Neural Network Blocks - ConvBlock

Loading in the clinical data

class ConvBlock(nn.Module):

    def __init__(self, c_in, c_out, ks, k_stride=1):
        
        super().__init__()

        self.conv1 = nn.Conv3d(c_in, c_out, ks, stride=k_stride, padding=(1,1,1))
        self.bn = nn.BatchNorm3d(c_out)
        self.elu = nn.ELU()
        self.pool = nn.MaxPool3d(kernel_size=(3,3,3), stride=2)
        self.dropout = nn.Dropout3d(p=0.1)

        
    def forward(self, x):
        
        out = self.conv1(x)
        out = self.bn(out)
        out = self.elu(out)
        out = self.pool(out)
        out = self.dropout(out)
        
        return out