_: Optional[Any]					)     ->      List[Any]:
	A__							:    Optional[int]        =		model_class.__name__
	A__							:    int        =		infer_framework(lowercase_					)
	if framework == "tf":
		A__							:    List[Any]        =		inspect.signature(model_class.call					)  # TensorFlow models
	elif framework == "pt":
		A__							:    Tuple        =		inspect.signature(model_class.forward					)  # PyTorch models
	else:
		A__							:    Optional[int]        =		inspect.signature(model_class.__call__					)  # Flax models

	if "QuestionAnswering" in model_name:
		return [p for p in signature.parameters if "label" in p or p in ("start_positions", "end_positions")]
	else:
		return [p for p in signature.parameters if "label" in p]

def 						UpperCamelCase					(lowercase_: MutableMapping    ,      lowercase_: str = ""    ,      lowercase_: str = "."					)     ->      List[Any]:

	def _flatten_dict(lowercase_: Union[str, Any]    ,      lowercase_: Union[str, Any]=""    ,      lowercase_: List[Any]="."					):
		for k, v in d.items():
			A__							:    List[str]        =		str(lowercase_					) + delimiter + str(lowercase_					) if parent_key else k
			if v and isinstance(lowercase_    ,      lowercase_					):
				yield from flatten_dict(lowercase_    ,      lowercase_    ,      delimiter=lowercase_					).items()
			else:
				yield key, v

	return dict(_flatten_dict(lowercase_    ,      lowercase_    ,      lowercase_					)					)

@contextmanager
def 						UpperCamelCase					(lowercase_: Optional[int]    ,      lowercase_: bool = False					)     ->      Optional[int]:
	if use_temp_dir:
		with tempfile.TemporaryDirectory() as tmp_dir:
			yield tmp_dir
	else:
		yield working_dir

def 						UpperCamelCase					(lowercase_: Optional[Any]    ,      lowercase_: Optional[Any]=None					)     ->      int:
	if is_numpy_array(lowercase_					):
		return np.transpose(lowercase_    ,      axes=lowercase_					)
	elif is_torch_tensor(lowercase_					):
		return array.T if axes is None else array.permute(*lowercase_					)
	elif is_tf_tensor(lowercase_					):
		import tensorflow as tf

		return tf.transpose(lowercase_    ,      perm=lowercase_					)
	elif is_jax_tensor(lowercase_					):
		return jnp.transpose(lowercase_    ,      axes=lowercase_					)
	else:
		raise ValueError(f"""Type not supported for transpose: {type(lowercase_					)}."""					)

def 						UpperCamelCase					(lowercase_: Dict    ,      lowercase_: Union[str, Any]					)     ->      List[str]:
	if is_numpy_array(lowercase_					):
		return np.reshape(lowercase_    ,      lowercase_					)
	elif is_torch_tensor(lowercase_					):
		return array.reshape(*lowercase_					)
	elif is_tf_tensor(lowercase_					):
		import tensorflow as tf

		return tf.reshape(lowercase_    ,      lowercase_					)
	elif is_jax_tensor(lowercase_					):
		return jnp.reshape(lowercase_    ,      lowercase_					)
	else:
		raise ValueError(f"""Type not supported for reshape: {type(lowercase_					)}."""					)

def 						UpperCamelCase					(lowercase_: int    ,      lowercase_: List[str]=None					)     ->      Any:
	if is_numpy_array(lowercase_					):
		return np.squeeze(lowercase_    ,      axis=lowercase_					)
	elif is_torch_tensor(lowercase_					):
		return array.squeeze() if axis is None else array.squeeze(dim=lowercase_					)
	elif is_tf_tensor(lowercase_					):
		import tensorflow as tf

		return tf.squeeze(lowercase_    ,      axis=lowercase_					)
	elif is_jax_tensor(lowercase_					):
		return jnp.squeeze(lowercase_    ,      axis=lowercase_					)
	else:
		raise ValueError(f"""Type not supported for squeeze: {type(lowercase_					)}."""					)

def 						UpperCamelCase					(lowercase_: str    ,      lowercase_: Optional[Any]					)     ->      str:
	if is_numpy_array(lowercase_					):
		return np.expand_dims(lowercase_    ,      lowercase_					)
	elif is_torch_tensor(lowercase_					):
		return array.unsqueeze(dim=lowercase_					)
	elif is_tf_tensor(lowercase_					):
		import tensorflow as tf

		return tf.expand_dims(lowercase_    ,      axis=lowercase_					)
	elif is_jax_tensor(lowercase_					):
		return jnp.expand_dims(lowercase_    ,      axis=lowercase_					)
	else:
		raise ValueError(f"""Type not supported for expand_dims: {type(lowercase_					)}."""					)

def 						UpperCamelCase					(lowercase_: Tuple					)     ->      Optional[int]:
	if is_numpy_array(lowercase_					):
		return np.size(lowercase_					)
	elif is_torch_tensor(lowercase_					):
		return array.numel()
	elif is_tf_tensor(lowercase_					):
		import tensorflow as tf

		return tf.size(lowercase_					)
	elif is_jax_tensor(lowercase_					):
		return array.size
	else:
		raise ValueError(f"""Type not supported for expand_dims: {type(lowercase_					)}."""					)

def 						UpperCamelCase					(lowercase_: str    ,      lowercase_: str					)     ->      Union[str, Any]:
	for key, value in auto_map.items():
		if isinstance(lowercase_    ,      (tuple, list)					):
			A__							:    Any        =		[f"""{repo_id}--{v}""" if (v is not None and """--""" not in v) else v for v in value]
		elif value is not None and "--" not in value:
			A__							:    Any        =		f"""{repo_id}--{value}"""

	return auto_map


def 						UpperCamelCase					(lowercase_: List[str]					)     ->      int:
	for base_class in inspect.getmro(lowercase_					):
		A__							:    Tuple        =		base_class.__module__
		A__							:    int        =		base_class.__name__
		if module.startswith("""tensorflow"""					) or module.startswith("""keras"""					) or name == "TFPreTrainedModel":
			return "tf"
		elif module.startswith("""torch"""					) or name == "PreTrainedModel":
			return "pt"
		elif module.startswith("""flax"""					) or module.startswith("""jax"""					) or name == "FlaxPreTrainedModel":
			return "flax"
	else:
		raise TypeError(f"""Could not infer framework from class {model_class}."""					)






import argparse
import os
import re


A_       : List[str]         =			'src/diffusers'

# Pattern that looks at the indentation in a line.
A_       : Union[str, Any]         =			re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
A_       : int         =			re.compile(r'^\s*"([^"]+)":')
# Pattern that matches `_import_structure["key"]` and puts `key` in group 0.
A_       : Optional[int]         =			re.compile(r'^\s*_import_structure\["([^"]+)"\]')
# Pattern that matches `"key",` and puts `key` in group 0.
A_       : List[Any]         =			re.compile(r'^\s*"([^"]+)",\s*$')
# Pattern that matches any `[stuff]` and puts `stuff` in group 0.
A_       : List[str]         =			re.compile(r'\[([^\]]+)\]')

def 						UpperCamelCase					(lowercase_: List[str]					)     ->      Dict:
	A__							:    Optional[Any]        =		_re_indent.search(lowercase_					)
	return "" if search is None else search.groups()[0]

def 						UpperCamelCase					(lowercase_: Dict    ,      lowercase_: Any=""    ,      lowercase_: Any=None    ,      lowercase_: Any=None					)     ->      Tuple:
	A__							:    Optional[Any]        =		0
	A__							:    str        =		code.split("""\n"""					)
	if start_prompt is not None:
		while not lines[index].startswith(lowercase_					):
			index += 1
		A__							:    Tuple        =		["""\n""".join(lines[:index]					)]
	else:
		A__							:    Optional[Any]        =		[]

	# We split into blocks until we get to the `end_prompt` (or the end of the block).
	A__							:    Union[str, Any]        =		[lines[index]]
	index += 1
	while index < len(lowercase_					) and (end_prompt is None or not lines[index].startswith(lowercase_					)):
		if len(lines[index]					) > 0 and get_indent(lines[index]					) == indent_level:
			if len(lowercase_					) > 0 and get_indent(current_block[-1]					).startswith(indent_level + """ """					):
				current_block.append(lines[index]					)
				blocks.append("""\n""".join(lowercase_					)					)
				if index < len(lowercase_					) - 1:
					A__							:    Union[str, Any]        =		[lines[index + 1]]
					index += 1
				else:
					A__							:    List[Any]        =		[]
			else:
				blocks.append("""\n""".join(lowercase_					)					)
				A__							:    int        =		[lines[index]]
		else:
			current_block.append(lines[index]					)
		index += 1

	# Adds current block if it's nonempty.
	if len(lowercase_					) > 0:
		blocks.append("""\n""".join(lowercase_					)					)

	# Add final block after end_prompt if provided.
	if end_prompt is not None and index < len(lowercase_					):
		blocks.append("""\n""".join(lines[index:]					)					)

	return blocks

def 						UpperCamelCase					(lowercase_: str					)     ->      str:

	def _inner(lowercase_: Union[str, Any]					):
		return key(lowercase_					).lower().replace("""_"""    ,      """"""					)

	return _inner

def 						UpperCamelCase					(lowercase_: int    ,      lowercase_: Any=None					)     ->      str:

	# If no key is provided, we use a noop.
	def noop(lowercase_: Any					):
		return x

	if key is None:
		A__							:    Optional[Any]        =		noop
	# Constants are all uppercase, they go first.
	A__							:    Optional[int]        =		[obj for obj in objects if key(lowercase_					).isupper()]
	# Classes are not all uppercase but start with a capital, they go second.
	A__							:    List[Any]        =		[obj for obj in objects if key(lowercase_					)[0].isupper() and not key(lowercase_					).isupper()]
	# Functions begin with a lowercase, they go last.
	A__							:    Tuple        =		[obj for obj in objects if not key(lowercase_					)[0].isupper()]

	A__							:    Any        =		ignore_underscore(lowercase_					)
	return sorted(lowercase_    ,      key=lowercase_					) + sorted(lowercase_    ,      key=lowercase_					) + sorted(lowercase_    ,      key=lowercase_					)

def 						UpperCamelCase					(lowercase_: List[Any]					)     ->      List[Any]:

	# This inner function sort imports between [ ].
	def _replace(lowercase_: List[Any]					):
		A__							:    Tuple        =		match.groups()[0]
		if "," not in imports:
			return f"""[{imports}]"""
		A__							:    Optional[int]        =		[part.strip().replace("""\""""    ,      """"""					) for part in imports.split(""","""					)]
		# We will have a final empty element if the line finished with a comma.
		if len(keys[-1]					) == 0:
			A__							:    Any        =		keys[:-1]
		return "[" + ", ".join([f"""\"{k}\"""" for k in sort_objects(lowercase_					)]					) + "]"

	A__							:    Dict        =		import_statement.split("""\n"""					)
	if len(lowercase_					) > 3:
		# Here we have to sort internal imports that are on several lines (one per name):
		# key: [
		#     "object1",
		#     "object2",
		#     ...
		# ]

		# We may have to ignore one or two lines on each side.
		A__							:    List[str]        =		2 if lines[1].strip() == """[""" else 1
		A__							:    Any        =		[(i, _re_strip_line.search(lowercase_					).groups()[0]) for i, line in enumerate(lines[idx:-idx]					)]
		A__							:    Any        =		sort_objects(lowercase_    ,      key=lambda lowercase_					: x[1]					)
		A__							:    int        =		[lines[x[0] + idx] for x in sorted_indices]
		return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]					)
	elif len(lowercase_					) == 3:
		# Here we have to sort internal imports that are on one separate line:
		# key: [
		#     "object1", "object2", ...
		# ]
		if _re_bracket_content.search(lines[1]					) is not None:
			A__							:    Union[str, Any]        =		_re_bracket_content.sub(_replace    ,      lines[1]					)
		else:
			A__							:    Any        =		[part.strip().replace("""\""""    ,      """"""					) for part in lines[1].split(""","""					)]
			# We will have a final empty element if the line finished with a comma.
			if len(keys[-1]					) == 0:
				A__							:    Tuple        =		keys[:-1]
			A__							:    List[Any]        =		get_indent(lines[1]					) + """, """.join([f"""\"{k}\"""" for k in sort_objects(lowercase_					)]					)
		return "\n".join(lowercase_					)
	else:
		# Finally we have to deal with imports fitting on one line
		A__							:    int        =		_re_bracket_content.sub(_replace    ,      lowercase_					)
		return import_statement

def 						UpperCamelCase					(lowercase_: Optional[int]    ,      lowercase_: str=True					)     ->      Any:
	with open(lowercase_    ,      """r"""					) as f:
		A__							:    Optional[int]        =		f.read()

	if "_import_structure" not in code:
		return

	# Blocks of indent level 0
	A__							:    Tuple        =		split_code_in_indented_blocks(
	    lowercase_    ,      start_prompt="""_import_structure = {"""    ,      end_prompt="""if TYPE_CHECKING:"""					)

	# We ignore block 0 (everything until start_prompt) and the last block (everything after end_prompt).
	for block_idx in range(1    ,      len(lowercase_					) - 1					):
		# Check if the block contains some `_import_structure`s thingy to sort.
		A__							:    int        =		main_blocks[block_idx]
		A__							:    Optional[Any]        =		block.split("""\n"""					)

		# Get to the start of the imports.
		A__							:    Any        =		0
		while line_idx < len(lowercase_					) and "_import_structure" not in block_lines[line_idx]:
			# Skip dummy import blocks
			if "import dummy" in block_lines[line_idx]:
				A__							:    Optional[Any]        =		len(lowercase_					)
			else:
				line_idx += 1
		if line_idx >= len(lowercase_					):
			continue

		# Ignore beginning and last line: they don't contain anything.
		A__							:    Union[str, Any]        =		"""\n""".join(block_lines[line_idx:-1]					)
		A__							:    List[Any]        =		get_indent(block_lines[1]					)
		# Slit the internal block into blocks of indent level 1.
		A__							:    Union[str, Any]        =		split_code_in_indented_blocks(lowercase_    ,      indent_level=lowercase_					)
		# We have two categories of import key: list or _import_structure[key].append/extend
		A__							:    Optional[Any]        =		_re_direct_key if """_import_structure""" in block_lines[0] else _re_indirect_key
		# Grab the keys, but there is a trap: some lines are empty or just comments.
		A__							:    int        =		[(pattern.search(lowercase_					).groups()[0] if pattern.search(lowercase_					) is not None else None) for b in internal_blocks]
		# We only sort the lines with a key.
		A__							:    int        =		[(i, key) for i, key in enumerate(lowercase_					) if key is not None]
		A__							:    List[Any]        =		[x[0] for x in sorted(lowercase_    ,      key=lambda lowercase_					: x[1]					)]

		# We reorder the blocks by leaving empty lines/comments as they were and reorder the rest.
		A__							:    Optional[int]        =		0
		A__							:    Any        =		[]
		for i in range(len(lowercase_					)					):
			if keys[i] is None:
				reordered_blocks.append(internal_blocks[i]					)
			else:
				A__							:    Any        =		sort_objects_in_import(internal_blocks[sorted_indices[count]]					)
				reordered_blocks.append(lowercase_					)
				count += 1

        # And we put our main block back together with its first and last line.
		A__							:    Tuple        =		"""\n""".join(block_lines[:line_idx] + reordered_blocks + [block_lines[-1]]					)

	if code != "\n".join(lowercase_					):
		if check_only:
			return True
		else:
			print(f"""Overwriting {file}."""					)
			with open(lowercase_    ,      """w"""					) as f:
				f.write("""\n""".join(lowercase_					)					)

def 						UpperCamelCase					(lowercase_: Any=True					)     ->      Any:
	A__							:    Dict        =		[]
	for root, _, files in os.walk(lowercase_					):
		if "__init__.py" in files:
			A__							:    List[Any]        =		sort_imports(os.path.join(lowercase_    ,      """__init__.py"""					)    ,      check_only=lowercase_					)
			if result:
				A__							:    Optional[int]        =		[os.path.join(lowercase_    ,      """__init__.py"""					)]
	if len(lowercase_					) > 0:
		raise ValueError(f"""Would overwrite {len(lowercase_					)} files, run `make style`."""					)


if __name__ == "__main__":
	A_       : Union[str, Any]         =			argparse.ArgumentParser()
	parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
	A_       : List[str]         =			parser.parse_args()

	sort_imports_in_all_inits(check_only=args.check_only)



