Artificial intelligence · University
Parameter count in a dense layer · formula reference
Assume one trainable bias per output and no parameter sharing.
Formula
Assume one trainable bias per output and no parameter sharing.
parameters = inputs×outputs + outputs
Worked example
A fully connected layer maps 22 inputs to 22 outputs with one bias per output. How many trainable parameters does it have? Round the final result to 4 decimal places if needed.
There are 484 weights plus 22 biases.
506
Prerequisites and checking
Algebra and the topic definitions. Keep units and rounding consistent. State the model conditions before applying the formula.
Further reading and review references
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