embedding_bag_mean

std.nn.embedding_bag_mean · Level L3

The mean of the embeddings of a bag of ids: one vector for a whole set of tokens. Calls embedding_lookup.

(1/k)·Σᵢ E[idsᵢ]

Signature

embedding_bag_mean(E: f64[v, d], ids: i64[k]) → f64[d]

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.

Ef64[v, d]idsi64[k]embedding_lookuprowsMeanyyf64[d]
  • input
  • operation
  • constant
  • call
  • output

Verification

  • Signature proven by NOVA’s shape solver, for every size.
  • Equal to the reference np.take(E, ids, axis=0).mean(axis=0) in exact rational arithmetic, on all 40 test cases.
  • All 176 float64 results inside the running error bound; the closest uses 41% of it.
  • Interpreter and NumPy backend return bit-identical results.
Accuracy in detail
correctly rounded (the float64 nearest the exact value)
88%
bit-equal to the NumPy formula in float64
100%
largest error, in units in the last place
3.00

Identity

Calls
embedding_lookup
Called by
—
sha256:4bc030f9a184e3f41494effa660121c89a37bd09daec804433eb2550f2b4eb27

The semantic hash of the graph. It changes when the program changes, and never when only its documentation does.