I am trying to understand the architecture of my keras model implemented by the sequential model.

Here is a piece of the code :

model = Sequential([
    layers.BatchNormalization(), .......

My question is why the two parameters input_shape and name are declared in the layer conv2D while they are not included in the set of defined parmeters for Conv2D() in this link https://keras.io/api/layers/convolution_layers/convolution2d/


Bot the name and input_shape come from the Layer class which Conv2D inherited. In the doc you provide, they are implicitly in **kwargs

  • $\begingroup$ I found the name parmeter but input_shape no $\endgroup$ – baddy Aug 7 '20 at 9:39

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.