refactor(ml-alpha): move Mamba2 stack 2 from PerceptionTrainer to CfcTrunk (X5)

Same pattern as X3: trainer constructs mamba2_l2 + Mamba2AdamW (against
&mamba2_l2), then moves the block into trunk.mamba2_stack_2. All
forward/backward/AdamW access sites redirect to self.trunk.mamba2_l2_mut().
Gradient buffers + AdamW state remain at trainer level.

Verification: golden bit-exact; ml-alpha lib green.

Per spec §2.2 (X5).

crates/ml-alpha/src/trainer/perception.rs

@@ -157,10 +157,8 @@ pub struct PerceptionTrainer {
     // Access via `self.trunk.mamba2_l1()` / `mamba2_l1_mut()`. Gradient
     // buffers + AdamW state remain at trainer level.
     pub mamba2_adamw: Mamba2AdamW,
-    /// Phase 2B: SECOND Mamba2 stack. Sits between the (first-stack-output
+    // X5: Mamba2 stack 2 weights moved to `self.trunk.mamba2_stack_2`.
-    /// + LN_a) and the existing LN_b → CfC. Same hidden_dim as stack 1
+    // Access via `self.trunk.mamba2_l2()` / `mamba2_l2_mut()`.
-    /// (128), in_dim=HIDDEN_DIM (consumes the LN_a output stream).
-    pub mamba2_l2: Mamba2Block,
     pub mamba2_l2_adamw: Mamba2AdamW,
     mamba2_l2_fwd_scratch: Mamba2BlockForwardScratch,
     mamba2_l2_bwd_scratch: Mamba2BackwardScratch,
@@ -672,6 +670,8 @@ impl PerceptionTrainer {
         let mamba2_l2_grads_buffers = Mamba2BackwardGradsBuffers::new(
             &stream, cfg.n_batch, cfg.seq_len, HIDDEN_DIM, HIDDEN_DIM, cfg.mamba2_state_dim,
         ).context("Mamba2BackwardGradsBuffers::new (l2)")?;
+        // X5: move Mamba2 stack 2 into the trunk.
+        trunk.mamba2_stack_2 = Some(mamba2_l2);
         let window_tensor_d = GpuTensor::zeros(&[cfg.n_batch, cfg.seq_len, FEATURE_DIM], &stream)
             .map_err(|e| anyhow::anyhow!("window_tensor_d alloc: {e}"))?;
         let h_enriched_seq_t_d = GpuTensor::zeros(&[cfg.seq_len, cfg.n_batch, HIDDEN_DIM], &stream)
@@ -1071,7 +1071,6 @@ impl PerceptionTrainer {
             mamba2_fwd_scratch,
             mamba2_bwd_scratch,
             mamba2_grads_buffers,
-            mamba2_l2,
             mamba2_l2_adamw,
             mamba2_l2_fwd_scratch,
             mamba2_l2_bwd_scratch,
@@ -1465,7 +1464,8 @@ impl PerceptionTrainer {
         }
 
         // ── 2b. Mamba2 stack-2 forward — consumes ln_a_out_d. in_dim = HIDDEN_DIM.
-        self.mamba2_l2
+        self.trunk
+            .mamba2_l2_mut()
             .forward_train_seq_into(&self.ln_a_out_d, &mut self.mamba2_l2_fwd_scratch)
             .context("mamba2 (l2) forward_train_seq_into")?;
 
@@ -2048,7 +2048,8 @@ impl PerceptionTrainer {
         //       Writes:
         //         mamba2_l2_grads_buffers.d_x_from_in = grad w.r.t. m2's
         //         input = grad w.r.t. LN_a output (consumed by LN_a bwd below).
-        self.mamba2_l2
+        self.trunk
+            .mamba2_l2_mut()
             .backward_from_h_enriched_seq_full_into(
                 &self.ln_a_out_d,
                 &self.mamba2_l2_fwd_scratch,
@@ -2305,7 +2306,7 @@ impl PerceptionTrainer {
             .step_from_buffers_gpu_clip(self.trunk.mamba2_l1_mut(), &self.mamba2_grads_buffers)
             .context("mamba2 (l1) AdamW step_from_buffers_gpu_clip")?;
         self.mamba2_l2_adamw
-            .step_from_buffers_gpu_clip(&mut self.mamba2_l2, &self.mamba2_l2_grads_buffers)
+            .step_from_buffers_gpu_clip(self.trunk.mamba2_l2_mut(), &self.mamba2_l2_grads_buffers)
             .context("mamba2 (l2) AdamW step_from_buffers_gpu_clip")?;
 
         // Queue loss_d → loss_host_d (mapped-pinned). Captured inside
@@ -2504,7 +2505,8 @@ impl PerceptionTrainer {
         }
 
         // Mamba2 stack-2 fwd → m2.h_enriched_seq.
-        self.mamba2_l2
+        self.trunk
+            .mamba2_l2_mut()
             .forward_train_seq_into(&self.ln_a_out_d, &mut self.mamba2_l2_fwd_scratch)
             .context("eval mamba2 (l2) fwd_into")?;