autodiff: finite-diff gradient-check harness

New xtrain-autodiff crate with a reusable central finite-difference
gradient check: grad_check(x, shape, f, analytic_grad, cfg) compares an
analytic gradient against (f(x+ε)-f(x-ε))/2ε per element with a relative
tolerance. Host-only (no CUDA): the loss closure owns any GPU work, so
T4's per-op backward checks can reuse it directly. Includes host unit
tests (sum(x²) grad 2x passes; a wrong grad is rejected).

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

crates/xtrain-autodiff/src/lib.rs

@@ -0,0 +1,15 @@
+//! Reusable numerical-gradient checking for xtrain (Phase T3+).
+//!
+//! Given a scalar loss `f(x)` and an analytic gradient `g`, verify that `g`
+//! matches the central finite-difference estimate
+//! `(f(x+ε·eᵢ) - f(x-ε·eᵢ)) / 2ε` for every element `i`, within a relative
+//! tolerance. Later phases (T4 autograd) reuse this per-op: wrap each op's
+//! forward as the loss, run its backward to get `g`, and `grad_check`.
+//!
+//! The harness is host-only and dtype-agnostic at this layer: it works on a
+//! flat `&[f32]` parameter vector + shape and a closure. The closure is free to
+//! push the data to the GPU and run kernels — that detail stays out of here.
+
+pub mod finite_diff;
+
+pub use finite_diff::{GradCheckConfig, GradCheckResult, ParamFn, grad_check};