============================================================
  Training Flow Bisection
============================================================

[Step 1] load_engine(max_seq_len=4096)...
  [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)
Traceback (most recent call last):
  File "/run/media/echo/Echo/ECHO/training/Prototype Fireecho/tool/kernel/FireEcho Engine/debug_bisect.py", line 43, in <module>
    check(engine, tokenizer, "after load")
  File "/run/media/echo/Echo/ECHO/.venv_infer312/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/training/Prototype Fireecho/tool/kernel/FireEcho Engine/debug_bisect.py", line 23, in check
    logits = engine.forward(ids, use_cache=True, position=0)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/training/Prototype Fireecho/tool/kernel/FireEcho Engine/fireecho_kernel.py", line 9964, in forward
    x = layer(x, self.kv_cache, self._current_seq_id, position, use_cache)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/.venv_infer312/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1779, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/.venv_infer312/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1790, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/training/Prototype Fireecho/tool/kernel/FireEcho Engine/fireecho_kernel.py", line 8820, in forward
    x = x + self.ffn(self.norm2(x))
            ^^^^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/.venv_infer312/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1779, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/.venv_infer312/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1790, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/training/Prototype Fireecho/tool/kernel/FireEcho Engine/fireecho_kernel.py", line 8710, in forward
    expert_out = self.experts[expert_idx](selected)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/.venv_infer312/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1779, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/.venv_infer312/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1790, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/training/Prototype Fireecho/tool/kernel/FireEcho Engine/fireecho_kernel.py", line 7565, in forward
    gate_up = self.gate_up_proj(x)  # [*, 2*intermediate]
              ^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/.venv_infer312/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1779, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/.venv_infer312/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1790, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/run/media/echo/Echo/ECHO/training/Prototype Fireecho/tool/kernel/FireEcho Engine/fireecho_kernel.py", line 7339, in forward
    return F.linear(x, self.weight, self.bias)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: size mismatch, got input (5), mat (5x2048), vec (0)