post-train: M4 — clipped_pg_loss + scale_rows (GRPO policy-gradient op)

The GRPO (M4) token-level loss op + the one primitive it needs:

- scale_rows(x[r,c], s[r]): per-row scale (new ~5-line CUDA kernel). The
  clipped-PG backward scales each completion token's row of (probs − onehot) by
  its own per-token coefficient, which cross_entropy_backward's single scalar
  scale can't express.
- clipped_pg_loss(logits, target, logp_old, logp_ref, A, eps, beta): per-token
  ρ_t = exp(logπθ_t − logp_old_t), L = −mean min(ρA, clip(ρ,1±ε)A) + β·mean KL
  (k3 estimator), masked to completion tokens. Backward reuses the CE machinery
  (probs − onehot) + scale_rows. Gates: grad-check the active PG path + the A=0
  (KL-only) path; degenerate value checks ε→∞ ⇒ vanilla PG, β=0 ⇒ no KL.

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

crates/xtrain-cuda/src/ffi.rs

@@ -152,6 +152,15 @@ unsafe extern "C" {
         pos0: i32,
         s: CudaStream,
     );
+    // Per-row scale: y[r,c] = x[r,c] * s[r] (GRPO policy-gradient backward).
+    pub fn launch_scale_rows_f32(
+        x: *const f32,
+        s: *const f32,
+        y: *mut f32,
+        rows: i32,
+        cols: i32,
+        stream: CudaStream,
+    );
     pub fn launch_rope_dx_f32(
         dy: *const f32,
         dx: *mut f32,