How to reimplement the code without reuse function?

Hello all, I have a code script as

class SPPBottleneck(nn.Module):
    """Spatial pyramid pooling layer used in YOLOv3-SPP"""

    def __init__(
        self, in_channels, out_channels, kernel_sizes=(5, 9, 13), activation="silu"
        hidden_channels = in_channels // 2
        self.conv1 = BaseConv(in_channels, hidden_channels, 1, stride=1, act=activation)
        self.m = nn.ModuleList(
                nn.MaxPool2d(kernel_size=ks, stride=1, padding=ks // 2)
                for ks in kernel_sizes
        conv2_channels = hidden_channels * (len(kernel_sizes) + 1)
        self.conv2 = BaseConv(conv2_channels, out_channels, 1, stride=1, act=activation)

    def forward(self, x):
        x = self.conv1(x)
        x =[x] + [m(x) for m in self.m], dim=1)
        x = self.conv2(x)

I want to reimplement the block x =[x] + [m(x) for m in self.m], dim=1) to ignore the warning [PyTorch Model Guidelines — AI Model Efficiency Toolkit Documentation: ver tf-torch-cpu_1.17.0](https://“Model with reused modules”). Could you please help me to do it?