Creating a custom layer in tensorflow

I'm trying to create a layer in TensorFlow, which works something like this:

And my implementation looks something, like this:

class BinaryLayer(Layer):
    def __init__(self):
        super(BinaryLayer, self).__init__()

    def build(self, input_shape):
        w_init = 0.5
        
        self.w = tf.Variable(name=kernel,   initial_value=w_init(dtype='float32'),trainable=True)

    def call(self, inputs):
        return tf.math.greater(inputs, self.w)

But it gives me an error saying 'float' object is not callable

And I also think there will be another problem in the future, which is, it will return boolean values, such as: [[TFT] [TTF] [FFT]], but I want something like this: [[101] [110] [001]]