





from __future__ import annotations


def 			SCREAMING_SNAKE_CASE__     (					_lowercase    :   int      ,						_lowercase    :   int      ,						_lowercase    :   int )      ->       tuple[float, float]:




		'''simple docstring'''
		assert (
		    c % greatest_common_divisor(_lowercase      ,						_lowercase ) == 0
		)  # greatest_common_divisor(a,b) function implemented below
		((lowercase__)      ,							(lowercase__)      ,							(lowercase__))				:			Tuple            =		extended_gcd(_lowercase      ,						_lowercase )  # extended_gcd(a,b) function implemented below
		lowercase__				:			int            =		c / d
		return (r * x, r * y)


def 			SCREAMING_SNAKE_CASE__     (					_lowercase    :   int      ,						_lowercase    :   int      ,						_lowercase    :   int      ,						_lowercase    :   int = 2 )      ->       None:




		'''simple docstring'''
		((lowercase__)      ,							(lowercase__))				:			List[Any]            =		diophantine(_lowercase      ,						_lowercase      ,						_lowercase )  # Initial value
		lowercase__				:			Tuple            =		greatest_common_divisor(_lowercase      ,						_lowercase )
		lowercase__				:			Any            =		a // d
		lowercase__				:			List[str]            =		b // d

		for i in range(_lowercase ):
				lowercase__				:			str            =		xa + i * q
				lowercase__				:			Tuple            =		ya - i * p
				print(_lowercase      ,						_lowercase )


def 			SCREAMING_SNAKE_CASE__     (					_lowercase    :   int      ,						_lowercase    :   int )      ->       int:




		'''simple docstring'''
		if a < b:
				lowercase__      ,							lowercase__				:			Union[str, Any]            =		b, a

		while a % b != 0:
				lowercase__      ,							lowercase__				:			Dict            =		b, a % b

		return b


def 			SCREAMING_SNAKE_CASE__     (					_lowercase    :   int      ,						_lowercase    :   int )      ->       tuple[int, int, int]:




		'''simple docstring'''
		assert a >= 0 and b >= 0

		if b == 0:
				lowercase__      ,							lowercase__      ,							lowercase__				:			int            =		a, 1, 0
		else:
				((lowercase__)      ,							(lowercase__)      ,							(lowercase__))				:			Optional[Any]            =		extended_gcd(_lowercase      ,						a % b )
				lowercase__				:			List[Any]            =		q
				lowercase__				:			Union[str, Any]            =		p - q * (a // b)

		assert a % d == 0 and b % d == 0
		assert d == a * x + b * y

		return (d, x, y)


if __name__ == "__main__":
			from doctest import testmod

			testmod(name="""diophantine""", verbose=True)
			testmod(name="""diophantine_all_soln""", verbose=True)
			testmod(name="""extended_gcd""", verbose=True)
			testmod(name="""greatest_common_divisor""", verbose=True)









import enum
import inspect
from typing import Iterable, List, Optional, Tuple, Union


class 			__lowerCAmelCase				(					enum.Enum			):


	'''simple docstring'''





	_A       	=							"timm"
	_A       	=							"transformers"


def 			SCREAMING_SNAKE_CASE__     (					_lowercase    :   Optional[Iterable[str]]      ,						_lowercase    :   Optional[Iterable[int]]      ,						_lowercase    :   Optional[Iterable[str]] )      ->       Optional[int]:




		'''simple docstring'''
		if stage_names is None:
				raise ValueError('Stage_names must be set for transformers backbones' )

		if out_features is not None:
				if not isinstance(_lowercase      ,						(list,) ):
						raise ValueError(f"""out_features must be a list {type(_lowercase )}""" )
				if any(feat not in stage_names for feat in out_features ):
						raise ValueError(f"""out_features must be a subset of stage_names: {stage_names} got {out_features}""" )

		if out_indices is not None:
				if not isinstance(_lowercase      ,						(list, tuple) ):
						raise ValueError(f"""out_indices must be a list or tuple, got {type(_lowercase )}""" )
				if any(idx >= len(_lowercase ) for idx in out_indices ):
						raise ValueError('out_indices must be valid indices for stage_names {stage_names}, got {out_indices}' )

		if out_features is not None and out_indices is not None:
				if len(_lowercase ) != len(_lowercase ):
						raise ValueError('out_features and out_indices should have the same length if both are set' )
				if out_features != [stage_names[idx] for idx in out_indices]:
						raise ValueError('out_features and out_indices should correspond to the same stages if both are set' )


def 			SCREAMING_SNAKE_CASE__     (					_lowercase    :   Optional[List[str]]      ,						_lowercase    :   Optional[Union[List[int], Tuple[int]]]      ,						_lowercase    :   List[str]      ,						)      ->       Dict:




		'''simple docstring'''
		if out_indices is None and out_features is None:
				lowercase__				:			str            =		[len(_lowercase ) - 1]
				lowercase__				:			Union[str, Any]            =		[stage_names[-1]]
		elif out_indices is None and out_features is not None:
				lowercase__				:			Optional[int]            =		[stage_names.index(_lowercase ) for layer in out_features]
		elif out_features is None and out_indices is not None:
				lowercase__				:			str            =		[stage_names[idx] for idx in out_indices]
		return out_features, out_indices


def 			SCREAMING_SNAKE_CASE__     (					_lowercase    :   Optional[List[str]]      ,						_lowercase    :   Optional[Union[List[int], Tuple[int]]]      ,						_lowercase    :   List[str]      ,						)      ->       Tuple[List[str], List[int]]:




		'''simple docstring'''
		verify_out_features_out_indices(out_features=_lowercase      ,						out_indices=_lowercase      ,						stage_names=_lowercase )
		lowercase__      ,							lowercase__				:			List[str]            =		_align_output_features_output_indices(
		    out_features=_lowercase      ,						out_indices=_lowercase      ,						stage_names=_lowercase )
		# Verify that the aligned out_features and out_indices are valid
		verify_out_features_out_indices(out_features=_lowercase      ,						out_indices=_lowercase      ,						stage_names=_lowercase )
		return output_features, output_indices


class 			__lowerCAmelCase				:


	'''simple docstring'''





	_A       	=							None

	def       snake_case__(	self:	Dict,				lowerCamelCase_:	Optional[Any] ):
			if getattr(self,				'_backbone',				lowerCamelCase_ ) is None:
					raise ValueError('self._backbone must be set before calling _init_timm_backbone' )

			# These will diagree with the defaults for the transformers models e.g. for resnet50
			# the transformer model has out_features = ['stem', 'stage1', 'stage2', 'stage3', 'stage4']
			# the timm model has out_features = ['act', 'layer1', 'layer2', 'layer3', 'layer4']
			lowercase__				:			Tuple            =		[stage['module'] for stage in self._backbone.feature_info.info]
			lowercase__				:			Union[str, Any]            =		[stage['num_chs'] for stage in self._backbone.feature_info.info]
			lowercase__				:			Dict            =		self._backbone.feature_info.out_indices
			lowercase__				:			Tuple            =		self._backbone.feature_info.module_name()

			# We verify the out indices and out features are valid
			verify_out_features_out_indices(
			    out_features=lowerCamelCase_,				out_indices=lowerCamelCase_,				stage_names=self.stage_names )
			lowercase__      ,							lowercase__				:			List[Any]            =		out_features, out_indices

	def       snake_case__(	self:	Any,				lowerCamelCase_:	List[str] ):
			lowercase__				:			Dict            =		getattr(lowerCamelCase_,				'stage_names' )
			lowercase__				:			List[str]            =		getattr(lowerCamelCase_,				'out_features',				lowerCamelCase_ )
			lowercase__				:			Optional[int]            =		getattr(lowerCamelCase_,				'out_indices',				lowerCamelCase_ )

			lowercase__				:			Optional[int]            =		stage_names
			lowercase__      ,							lowercase__				:			Union[str, Any]            =		get_aligned_output_features_output_indices(
			    out_features=lowerCamelCase_,				out_indices=lowerCamelCase_,				stage_names=lowerCamelCase_ )
			# Number of channels for each stage. This is set in the transformer backbone model init
			lowercase__				:			Dict            =		None

	def       snake_case__(	self:	List[Any],				lowerCamelCase_:	List[str] ):
			lowercase__				:			List[Any]            =		config

			lowercase__				:			Optional[int]            =		getattr(lowerCamelCase_,				'use_timm_backbone',				lowerCamelCase_ )
			lowercase__				:			List[Any]            =		BackboneType.TIMM if self.use_timm_backbone else BackboneType.TRANSFORMERS

			if self.backbone_type == BackboneType.TIMM:
					self._init_timm_backbone(lowerCamelCase_ )
			elif self.backbone_type == BackboneType.TRANSFORMERS:
					self._init_transformers_backbone(lowerCamelCase_ )
			else:
					raise ValueError(F"""backbone_type {self.backbone_type} not supported.""" )

	@property
	def       snake_case__(	self:	List[str] ):
			return self._out_features

	@out_features.setter
	def       snake_case__(	self:	Union[str, Any],				lowerCamelCase_:	List[str] ):
			lowercase__      ,							lowercase__				:			Optional[int]            =		get_aligned_output_features_output_indices(
			    out_features=lowerCamelCase_,				out_indices=lowerCamelCase_,				stage_names=self.stage_names )

	@property
	def       snake_case__(	self:	List[Any] ):
			return self._out_indices

	@out_indices.setter
	def       snake_case__(	self:	Tuple,				lowerCamelCase_:	Union[Tuple[int], List[int]] ):
			lowercase__      ,							lowercase__				:			List[str]            =		get_aligned_output_features_output_indices(
			    out_features=lowerCamelCase_,				out_indices=lowerCamelCase_,				stage_names=self.stage_names )

	@property
	def       snake_case__(	self:	str ):
			# the current backbones will output the number of channels for each stage
			# even if that stage is not in the out_features list.
			return {stage: self.num_features[i] for i, stage in enumerate(self.stage_names )}

	@property
	def       snake_case__(	self:	Optional[int] ):
			return [self.out_feature_channels[name] for name in self.out_features]

	def       snake_case__(	self:	List[Any],				*lowerCamelCase_:	List[Any],				**lowerCamelCase_:	Optional[Any] ):
			lowercase__				:			Any            =		dict(inspect.signature(self.forward ).parameters )
			lowercase__				:			List[Any]            =		{k: v for k, v in kwargs.items() if k in signature}
			return self(*lowerCamelCase_,				**lowerCamelCase_ )

	def       snake_case__(	self:	int,				lowerCamelCase_:	str,				lowerCamelCase_:	Optional[bool] = None,				lowerCamelCase_:	Optional[bool] = None,				lowerCamelCase_:	Optional[bool] = None,				):
			raise NotImplementedError('This method should be implemented by the derived class.' )





	def       snake_case__(	self:	Dict ):
			lowercase__				:			List[Any]            =		super().to_dict()
			lowercase__				:			Union[str, Any]            =		output.pop('_out_features' )
			lowercase__				:			Any            =		output.pop('_out_indices' )
			return output


class 			__lowerCAmelCase				:


	'''simple docstring'''





	@property
	def       snake_case__(	self:	Optional[int] ):
			return self._out_features

	@out_features.setter
	def       snake_case__(	self:	List[Any],				lowerCamelCase_:	List[str] ):
			lowercase__      ,							lowercase__				:			List[Any]            =		get_aligned_output_features_output_indices(
			    out_features=lowerCamelCase_,				out_indices=lowerCamelCase_,				stage_names=self.stage_names )

	@property
	def       snake_case__(	self:	Dict ):
			return self._out_indices

	@out_indices.setter
	def       snake_case__(	self:	Optional[int],				lowerCamelCase_:	Union[Tuple[int], List[int]] ):
			lowercase__      ,							lowercase__				:			Any            =		get_aligned_output_features_output_indices(
			    out_features=lowerCamelCase_,				out_indices=lowerCamelCase_,				stage_names=self.stage_names )





	def       snake_case__(	self:	Union[str, Any] ):
			lowercase__				:			List[str]            =		super().to_dict()
			lowercase__				:			str            =		output.pop('_out_features' )
			lowercase__				:			str            =		output.pop('_out_indices' )
			return output


