```
class MyDenseLayer(tf.keras.layers.Layer):
def __init__(self):
super(MyDenseLayer, self).__init__()
def build(self, input_shape):
self.omegam = tfd.Normal(loc=tf.Variable(0.3, name='omegam'), scale=0.01)
self.omegaw0 = tfd.Normal(loc=tf.Variable(-1., name='omegaw0'), scale=0.01)
self.omegaw1 = tfd.Normal(loc=tf.Variable(0., name='omegaw1'), scale=0.01)
def call(self, inputs):
inputs=inputs
uffa= self.omegam.sample()
uffa2= self.omegaw1.sample()
uffa3=self.omegaw0.sample()
uff= 1/tf.math.sqrt(uffa*(1+inputs)**3+ (1-uffa)*tf.math.exp(uffa2*inputs+(1+uffa3 -uffa2)*tf.math.log(1+inputs)))
return uff
```

i just want to apply a function to the input variable but it never works ffs why doesn’t it work?

when i try

```
mydense = MyDenseLayer()
mydense(5)
```

i get

```
14 uffa2= self.omegaw1.sample()
15 uffa3=self.omegaw0.sample()
---> 16 uff= 1/tf.math.sqrt(uffa*(1+inputs)**3+ (1-uffa)*tf.math.exp(uffa2*inputs+(1+uffa3 -uffa2)*tf.math.log(1+inputs)))
17
18
InvalidArgumentError: Exception encountered when calling layer "my_dense_layer_34" (type MyDenseLayer).
cannot compute Mul as input #1(zero-based) was expected to be a float tensor but is a int32 tensor [Op:Mul]
Call arguments received by layer "my_dense_layer_34" (type MyDenseLayer):
• inputs=tf.Tensor(shape=(), dtype=int32)
```