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ComfyUI native single-file loader fails on all Comfy-Org checkpoints: _Block expects split q/k/v but checkpoints ship fused proj.qkv (AttributeError: 'NoneType' object has no attribute 'dtype')

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Valutazione

Difficoltà
2/5
Tempo stimato
1-3 ore
Idoneità per principianti
66/100
Tipo di issue
Bug
Chiarezza
Specificata chiaramente
Stato di attività
Attiva
Stack tecnologico
python, pytorch
Ambito
backend

Direzione di ricerca

Inizia da comfyui/moss-image/model.py, confronta _Block con _TextBlock e verifica come il loader nativo associa le chiavi del checkpoint. Conferma le chiavi fuse proj.qkv segnalate rispetto alle aspettative per proj.q/k/v separate. Poi carica un checkpoint Comfy-Org in un singolo file e verifica che raggiunga il campionamento senza pesi di proiezione mancanti. Il lavoro è completato quando il loader nativo gestisce correttamente i checkpoint segnalati.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Summary

MOSSImageUNETLoader (the native single-file loader) cannot load any of the four Comfy-Org/MOSS-Image single-file checkpoints. It fails immediately with:

AttributeError: 'NoneType' object has no attribute 'dtype'

Root cause: _Block in comfyui/moss-image/model.py declares separate proj.q / proj.k / proj.v / proj.o linears, but every Comfy-Org repackaged checkpoint stores a fused proj.qkv.weight [3*dim, dim]. Nothing populates proj.q/k/v, so under ComfyUI's DynamicVRAM lazy init they stay None and line 96 blows up.

Note this is inconsistent with _TextBlock in the same file, which already uses fused self.qkv — so it looks like a simple oversight, not an intentional design difference.

Environment
ComfyUI 0.39.0 (d49e888)
comfy-aimdo present → DynamicVRAM enabled (comfy.memory_management.aimdo_enabled = True)
Custom node comfyui/moss-image copied to custom_nodes/moss-image/
Python 3.12
GPU 24 GB VRAM laptop (CUDA 13.x, torch 2.14.1+cu130)
Repo revision 95559c9 (docs: use official arXiv BibTeX citation)

Steps to reproduce

  1. Download Comfy-Org/MOSS-Image → diffusion_models/moss_image_base_int8_convrot.safetensors (5.41 GB), text_encoders/qwen3.5_9b_w4a8_gptq.safetensors, vae/flux2-vae.safetensors into the standard ComfyUI/models/{diffusion_models,text_encoders,vae}/ folders.
  2. Load the node MOSS-Image UNET Loader (MOSSImageUNETLoader) with unet_name = moss_image_base_int8_convrot.safetensors.
  3. Queue any prompt.

Result: node fails during model load, before sampling starts.

Evidence — checkpoint key layout

All four Comfy-Org single-file DiT checkpoints use fused qkv, zero split q/k/v:

Checkpoint proj.qkv.weight proj.{q,k,v}.weight
moss_image_base_int8_convrot.safetensors 42 0
moss_image_sft_int8_convrot.safetensors 42 0
moss_image_base_bf16.safetensors 42 0
moss_image_sft_bf16.safetensors 42 0

Example keys from moss_image_base_int8_convrot.safetensors (layers.0.*, 42 blocks total):

layers.0.proj.qkv.weight        [9216, 3072]     # dim = 3072 -> 3*dim
layers.0.proj.qkv.weight_scale  [9216, 1]
layers.0.proj.o.weight          [3072, 3072]
layers.0.proj.ffn_up_gate.weight[16384, 3072]
layers.0.proj.ffn_down.weight   [3072, 8192]

For comparison, the original diffusers repo OpenMOSS-Team/MOSS-Image-Base stores split keys — transformer/diffusion_pytorch_model.safetensors.index.json maps 126 layers.N.proj.{q,k,v}.weight entries (42 blocks × 3; 60 in shard -00001-of-00003, 66 in -00002-of-00003) — which is exactly what the current _Block expects. That is why the HF Loader path works and only the native single-file path breaks.

Root cause in code

comfyui/moss-image/model.py (revision 95559c9), _Block.__init__ lines 84–89:

self.proj = nn.ModuleDict(
    {
        name: operations.Linear(dim, dim, bias=False, device=device, dtype=dtype)
        for name in ("q", "k", "v", "o")
    }
)

and _Block.forward lines 96–100:

dtype = self.proj["q"].weight.dtype                                    # <-- raises
q = self.q_norm(self.proj["q"](y).unflatten(-1, (self.heads, -1))).flatten(2)
k = self.k_norm(self.proj["k"](y).unflatten(-1, (self.heads, -1))).flatten(2)
x = x + self.proj["o"](_attention(q, k, self.proj["v"](y), rope, self.heads)) * gate_a[:, None]

load_state_dict(..., strict=False) confirms the mismatch:

missing_keys    : ['proj.k.weight', 'proj.q.weight', 'proj.v.weight']
unexpected_keys : ['proj.qkv.weight']

With comfy-aimdo enabled, comfy.ops.disable_weight_init.Linear.__init__ skips torch.nn.Linear.__init__ and leaves self.weight = None (it is materialised lazily in _load_from_state_dict, only for keys present in the checkpoint). Since proj.q.weight is absent, it stays None → .dtype on None → AttributeError.

Fix that works (verified)

Patch _Block to a fused qkv projection, mirroring _TextBlock:

self.proj = nn.ModuleDict(
    {
        "qkv": operations.Linear(dim, 3 * dim, bias=False, device=device, dtype=dtype),
        "o": operations.Linear(dim, dim, bias=False, device=device, dtype=dtype),
    }
)

def forward(self, x, rope, modulation):
    shift_a, scale_a, gate_a, shift_f, scale_f, gate_f = modulation.unbind(1)
    y = self.norm1(x) * (1 + scale_a[:, None]) + shift_a[:, None]
    dtype = self.proj["qkv"].weight.dtype
    y = y.to(dtype)
    q, k, v = self.proj["qkv"](y).chunk(3, -1)
    q = self.q_norm(q.unflatten(-1, (self.heads, -1))).flatten(2)
    k = self.k_norm(k.unflatten(-1, (self.heads, -1))).flatten(2)
    x = x + self.proj["o"](_attention(q, k, v, rope, self.heads)) * gate_a[:, None]
    ...

After the patch, load_state_dict reports no missing/unexpected keys and generation succeeds.

Verified output with the patch (ComfyUI 0.39.0, int8 single-file)

Official recipe from the workflow (50 steps, CFG 3, Shift 5, SLG layer 22, 1024×1024, Euler/sgm_uniform):

Seed CFG Steps Wall time Peak VRAM
42 3.0 50 71.7 s ~10.5 GB / 24 GB
1234 3.5 50 48.8 s ~10.5 GB / 24 GB

≈1.15 it/s, no OOM, images are clean (not noise/black).

Suggestion

Since the fused layout is what Comfy-Org ships (and what HF diffusers actually uses for text_embedder), making _Block fused is likely the low-risk default. Options:

  1. Preferred: switch _Block to fused qkv (matches _TextBlock and all Comfy-Org checkpoints).
  2. Accept both by branching on the key layout.
  3. Or add a key-remap in load_model_state() that splits proj.qkv.weight into proj.q/k/v when the split layout is detected — this would keep the original diffusers shards loading through the native loader too.

Also worth documenting: the native single-file loader currently only works with the diffusers-layout shards, not the Comfy-Org repackaged single files linked from the main README's day-0 support note.

Happy to send a PR for option 1 if that's the direction you prefer.

中文摘要

comfyui/moss-image/model.py 嘅 _Block 用分開 q/k/v/o，但 Comfy-Org 全部 4 個單檔 checkpoint 都係融合 proj.qkv（42 個 block、[9216,3072]），proj.q/k/v 完全冇 key → 開 DynamicVRAM 時 weight 保持 None → AttributeError: 'NoneType' object has no attribute 'dtype'。

同一份檔案嘅 _TextBlock 本身已經用融合 qkv，所以似係手誤。改成融合 qkv 之後實測正常出圖（1024²、50 步、48.8–71.7 秒、峰值 ~10.5GB VRAM）。而原始 diffusers 格式（OpenMOSS-Team/MOSS-Image-Base）確實係分開 q/k/v，所以只有 native 單檔 loader 配 Comfy-Org 檔先爆。

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