@@ -115,7 +115,7 @@ class DoubleConv(nn.Module):
115115 activations.
116116 """
117117
118- def __init__ (self , in_channels , out_channels , mid_channels = None ):
118+ def __init__ (self , in_channels , out_channels , kernel_size = 3 , mid_channels = None ):
119119 """
120120 Instantiates a DoubleConv object.
121121
@@ -125,6 +125,8 @@ def __init__(self, in_channels, out_channels, mid_channels=None):
125125 Number of input channels to this module.
126126 out_channels : int
127127 Number of output channels produced by this module.
128+ kernel_size : int, optional
129+ Size of kernel used in convolutional layers. Default is 3.
128130 mid_channels : int, optional
129131 Number of channels in the intermediate convolution. Default is
130132 None.
@@ -138,10 +140,10 @@ def __init__(self, in_channels, out_channels, mid_channels=None):
138140
139141 # Instance attributes
140142 self .double_conv = nn .Sequential (
141- nn .Conv3d (in_channels , mid_channels , kernel_size = 4 , padding = 1 ),
143+ nn .Conv3d (in_channels , mid_channels , kernel_size = kernel_size , padding = 1 ),
142144 nn .BatchNorm3d (mid_channels ),
143145 nn .LeakyReLU (negative_slope = 0.01 , inplace = True ),
144- nn .Conv3d (mid_channels , out_channels , kernel_size = 4 , padding = 1 ),
146+ nn .Conv3d (mid_channels , out_channels , kernel_size = kernel_size , padding = 1 ),
145147 nn .BatchNorm3d (out_channels ),
146148 nn .LeakyReLU (negative_slope = 0.01 , inplace = True )
147149 )
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