discount_step

std.seq.discount_step · Level L0

One step of a discounted return: this reward plus γ times the return after it. The body that discounted_returns scans, backwards.

g′ = r + γ·g

Signature

discount_step(g: f64[], r: f64[], gamma: f64[]) → 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.

gf64[]gammaf64[]rf64[]MultiplylaterAddg2g2f64[]
  • input
  • operation
  • constant
  • call
  • output

Verification

  • Signature proven by NOVA’s shape solver, for every size.
  • Equal to the reference r + gamma * g in exact rational arithmetic, on all 40 test cases.
  • All 40 float64 results inside the running error bound; the closest uses 85% of it.
  • Interpreter and NumPy backend return bit-identical results.
Accuracy in detail
correctly rounded (the float64 nearest the exact value)
83%
bit-equal to the NumPy formula in float64
100%
largest error, in units in the last place
0.75

Identity

Calls
—
Called by
discounted_returns
sha256:9692746b555d3ec3cde0550d0e06ced838bb3261defec2b24c04efce5c02c598

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