Convolution output shape and parameters

Problem

An input has shape $32\times32\times3$ . A convolution uses $16$ filters of size $5\times5$ , stride $2$ , padding $2$ , and one bias per filter. Compute the output shape and trainable parameter count.

Reveal answer or reference solution

Each spatial dimension is

$\left\lfloor\frac{32+2(2)-5}{2}\right\rfloor+1=16,$

so the output is $16\times16\times16$ . The parameter count is

$5\times5\times3\times16+16=1216.$

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Appears in

Machine Learning Diagnostic
Convolution Practice