How do I get the weights of all filters (like 32 ,64, etc.) of a Conv2D layer in Keras after each epoch? I mention that, because initial weights are random but after optimization they will change.
I checked this answer but did not understand. Please help me find a solution of getting the weights of all the filter and after every epoch.
And one more question is that in Keras documentation for the Conv2D layer input shape is (samples, channels, rows, cols). What exactly does samples mean? Is it the total number of inputs we have (like in MNIST data set it is 60.000 training images) or the batch size (like 128 or other)?