[New model] Qwen-Image-2.1 support (rebase + review follow-ups) (#8099)

Signed-off-by: NumberWan <wantszkin2003@gmail.com>
Signed-off-by: SamitHuang <285365963@qq.com>
Signed-off-by: Samit <285365963@qq.com>
Co-authored-by: Isotr0py <Isotr0py@outlook.com>
Co-authored-by: Tianyu Guo <guoty9@mail2.sysu.edu.cn>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: SamitHuang <285365963@qq.com>
Co-authored-by: Gao Han <hgaoaf@connect.ust.hk>
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@@ -163,6 +163,7 @@ The following tables show which models support each feature:
| **Qwen-Image-Edit** | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ✅ (decode) | ❌ | ❌ |
| **Qwen-Image-Edit-2509** | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ (decode) | ✅ | ❌ | ❌ |
| **Qwen-Image-Layered** | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ✅ (decode) | ❌ | ❌ |
| **Qwen-Image-2.1** | ❌ | ❌ | ❓ | ✅ | ✅ | ❌ | ❓ | ❓ | ✅ (decode) | ✅ | ✅ |
| **SenseNova-U1** | ❌ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
| **SenseNova-U1.5** | ❌ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ✅ | ❌ |
| **SenseNova-U1-A3B** | ❌ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
@@ -181,7 +182,8 @@ The following tables show which models support each feature:
> 5. HunyuanImage3 supports step execution. Multi-request step execution requires `TORCH_SDPA`; see [Diffusion Execution Modes](diffusion/execution_modes.md#step-execution).
> 6. BAGEL step execution supports image generation with `bagel.yaml`, `bagel_think.yaml`, and `bagel_single_stage.yaml`; two-stage Thinker execution and explicit single-stage text output remain on their existing complete-request paths. Image requests require `num_inference_steps >= 2`. BAGEL step execution cannot currently be combined with sequence parallelism or a diffusion cache backend; see [Diffusion Execution Modes](diffusion/execution_modes.md#step-execution).
> 7. MammothModa2 runs its DiT stage on the diffusion runner (`StageExecutionType.DIFFUSION`); Cache-DiT is enabled through the standard diffusion-stage knobs on the stage entry of the deploy YAML (`cache_backend: cache_dit`, plus optional `cache_config` / `enable_cache_dit_summary`). The runner installs the backend at startup and the pipeline adopts it per request. Only the repeated main-layer stack is cached; requests with `text_guidance_scale = 1.0` bypass the cache hooks.
> 8. SenseNova-U1-A3B: `--cfg-parallel-size 2` and TP=2 both complete. CFG-P covers t2i 2-branch (`cond`+`uncond`), img2img 2-branch (`cond`+`img_cond` when `img_cfg_scale=1`), and img2img 3-branch (`cond`+`img_cond`+`uncond` when `img_cfg_scale` is neither 1 nor equal to `cfg_scale`; 3 branches on 2 ranks dispatch as `[[0, 2], [1]]`). Cache-DiT does not: the adapter is declared on `SenseNovaU1Model`, but discovery walks `_dit_modules` (`language_model` / `SenseNovaU1ForCausalLM`) and raises. Layerwise CPU offload is a no-op for the same reason — that class has no `_layerwise_offload_blocks_attrs`, so the 72.2 GiB expert weights stay resident.
> 8. Qwen-Image-2.1 (`QwenImage21Pipeline`) handles both text-to-image and image-conditioned generation (up to 4 condition images) and supports LoRA through `QwenImageLoraLoaderMixin`. Ulysses sequence parallelism is wired and ring attention is not supported, but multi-GPU padding e2e and a parity number are not in this PR's H200 results, so SP stays ❓. Cache acceleration (TeaCache / Cache-DiT) is unavailable; its built-in KV cache for the text/condition prefix is a separate feature from those cache backends. Online FP8 is documented in the quantization guide with H200 numbers.
> 9. SenseNova-U1-A3B: `--cfg-parallel-size 2` and TP=2 both complete. CFG-P covers t2i 2-branch (`cond`+`uncond`), img2img 2-branch (`cond`+`img_cond` when `img_cfg_scale=1`), and img2img 3-branch (`cond`+`img_cond`+`uncond` when `img_cfg_scale` is neither 1 nor equal to `cfg_scale`; 3 branches on 2 ranks dispatch as `[[0, 2], [1]]`). Cache-DiT does not: the adapter is declared on `SenseNovaU1Model`, but discovery walks `_dit_modules` (`language_model` / `SenseNovaU1ForCausalLM`) and raises. Layerwise CPU offload is a no-op for the same reason — that class has no `_layerwise_offload_blocks_attrs`, so the 72.2 GiB expert weights stay resident.
### VideoGen