[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>

vllm_omni/diffusion/data.py

@@ -16,7 +16,7 @@ import diffusers
 import huggingface_hub
 import torch
 from PIL import Image
-from pydantic import Field, model_validator
+from pydantic import model_validator
 from typing_extensions import Self
 from vllm.config.utils import config
 from vllm.logger import init_logger
@@ -981,6 +981,19 @@ class OmniDiffusionConfig:
 
     # Compilation
     enforce_eager: bool = False
+    # Capture fixed-shape KV-cache decode (denoising) steps into CUDA graphs.
+    # Currently only Qwen-Image-2.1's transformer implements this; other models
+    # ignore the flag. This is a per-model diffusion path, independent of the
+    # AR engine's ``compilation_config.cudagraph_mode`` (which does not apply
+    # to diffusion stages). It stacks with ``diffusion_compile_granularity``:
+    # the DiT blocks are still torch.compile'd and graph capture records the
+    # compiled (fused) kernels, while inductor's own cudagraphs stay off.
+    # ``enforce_eager=True`` forces eager decode and
+    # disables capture regardless of this flag; unsupported configurations
+    # (SP/TP, ring, HSDP, dynamic LoRA, padded masks, quantized prefix KV, or
+    # a second in-flight request aliasing the same graph key) log and fall
+    # back to eager decode.
+    enable_cuda_graph_decode: bool = True
     # Controls the generic compilation path used when a pipeline does not
     # provide its own setup_compile() implementation.
     diffusion_compile_granularity: str = "regional"
@@ -1140,7 +1153,7 @@ class OmniDiffusionConfig:
     request_batch_max_wait_ms: float = 0.0
 
     # Supplementary model specific parameters
-    extras: dict[str, Any] = Field(default_factory=dict)
+    extras: dict[str, Any] = field(default_factory=dict)
 
     @property
     def is_moe(self) -> bool: