     public func applied(to input: Tensor<Scalar>) -> Tensor<Scalar> {
         return input.convolved2D(withFilter: filter,
                                  strides: (1, strides.0, strides.1, 1),
-                                 padding: padding)
+                                 padding: padding) + bias
     }
 }
 

            Int32(filterShape.2), Int32(filterShape.3)])
        self.init(
            filter: Tensor(glorotUniform: filterTensorShape),
            strides: (Int32(strides.0), Int32(strides.1)), padding: padding)
    }
}

public struct Conv2D<Scalar>: Layer
    where Scalar: FloatingPoint & Differentiable & TensorFlowScalar {
    public var filter: Tensor<Scalar>
    public var bias: Tensor<Scalar>
    @noDerivative public let strides: (Int32, Int32)
    @noDerivative public let padding: Padding

