Add a custom layer with a bitwise operation

Hello,
I have a use case where I want to introduce a bitwise operation or as a custom layer. As a 1st step, I trained a simple model with 8-bit integers as follows:
```
from qkeras import *

qmodel = Sequential()
qmodel.add(QDense(512,
kernel_quantizer="quantized_bits(bits=8, integer=7, keep_negative=True, alpha=1)",
bias_quantizer="quantized_bits(bits=8, integer=7, keep_negative=True, alpha=1)",
input_shape=(784,)))

qmodel.add(QActivation("quantized_relu(bits=8, integer=7)"))

qmodel.add(QDense(256,
kernel_quantizer="quantized_bits(bits=8, integer=7, keep_negative=True, alpha=1)",
bias_quantizer="quantized_bits(bits=8, integer=7, keep_negative=True, alpha=1)"))

qmodel.add(QActivation("quantized_relu(bits=8, integer=7)"))

qmodel.add(QDense(10,
kernel_quantizer="quantized_bits(bits=8, integer=7, keep_negative=True, alpha=1)",
bias_quantizer="quantized_bits(bits=8, integer=7, keep_negative=True, alpha=1)"))

qmodel.add(Activation("softmax"))
qmodel.summary()
```

Then I want to add another layer that performs the following operation `(x | 5) % 256`, which looks similar to this in Keras:
```
class CustomLayer(tf.keras.layers.Layer):
def __init__(self, **kwargs):
super(CustomLayer, self).__init__(**kwargs)

def call(self, x):
result = tf.math.mod((x | 5), 256)
return result
```
How can I proceed if I want to make the same in QKeras to be able to perform QAT with the custom layer?

Start by reviewing QKeras's existing quantized layers and the TensorFlow custom-layer API; the issue does not name repository files or tests. Determine how a bitwise operation and modulo should be represented for quantization-aware training, and define a supported custom-layer path with validation before considering implementation.

Written by the indexing model from the issue text.