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). Adds
xtrain-cuda dev-dep for device selection in tests.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

Cargo.lock

@@ -92,6 +92,7 @@ checksum = "e6e4313cd5fcd3dad5cafa179702e2b244f760991f45397d14d4ebf38247da75"
 name = "xtrain-autodiff"
 version = "0.1.0"
 dependencies = [
+ "xtrain-cuda",
  "xtrain-tensor",
 ]