## Issue

I want to add some error percentage (relative error) to the output of max-pooling layer in CNN. I am using max pooling layer from keras.

Below is the code

```
i = Input(shape=x_train[0].shape)
x = Conv2D(32, (3, 3), activation='relu', padding='same')(i)
x = BatchNormalization()(x)
x = Conv2D(32, (3, 3), activation='relu', padding='same')(x)
x = BatchNormalization()(x)
x = MaxPooling2D((2, 2))(x)
```

How can I add some errors to the output of this layer?

I want to add some fraction of the original output.

e.g. if x is my original output, I want my output to be x+ some fraction of (x).

Thanks in advance.

## Solution

If you just want to add a fraction of the input, you can just use `Add`

:

```
x = K.layers.Add()([x, 1/4 * x])
```

for example:

```
input = K.layers.Input(shape=(5,))
x = K.layers.Add()([input, 1/4 * input])
model = K.Model(inputs=[input], outputs=[x])
model(np.ones((1,5)))
#<tf.Tensor: shape=(1, 5), dtype=float32, numpy=array([[1.25, 1.25, 1.25, 1.25, 1.25]], dtype=float32)>
```

However this is not noise, and the affine transformation after this layer will vanish what you have done, infact:

```
A(x+ 1/4x)+b
= A(5/4x)+b
= 5/4 * A(x)+b
```

so you are not adding any "additional expressivity" to your network

if you clarify what noise (wrt to a *a fraction of the input*) you want, I’ll fix my answer

Answered By – Alberto Sinigaglia

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