Hi,

Can we use tf.experimental.numpy with Keras Functional API?

When I create the following code:

inp1 = keras.layers.Input(shape=(1,), name=“inp1”)

inp2 = keras.layers.Input(shape=(1,), name=“inp2”)out = tf.experimental.numpy.add(inp1, inp2)

m = keras.Model([inp1, inp2], out)

I get the following error:

`Cannot interpret '<KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'inp1')>' as a data type`

Whereas when I use `out = tf.math.add(inp1, inp2)`

, there is no issue.

What could be the problem please?

**PS:** The use case that I have is to calculate the mean of a tensor ignoring all nan values. That’s why I was trying to use tf.experimental.numpy.nanmean which gave the same error.

Thanks!

Fadi Badine