# Understanding declared parameters in my Conv2d layer of my convolutional neural network

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([
#block1
layers.Activation("relu"),
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

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