accuracy
std.nn.accuracy · Level L2Classification accuracy: the share of rows whose largest logit is at the position of the largest label entry (one-hot labels).
(1/n)·Σᵢ [argmaxⱼ Zᵢⱼ = argmaxⱼ Yᵢⱼ]
Signature
accuracy(logits: f64[n, c], labels: f64[n, c]) → f64[]
Structure
The function as NOVA stores it: one box per input, operation and output, and arrows that carry values. A double border marks another library function this one runs — called once, or by Scan once per element; select it to open that function.
- input
- operation
- constant
- call
- output
Verification
- Signature proven by NOVA’s shape solver, for every size.
- Equal to the reference
np.mean(np.argmax(logits, 1) == np.argmax(labels, 1))in exact rational arithmetic, on all 40 test cases. - All 40 float64 results inside the running error bound; the closest uses 17% of it.
- Interpreter and NumPy backend return bit-identical results.
Accuracy in detail
- correctly rounded (the float64 nearest the exact value)
- 100%
- bit-equal to the NumPy formula in float64
- 100%
- largest error, in units in the last place
- 0.40
Identity
Calls
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Called by
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sha256:7c273578d51117fc08bb69929b672ae4b7772d9a142da05acc8b7b8ae0590cbfThe semantic hash of the graph. It changes when the program changes, and never when only its documentation does.