





import math

import torch
from torch import nn
from torch.nn import init

from .binarizer import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer

class 		__a							(	nn.Linear      ):



       def __init__(     self	:   Dict					,			UpperCAmelCase	:   int					,			UpperCAmelCase	:   int					,			UpperCAmelCase	:   bool = True					,			UpperCAmelCase	:   str = "constant"					,			UpperCAmelCase	:   float = 0.0					,			UpperCAmelCase	:   str = "topK"					,			):
           super(UpperCAmelCase					,			self			).__init__(in_features=UpperCAmelCase					,			out_features=UpperCAmelCase					,			bias=UpperCAmelCase			)
           assert pruning_method in ["topK", "threshold", "sigmoied_threshold", "magnitude", "l0"]
           lowerCAmelCase_					:	int						=   pruning_method

           if self.pruning_method in ["topK", "threshold", "sigmoied_threshold", "l0"]:
               lowerCAmelCase_					:	Dict						=   mask_scale
               lowerCAmelCase_					:	str						=   mask_init
               lowerCAmelCase_					:	List[Any]						=   nn.Parameter(torch.empty(self.weight.size()			)			)
               self.init_mask()



       def  A							(     self	:   List[Any]			):
           if self.mask_init == "constant":
               init.constant_(self.mask_scores					,			val=self.mask_scale			)
           elif self.mask_init == "uniform":
               init.uniform_(self.mask_scores					,			a=-self.mask_scale					,			b=self.mask_scale			)
           elif self.mask_init == "kaiming":
               init.kaiming_uniform_(self.mask_scores					,			a=math.sqrt(5			)			)



       def  A							(     self	:   List[str]					,			UpperCAmelCase	:   torch.tensor					,			UpperCAmelCase	:   float			):
           # Get the mask
           if self.pruning_method == "topK":
               lowerCAmelCase_					:	Optional[Any]						=   TopKBinarizer.apply(self.mask_scores					,			UpperCAmelCase			)
           elif self.pruning_method in ["threshold", "sigmoied_threshold"]:
               lowerCAmelCase_					:	List[Any]						=   """sigmoied""" in self.pruning_method
               lowerCAmelCase_					:	List[str]						=   ThresholdBinarizer.apply(self.mask_scores					,			UpperCAmelCase					,			UpperCAmelCase			)
           elif self.pruning_method == "magnitude":
               lowerCAmelCase_					:	List[Any]						=   MagnitudeBinarizer.apply(self.weight					,			UpperCAmelCase			)
           elif self.pruning_method == "l0":
               lowerCAmelCase_		,		lowerCAmelCase_		,		lowerCAmelCase_					:	str						=   -0.1, 1.1, 2 / 3
               if self.training:
                   lowerCAmelCase_					:	Tuple						=   torch.zeros_like(self.mask_scores			).uniform_().clamp(0.0001					,			0.9999			)
                   lowerCAmelCase_					:	Optional[int]						=   torch.sigmoid((u.log() - (1 - u).log() + self.mask_scores) / b			)
               else:
                   lowerCAmelCase_					:	Any						=   torch.sigmoid(self.mask_scores			)
               lowerCAmelCase_					:	Union[str, Any]						=   s * (r - l) + l
               lowerCAmelCase_					:	Tuple						=   s_bar.clamp(min=0.0					,			max=1.0			)
           # Mask weights with computed mask
           lowerCAmelCase_					:	Optional[int]						=   mask * self.weight
           # Compute output (linear layer) with masked weights
           return nn.functional.linear(UpperCAmelCase					,			UpperCAmelCase					,			self.bias			)









from ..utils import deprecate
from .attention_processor import (  # noqa: F401
    Attention,
    AttentionProcessor,
    AttnAddedKVProcessor,
    AttnProcessor2_0,
    LoRAAttnProcessor,
    LoRALinearLayer,
    LoRAXFormersAttnProcessor,
    SlicedAttnAddedKVProcessor,
    SlicedAttnProcessor,
    XFormersAttnProcessor,
)
from .attention_processor import AttnProcessor as AttnProcessorRename  # noqa: F401


deprecate(
    'cross_attention',
    '0.20.0',
    'Importing from cross_attention is deprecated. Please import from diffusers.models.attention_processor instead.',
    standard_warn=False,
)


__UpperCAmelCase						=      AttentionProcessor

class 		__a							(	__UpperCamelCase      ):



       def __init__(     self	:   List[Any]					,			*UpperCAmelCase	:   List[Any]					,			**UpperCAmelCase	:   Any			):
           lowerCAmelCase_					:	str						=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"			)			)} instead.'
           deprecate("""cross_attention"""					,			"""0.20.0"""					,			UpperCAmelCase					,			standard_warn=UpperCAmelCase			)
           super().__init__(*UpperCAmelCase					,			**UpperCAmelCase			)






class 		__a							(	__UpperCamelCase      ):



       def __init__(     self	:   Optional[Any]					,			*UpperCAmelCase	:   List[Any]					,			**UpperCAmelCase	:   List[str]			):
           lowerCAmelCase_					:	List[Any]						=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"			)			)} instead.'
           deprecate("""cross_attention"""					,			"""0.20.0"""					,			UpperCAmelCase					,			standard_warn=UpperCAmelCase			)
           super().__init__(*UpperCAmelCase					,			**UpperCAmelCase			)






class 		__a							(	__UpperCamelCase      ):



       def __init__(     self	:   List[str]					,			*UpperCAmelCase	:   str					,			**UpperCAmelCase	:   Union[str, Any]			):
           lowerCAmelCase_					:	Tuple						=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"			)			)} instead.'
           deprecate("""cross_attention"""					,			"""0.20.0"""					,			UpperCAmelCase					,			standard_warn=UpperCAmelCase			)
           super().__init__(*UpperCAmelCase					,			**UpperCAmelCase			)






class 		__a							(	__UpperCamelCase      ):



       def __init__(     self	:   Optional[int]					,			*UpperCAmelCase	:   Union[str, Any]					,			**UpperCAmelCase	:   Any			):
           lowerCAmelCase_					:	Tuple						=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"			)			)} instead.'
           deprecate("""cross_attention"""					,			"""0.20.0"""					,			UpperCAmelCase					,			standard_warn=UpperCAmelCase			)
           super().__init__(*UpperCAmelCase					,			**UpperCAmelCase			)






class 		__a							(	__UpperCamelCase      ):



       def __init__(     self	:   str					,			*UpperCAmelCase	:   Any					,			**UpperCAmelCase	:   List[Any]			):
           lowerCAmelCase_					:	Union[str, Any]						=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"			)			)} instead.'
           deprecate("""cross_attention"""					,			"""0.20.0"""					,			UpperCAmelCase					,			standard_warn=UpperCAmelCase			)
           super().__init__(*UpperCAmelCase					,			**UpperCAmelCase			)






class 		__a							(	__UpperCamelCase      ):



       def __init__(     self	:   List[str]					,			*UpperCAmelCase	:   Union[str, Any]					,			**UpperCAmelCase	:   Tuple			):
           lowerCAmelCase_					:	Tuple						=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"			)			)} instead.'
           deprecate("""cross_attention"""					,			"""0.20.0"""					,			UpperCAmelCase					,			standard_warn=UpperCAmelCase			)
           super().__init__(*UpperCAmelCase					,			**UpperCAmelCase			)






class 		__a							(	__UpperCamelCase      ):



       def __init__(     self	:   Dict					,			*UpperCAmelCase	:   int					,			**UpperCAmelCase	:   int			):
           lowerCAmelCase_					:	List[str]						=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"			)			)} instead.'
           deprecate("""cross_attention"""					,			"""0.20.0"""					,			UpperCAmelCase					,			standard_warn=UpperCAmelCase			)
           super().__init__(*UpperCAmelCase					,			**UpperCAmelCase			)






class 		__a							(	__UpperCamelCase      ):



       def __init__(     self	:   Optional[Any]					,			*UpperCAmelCase	:   Any					,			**UpperCAmelCase	:   int			):
           lowerCAmelCase_					:	Union[str, Any]						=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"			)			)} instead.'
           deprecate("""cross_attention"""					,			"""0.20.0"""					,			UpperCAmelCase					,			standard_warn=UpperCAmelCase			)
           super().__init__(*UpperCAmelCase					,			**UpperCAmelCase			)


