nohup: ignoring input
Loading model...
  [Auto-detect] Qwen3-Omni MoE thinker (30.5B total, ~3.3B active)
[FireEcho] Loading /run/media/echo/Echo/ECHO/training/Prototype Fireecho/model/Qwen3-Omni-30B-A3B-Instruct...
  [FireEcho] AutoConfig failed ('Qwen3OmniMoeTalkerCodePredictorConfig' object has no attribute 'use_sliding_window'), loading config.json directly
  Qwen3-Omni: will stream-load from 15 shards
  [Qwen3 Streaming] Loaded shard index: 28010 keys across 15 shards
  [Qwen3 Streaming] Building engine skeleton...
  [Qwen3 Streaming] Global params on GPU: 1.2 GB
    Layer 4/48: 393 weights, VRAM 2.8 GB, CPU 1.4 GB
    Layer 8/48: 393 weights, VRAM 4.3 GB, CPU 1.6 GB
    Layer 12/48: 393 weights, VRAM 5.8 GB, CPU 1.7 GB
    Layer 16/48: 393 weights, VRAM 7.4 GB, CPU 1.9 GB
    Layer 20/48: 393 weights, VRAM 8.9 GB, CPU 2.0 GB
    Layer 24/48: 393 weights, VRAM 10.4 GB, CPU 2.2 GB
    Layer 28/48: 393 weights, VRAM 11.9 GB, CPU 2.3 GB
    Layer 32/48: 393 weights, VRAM 13.5 GB, CPU 2.5 GB
    Layer 36/48: 393 weights, VRAM 15.0 GB, CPU 2.6 GB
    Layer 40/48: 393 weights, VRAM 16.5 GB, CPU 2.8 GB
    Layer 44/48: 393 weights, VRAM 18.0 GB, CPU 2.9 GB
    Layer 48/48: 393 weights, VRAM 19.6 GB, CPU 3.1 GB
  [Qwen3 Streaming] Final VRAM: 19.6 GB (FP4 quantized)
  [Qwen3 Streaming] Done: 1571.8M params, 18867 weights loaded
  Total params:     1.57B
  Frozen params:    1.54B (base model, FP4)
  Trainable params: 30.2M (Hebbian only)
  [Packed MoE] 48 layers packed (6144 experts → contiguous)
  [Flat KV] Enabled: 4096 tokens, 403 MB
Warmup...

============================================================
  Testing D=2 (D=2 baseline)
============================================================
  [EAGLE] Loaded legacy D=2 checkpoint. 0 new layer params initialized randomly.
  [EAGLE-3] Draft head: D=2, 104.9M params, 210 MB, capture layers [8, 24, 47] + Hebbian memory
  Target prefill logits: has_nan=True, min=nan, max=nan
  First decoded token: 0 = '!'
  Target predicts next: 0 = '!'
  Feature layer 8: has_nan=True, min=nan, max=nan
  Feature layer 24: has_nan=True, min=nan, max=nan
  Feature layer 47: has_nan=True, min=nan, max=nan
  Draft tokens:
    [0] 0 = '!'
    [1] 0 = '!'
    [2] 0 = '!'
    [3] 0 = '!'
    [4] 0 = '!'
  Draft logits[0]: has_nan=True, min=nan, max=nan
  Target verify predictions:
    [1] target=0 ('!'), draft=0 ('!') → MATCH
    [2] target=0 ('!'), draft=0 ('!') → MATCH
    [3] target=0 ('!'), draft=0 ('!') → MATCH
    [4] target=0 ('!'), draft=0 ('!') → MATCH
  Accepted: 5/5

  --- Full speculative_generate (max_new=30) ---
  [EAGLE-3] 5 rounds, 21 drafted, 21 accepted (100%), avg 4.2/round
  Output: !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

============================================================
  Testing D=8 (D=8 with random layers 2-7)
============================================================
  [EAGLE] Loaded legacy D=2 checkpoint. 54 new layer params initialized randomly.
  [FE-XT] Draft head: D=8, 356.5M params, 713 MB, capture layers [8, 24, 47] + Hebbian memory
  Target prefill logits: has_nan=True, min=nan, max=nan
  First decoded token: 0 = '!'
  Target predicts next: 0 = '!'
  Feature layer 8: has_nan=True, min=nan, max=nan
  Feature layer 24: has_nan=True, min=nan, max=nan
  Feature layer 47: has_nan=True, min=nan, max=nan
  Draft tokens:
    [0] 0 = '!'
    [1] 0 = '!'
    [2] 0 = '!'
    [3] 0 = '!'
    [4] 0 = '!'
  Draft logits[0]: has_nan=True, min=nan, max=nan
  Target verify predictions:
    [1] target=0 ('!'), draft=0 ('!') → MATCH
    [2] target=0 ('!'), draft=0 ('!') → MATCH
    [3] target=0 ('!'), draft=0 ('!') → MATCH
    [4] target=0 ('!'), draft=0 ('!') → MATCH
  Accepted: 5/5

  --- Full speculative_generate (max_new=30) ---
  [EAGLE-3] 5 rounds, 21 drafted, 21 accepted (100%), avg 4.2/round
  Output: !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

============================================================
  D=2 accepted: 5/5
  D=8 accepted: 5/5
============================================================