analytical-viz: add FFN-only scope + 3rd sweep button

Both auto tabs now offer three sweep scopes via three buttons instead
of two:
  - Run sweep — Attention          → include_attention=T, include_ffn=F
  - Run sweep — FFN/MoE            → include_attention=F, include_ffn=T
  - Run sweep — Attn + FFN/MoE     → include_attention=T, include_ffn=T

Each button caches its result under its own session_state key; the most
recently clicked button drives the display. All three caches persist so
users can flip between scopes without re-running.

Core changes:
  auto_explore.py + auto_hardware.py:
    - New include_attention: bool = True param alongside include_ffn
    - _sum_visible_latency, _efficiency, score_config, run_auto_explore,
      compute_parallelism_sensitivity, joint_explore, compute_sensitivity,
      _best_parallelism_for_hw, _best_parallelism_two_stage all wired.
    - Attention and FFN are additive with no overlap: measured 7.35 ms
      (attn) + 5.50 ms (ffn) = 12.85 ms (full) for Llama 70B decode 128K.

Bug fix (drive-by): the display block in both tab render functions was
incorrectly nested inside the "cached ctx is stale" warning branch, so
metrics/scatter/table/sensitivity/load only rendered when the cache
was stale. Un-indented and removed the dead trailing else-info block.

Verified:
  - 24 pytest tests pass (added 1 new for FFN-only scope invariants)
  - Smoke: Llama 70B decode 128K all three scopes produce sensible Pareto:
      * Attention only: 7.35 ms (14 pareto configs)
      * FFN / MoE only: 5.50 ms (34 pareto configs)
      * Attn + FFN/MoE: 12.85 ms (6 pareto configs)
    Sums add up exactly, confirming no overlap in stage summation.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

tests/analytical_visualization/test_auto_explore.py

@@ -183,11 +183,31 @@ def test_attention_only_pareto_non_empty():
     model = PRESETS["Llama 3.1 70B"].model
     machine = MachineParams()
     res = run_auto_explore(model, machine, s_kv=8192, mode="decode",
-                             include_ffn=False)
+                             include_attention=True, include_ffn=False)
     assert res.total_feasible > 0
     assert len(res.pareto_scores) > 0
 
 
+def test_ffn_only_latency_less_than_full_and_different_from_attn():
+    """FFN-only latency must be > 0, < full-model latency, and != attn-only."""
+    model = PRESETS["Llama 3.1 70B"].model
+    machine = MachineParams()
+    r_full = run_auto_explore(model, machine, s_kv=8192, mode="decode",
+                                include_attention=True, include_ffn=True)
+    r_attn = run_auto_explore(model, machine, s_kv=8192, mode="decode",
+                                include_attention=True, include_ffn=False)
+    r_ffn = run_auto_explore(model, machine, s_kv=8192, mode="decode",
+                               include_attention=False, include_ffn=True)
+    b_full = min(r_full.pareto_scores, key=lambda s: s.total_latency_ns)
+    b_attn = min(r_attn.pareto_scores, key=lambda s: s.total_latency_ns)
+    b_ffn = min(r_ffn.pareto_scores, key=lambda s: s.total_latency_ns)
+    assert b_ffn.total_latency_ns > 0
+    assert b_ffn.total_latency_ns < b_full.total_latency_ns
+    assert abs(b_ffn.total_latency_ns - b_attn.total_latency_ns) > 1.0, (
+        "FFN-only and attention-only latencies should not be identical"
+    )
+
+
 def test_parallelism_sensitivity_includes_baseline_value():
     """Each row's values contain the baseline_value."""
     from tests.analytical_visualization.auto_explore import (