Junior interview questionAsked at Tesla · interview write-up
How many learnable parameters does a Conv2D layer have, with and without bias, given its channels and kernel size?
Model answer
Each output channel has one kernel spanning all input channels, so weights are in-channels times out-channels times kernel height times width. Bias adds one per output channel.
Example: 3 in, 64 out, 3 by 3 kernel gives 1,728 weights, 1,792 with bias. Groups divide the weight count.
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