Keras: Vanishing Parameters In Conv2d Layer Within Lambda Function

I am defining a Lambda layer with a function that uses the Conv2D layer. def lambda_func(x,k): y = Conv2D(k, (3,3), padding='same')(x) return y And calling it using k = 64

Solution 1:

Lambda layers don't have parameters.

Parameters, in the summary, are the variables that can "learn". Lambda layers never learn, they're functions created by you.

If you do intend to use a "Convolutional Layer", use it outside of the lambda layer. Now, if you want to use a "convolution operation", then use it inside the lambda layer, but there is no learnable parameter, you define the filters yourself.

If you want to create a special layer that learns in a different way, then create a custom layer.