class
ResBlock
[source]
ResBlock
(expansion
,ni
,nf
,stride
=1
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sa
=False
,sym
=False
,norm_type
=<NormType.Batch: 1>
,act_cls
=ReLU
,ndim
=2
,ks
=3
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
) ::Module
Resnet block from ni
to nh
with stride
ResNeXtBlock
[source]
ResNeXtBlock
(expansion
,ni
,nf
,groups
=32
,stride
=1
,base_width
=4
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sa
=False
,sym
=False
,norm_type
=<NormType.Batch: 1>
,act_cls
=ReLU
,ndim
=2
,ks
=3
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
SEBlock
[source]
SEBlock
(expansion
,ni
,nf
,groups
=1
,se_reduction
=16
,stride
=1
,se_act_cls
=ReLU
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sa
=False
,sym
=False
,norm_type
=<NormType.Batch: 1>
,act_cls
=ReLU
,ndim
=2
,ks
=3
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
A Squeeze and Excitation XResNet
Block. Can set se_act_cls
seperately.
SEResNeXtBlock
[source]
SEResNeXtBlock
(expansion
,ni
,nf
,groups
=32
,se_reduction
=16
,stride
=1
,base_width
=4
,se_act_cls
=ReLU
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sa
=False
,sym
=False
,norm_type
=<NormType.Batch: 1>
,act_cls
=ReLU
,ndim
=2
,ks
=3
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
A Squeeze and Excitation XResNeXtBlock
. Can set se_act_cls
seperately.
ECABlock
[source]
ECABlock
(expansion
,ni
,nf
,groups
=1
,eca_ks
=None
,stride
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sa
=False
,sym
=False
,norm_type
=<NormType.Batch: 1>
,act_cls
=ReLU
,ndim
=2
,ks
=3
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
An Efficient Channel Attention XResNet
Block
ECAResNeXtBlock
[source]
ECAResNeXtBlock
(expansion
,ni
,nf
,groups
=32
,eca_ks
=None
,stride
=1
,base_width
=4
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sa
=False
,sym
=False
,norm_type
=<NormType.Batch: 1>
,act_cls
=ReLU
,ndim
=2
,ks
=3
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
An Efficient Channel Attention XResNeXtBlock
SABlock
[source]
SABlock
(expansion
,ni
,nf
,groups
=1
,sa_grps
=64
,stride
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sa
=False
,sym
=False
,norm_type
=<NormType.Batch: 1>
,act_cls
=ReLU
,ndim
=2
,ks
=3
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
A Shuffle Attention XResNet
Block
SAResNeXtBlock
[source]
SAResNeXtBlock
(expansion
,ni
,nf
,groups
=32
,sa_grps
=64
,stride
=1
,base_width
=4
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sa
=False
,sym
=False
,norm_type
=<NormType.Batch: 1>
,act_cls
=ReLU
,ndim
=2
,ks
=3
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
A Shuffle Attention XResNeXtBlock
TABlock
[source]
TABlock
(expansion
,ni
,nf
,groups
=1
,ta_ks
=7
,stride
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sa
=False
,sym
=False
,norm_type
=<NormType.Batch: 1>
,act_cls
=ReLU
,ndim
=2
,ks
=3
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
A Triplet Attention XResNet
Block
TAResNeXtBlock
[source]
TAResNeXtBlock
(expansion
,ni
,nf
,groups
=32
,ta_ks
=7
,stride
=1
,base_width
=4
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sa
=False
,sym
=False
,norm_type
=<NormType.Batch: 1>
,act_cls
=ReLU
,ndim
=2
,ks
=3
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
A Triplet Attention XResNeXtBlock
class
XResNet
[source]
XResNet
(block
,expansion
,layers
,p
=0.0
,c_in
=3
,n_out
=1000
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
) ::Sequential
A flexible version of fastai's XResNet
xresnet18
[source]
xresnet18
(n_out
=1000
,c_in
=3
,p
=0.0
,act_cls
=ReLU
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xresnet34
[source]
xresnet34
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xresnet50
[source]
xresnet50
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xresnet101
[source]
xresnet101
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xresnext18
[source]
xresnext18
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xresnext34
[source]
xresnext34
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xresnext50
[source]
xresnext50
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xresnext101
[source]
xresnext101
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xse_resnet18
[source]
xse_resnet18
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xse_resnet34
[source]
xse_resnet34
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xse_resnet50
[source]
xse_resnet50
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xse_resnet101
[source]
xse_resnet101
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xse_resnext18
[source]
xse_resnext18
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xse_resnext34
[source]
xse_resnext34
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xse_resnext50
[source]
xse_resnext50
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xse_resnext101
[source]
xse_resnext101
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xeca_resnet18
[source]
xeca_resnet18
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xeca_resnet34
[source]
xeca_resnet34
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xeca_resnet50
[source]
xeca_resnet50
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xeca_resnet101
[source]
xeca_resnet101
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xeca_resnext18
[source]
xeca_resnext18
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xeca_resnext34
[source]
xeca_resnext34
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xeca_resnext50
[source]
xeca_resnext50
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xeca_resnext101
[source]
xeca_resnext101
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xsa_resnet18
[source]
xsa_resnet18
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xsa_resnet34
[source]
xsa_resnet34
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xsa_resnet50
[source]
xsa_resnet50
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xsa_resnet101
[source]
xsa_resnet101
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xsa_resnext18
[source]
xsa_resnext18
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xsa_resnext34
[source]
xsa_resnext34
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xsa_resnext50
[source]
xsa_resnext50
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xsa_resnext101
[source]
xsa_resnext101
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xta_resnet18
[source]
xta_resnet18
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xta_resnet34
[source]
xta_resnet34
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xta_resnet50
[source]
xta_resnet50
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xta_resnet101
[source]
xta_resnet101
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xta_resnext18
[source]
xta_resnext18
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xta_resnext34
[source]
xta_resnext34
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xta_resnext50
[source]
xta_resnext50
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)
xta_resnext101
[source]
xta_resnext101
(n_out
=1000
,p
=0.0
,c_in
=3
,stem_szs
=(32, 32, 64)
,block_szs
=[64, 128, 256, 512]
,widen
=1.0
,sa
=False
,act_cls
=ReLU
,ndim
=2
,ks
=3
,stride
=2
,stem_layer
=ConvLayer
,stem_pool
=MaxPool
,head_pool
=AdaptiveAvgPool
,custom_head
=None
,groups
=1
,attn_mod
=None
,nh1
=None
,nh2
=None
,dw
=False
,g2
=1
,sym
=False
,norm_type
=<NormType.Batch: 1>
,block_pool
=AvgPool
,pool_first
=True
,stoch_depth
=0
,padding
=None
,bias
=None
,bn_1st
=True
,transpose
=False
,init
='auto'
,xtra
=None
,bias_std
=0.01
,dilation
:Union
[int
,typing.Tuple[int, int]
]=1
,padding_mode
:str
='zeros'
,device
=None
,dtype
=None
)