3fa215ad2e
CfcTrunk::save_checkpoint(path) reads each device weight tensor back
via memcpy_dtoh and bincode-serialises into a CheckpointV1 envelope:
{ version, n_in, n_hid,
w_in, w_rec, b, tau,
heads_w, heads_b,
proj_w, proj_b, proj_g, proj_n }
Total ~22k-25k f32 = ~90 KB per trunk. Tiny.
CfcTrunk::load_checkpoint(dev, cfg, path) deserialises + validates
(version == 1, n_in/n_hid match the supplied CfcConfig — a model
trained for one arch can't silently load against another). Constructs
a fresh trunk via new_random (for kernel bindings + scratch buffers)
then overwrites every weight tensor via memcpy_htod. The random init
values are thrown away — marginally wasteful, but keeps the
construction code paths unified.
Roundtrip test (--ignored, CUDA-required): save trunk_A → load → read
back every device tensor and assert bit-equality between trunk_A and
the loaded trunk_B. Passed locally. Dim-mismatch rejection test runs
without CUDA (verifies bincode envelope serialise/deserialise).
bin/fxt-backtest --checkpoint <path>: when set, overrides --seed and
loads from disk. When absent, warns loudly that the trunk is
random-initialised and backtest results are noise. This makes the
binary genuinely useful as a deployment tool — point it at a trained
checkpoint and run real backtests.
Adds bincode workspace dep to ml-alpha (was already in workspace
dependencies, just not in ml-alpha's [dependencies] block). serde
features bumped to ["derive"] (was using workspace default which
omits derive macros).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
51 lines
1.8 KiB
TOML
51 lines
1.8 KiB
TOML
[package]
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name = "ml-alpha"
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version.workspace = true
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edition.workspace = true
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rust-version.workspace = true
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description = "CfC perception + multi-horizon alpha heads (Phase A foundation for CfC+PPO greenfield)"
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publish = false
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# Phase A scope: snapshot-level CfC trunk + 5 multi-horizon BCE heads,
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# pre-compiled CUDA cubins, GPU-resident weights. The hard validation gate
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# (CfC vs Mamba2 AUC at every horizon) sits at the end of Phase A. Phase B
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# (PPO) extends this crate; live integration lives in trading_agent_service.
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[features]
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default = ["cuda"]
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cuda = []
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[dependencies]
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ml-core = { workspace = true }
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# NOTE: cannot depend on `ml` (would cycle — ml depends on ml-alpha for the
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# mamba2_block gate reference). MappedF32Buffer is duplicated locally in
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# `src/pinned_mem.rs`; eventually we should move mapped-pinned to ml-core.
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ml-features = { workspace = true }
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data = { workspace = true }
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cudarc = { version = "0.19", default-features = false, features = ["driver", "cublas", "dynamic-linking", "std", "cuda-version-from-build-system", "f16"] }
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# Standard async + error + logging plumbing
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tokio = { workspace = true, features = ["rt-multi-thread", "macros", "fs", "io-util"] }
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anyhow.workspace = true
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tracing.workspace = true
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tracing-subscriber.workspace = true
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serde = { workspace = true, features = ["derive"] }
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serde_json.workspace = true
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bincode.workspace = true
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thiserror.workspace = true
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clap = { workspace = true, features = ["derive"] }
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# Arrow IPC for fxcache reading (gate reference path).
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arrow = { workspace = true, features = ["ipc"] }
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# Deterministic RNG for weight init, shuffling.
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rand = { workspace = true }
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rand_chacha = "0.3"
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# Phase A data path: mmap predecoded MBP-10 sidecars.
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memmap2 = { workspace = true }
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[dev-dependencies]
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tempfile = { workspace = true }
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approx = { workspace = true }
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