def METHOD_NAME(self, in_channels, features, padding=1, kernel_size=5, name="block"):
    return nn.Sequential(
        OrderedDict(
            (
                (
                    f"{name}_conv1",
                    nn.Conv3d(
                        in_channels=in_channels,
                        out_channels=features,
                        kernel_size=kernel_size,
                        padding=padding,
                        bias=True,
                    ),
                ),
                (f"{name}_norm1", nn.BatchNorm3d(num_features=features)),
                (f"{name}_relu1", nn.ReLU(inplace=True)),
                (
                    f"{name}_conv2",
                    nn.Conv3d(
                        in_channels=features,
                        out_channels=features,
                        kernel_size=kernel_size,
                        padding=padding,
                        bias=True,
                    ),
                ),
                (f"{name}_norm2", nn.BatchNorm3d(num_features=features)),
                (f"{name}_relu2", nn.ReLU(inplace=True)),
            )
        )
    )