Manuel Raimann
74cf0643eb
- Replace Mutex<fastrand::Rng> with a stored seed + MurmurHash3 mixer in RandomSampler, TpeSampler, and MotpeSampler so parallel workers no longer serialize on a shared lock - Add mix_seed() and distribution_fingerprint() to rng_util for deterministic per-call RNG derivation from (seed, trial_id, distribution) - Include an AtomicU64 call counter to disambiguate parameters that share the same distribution within a trial
59 lines
2.1 KiB
Rust
59 lines
2.1 KiB
Rust
use crate::distribution::Distribution;
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/// Generate a random `f64` in the range `[low, high)`.
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#[inline]
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pub(crate) fn f64_range(rng: &mut fastrand::Rng, low: f64, high: f64) -> f64 {
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low + rng.f64() * (high - low)
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}
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/// Combine a base seed, trial id, and distribution fingerprint into a
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/// deterministic per-call seed using `MurmurHash3`'s 64-bit finalizer.
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#[inline]
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pub(crate) fn mix_seed(base: u64, trial_id: u64, dist_fingerprint: u64) -> u64 {
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let mut h = base
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.wrapping_mul(0xff51_afd7_ed55_8ccd)
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.wrapping_add(trial_id)
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.wrapping_mul(0xc4ce_b9fe_1a85_ec53)
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.wrapping_add(dist_fingerprint);
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h ^= h >> 33;
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h = h.wrapping_mul(0xff51_afd7_ed55_8ccd);
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h ^= h >> 33;
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h = h.wrapping_mul(0xc4ce_b9fe_1a85_ec53);
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h ^= h >> 33;
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h
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}
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/// Stable `u64` fingerprint for a [`Distribution`], using variant tags and
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/// `f64::to_bits()` for float fields so that distinct distributions within
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/// the same trial produce different RNG streams.
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#[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
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pub(crate) fn distribution_fingerprint(distribution: &Distribution) -> u64 {
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match distribution {
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Distribution::Float(d) => {
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let mut h: u64 = 1;
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h = h.wrapping_mul(31).wrapping_add(d.low.to_bits());
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h = h.wrapping_mul(31).wrapping_add(d.high.to_bits());
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h = h.wrapping_mul(31).wrapping_add(u64::from(d.log_scale));
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if let Some(step) = d.step {
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h = h.wrapping_mul(31).wrapping_add(step.to_bits());
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}
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h
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}
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Distribution::Int(d) => {
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let mut h: u64 = 2;
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h = h.wrapping_mul(31).wrapping_add(d.low as u64);
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h = h.wrapping_mul(31).wrapping_add(d.high as u64);
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h = h.wrapping_mul(31).wrapping_add(u64::from(d.log_scale));
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if let Some(step) = d.step {
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h = h.wrapping_mul(31).wrapping_add(step as u64);
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}
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h
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}
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Distribution::Categorical(d) => {
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let mut h: u64 = 3;
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h = h.wrapping_mul(31).wrapping_add(d.n_choices as u64);
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h
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}
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}
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}
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