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Author SHA1 Message Date
Gahow Wang
2e68942032 docs: Phase T4 — autograd engine 
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-15 15:44:27 +08:00
Gahow Wang
7de172a2cf ops: differentiable autograd nodes + per-op grad-check tests 
ops.rs wraps each Tensor op as a Var node with its backward closure (forward
caches captured by move). swiglu = mul(silu(gate), up); attention is composed
(matmul+scale+softmax+matmul), no fused kernel. tests/autograd.rs grad-checks
every op via the L=sum(W∘out) template, plus a fan-out grad-accumulation test
(dL/dx=4x) and an end-to-end composed-attention grad-check (dQ/dK/dV).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-06-15 15:44:27 +08:00
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crates/xtrain-autodiff/Cargo.toml
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@@ -5,7 +5,3 @@ edition.workspace = true
[dependencies]
xtrain-tensor = { path = "../xtrain-tensor" }
[dev-dependencies]
# Acceptance tests need device selection (set_device) to drive the GPU.
xtrain-cuda = { path = "../xtrain-cuda" }