     /// - Returns: The output.
     @differentiable
     public func callAsFunction(_ input: Tensor<Scalar>) -> Tensor<Scalar> {
-        return activation(conv3D(input, filter: filter,
-                                 strides: (1, strides.0, strides.1, strides.2, 1),
-                                 padding: padding) + bias)
+        return activation(conv3D(
+            input,
+            filter: filter,
+            strides: (1, strides.0, strides.1, strides.2, 1),
+            padding: padding) + bias)
     }
 }
 

    public init(
        filter: Tensor<Scalar>,
        bias: Tensor<Scalar>,
        activation: @escaping Activation,
        strides: (Int, Int),
        padding: Padding
    ) {
        self.filter = filter
        self.bias = bias

    /// - Parameters:
    ///   - filterShape: The 3-D shape of the filter, representing
    ///     `[width, inputChannels, outputChannels]`.
    ///   - stride: The stride of the sliding window for the temporal dimension.
    ///   - padding: The padding algorithm for convolution.
    ///   - dilation: The dilation factor for the temporal dimension.
    ///   - activation: The element-wise activation function.
