inner spec. This can be used to extract the structure of nested
        datasets.
    *   Add `tf.data.experimental.AutoShardingPolicy.HINT` which can be used to
        provide hints to tf.distribute-based auto-sharding as to where in the
        input pipeline to insert sharding transformations.
    *   Make tf.data.Options persistent across `tf.function` and `GraphDef`
        boundaries.

of A η int // bound for secret coefficients γ1 int // log₂(γ₁), where [-γ₁+1, γ₁] is the bound of y γ2 int // denominator of γ₂ = (q - 1) / γ2 λ int // collison strength τ int // number of non-zero coefficients in challenge ω int // max number of hints in MakeHint } var ( params44 = parameters{k: 4, l: 4, η: 2, γ1: 17, γ2: 88, λ: 128, τ: 39, ω: 80} params65 = parameters{k: 6, l: 5, η: 4, γ1: 19, γ2: 32, λ: 192, τ: 49, ω: 55} params87 = parameters{k: 8, l: 7, η: 2, γ1: 19, γ2: 32, λ: 256, τ: 60, ω:...