[CI] Select mirror_hardwares presets via MIRROR_HW (H100/B200) (#5543)

Signed-off-by: wangyu <410167048@qq.com>
Signed-off-by: lishunyang12 <lishunyang12@163.com>
Signed-off-by: [Your Name] <your.email@example.com>
Signed-off-by: wangyu <53896905+yenuo26@users.noreply.github.com>
Signed-off-by: Bo Li <22713281+bobboli@users.noreply.github.com>
Co-authored-by: lishunyang12 <lishunyang12@163.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Bo Li <22713281+bobboli@users.noreply.github.com>

vllm_omni/diffusion/models/diffusers_adapter/pipeline_diffusers_adapter.py

@@ -1,5 +1,5 @@
 # SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
 """Diffusers backend adapter for vLLM-Omni.
 
 Provides a black-box wrapper around any 🤗 Diffusers pipeline, enabling
@@ -44,13 +44,21 @@ logger = logging.getLogger(__name__)
 # with the accuracy tests' diffusers reference runs so both sides of a
 # similarity comparison resolve to the same backend on any given image
 # (hub kernels may lack a build variant for the image's torch).
-CUDA_FLASH_ATTENTION_BACKEND_ATTEMPTS: list[str] = [
+# Automatic / FLASH_ATTN selection walks the full chain. Explicit Hub
+# options attempt only their matching Diffusers backend names.
+CUDA_FLASH_ATTN_3_HUB_ATTEMPTS: list[str] = [
     "_flash_3_hub",
     "_flash_3_varlen_hub",
-    "_flash_3",
-    "_flash_varlen_3",
+]
+CUDA_FLASH_ATTN_HUB_ATTEMPTS: list[str] = [
     "flash_hub",
     "flash_varlen_hub",
+]
+CUDA_FLASH_ATTENTION_BACKEND_ATTEMPTS: list[str] = [
+    *CUDA_FLASH_ATTN_3_HUB_ATTEMPTS,
+    "_flash_3",
+    "_flash_varlen_3",
+    *CUDA_FLASH_ATTN_HUB_ATTEMPTS,
     "flash",
     "flash_varlen",
     "_native_flash",
@@ -293,6 +301,24 @@ class DiffusersAdapterPipeline(nn.Module, DiffusionPipelineProfilerMixin):
     # Wrap settings, inputs, and outputs
     # ------------------------------------------------------------------
 
+    @staticmethod
+    def _is_blackwell_gpu() -> bool:
+        """Return True on Blackwell-class CUDA GPUs (sm_10x / sm_11x / sm_12x)."""
+        capability = None
+        try:
+            capability = current_omni_platform.get_device_capability()
+        except Exception:
+            capability = None
+        if capability is not None:
+            return capability.major in (10, 11, 12)
+        if torch.cuda.is_available():
+            try:
+                major, _ = torch.cuda.get_device_capability()
+                return major in (10, 11, 12)
+            except Exception:
+                return False
+        return False
+
     def _set_attention_backend(self) -> None:
         """Set the attention backend.
 
@@ -308,6 +334,20 @@ class DiffusersAdapterPipeline(nn.Module, DiffusionPipelineProfilerMixin):
         attention_backend_config = default_spec.backend if default_spec is not None else None
         attention_backend_attempts: list[str] = []
         match attention_backend_config:
+            case "FLASH_ATTN_3_HUB":
+                if self._is_blackwell_gpu():
+                    raise ValueError(
+                        "FLASH_ATTN_3_HUB was explicitly selected for a Diffusers adapter on "
+                        "Blackwell, but no runnable sm_10x+ Flash Attention kernel is available."
+                    )
+                attention_backend_attempts.extend(CUDA_FLASH_ATTN_3_HUB_ATTEMPTS)
+            case "FLASH_ATTN_HUB":
+                if self._is_blackwell_gpu():
+                    raise ValueError(
+                        "FLASH_ATTN_HUB was explicitly selected for a Diffusers adapter on "
+                        "Blackwell, but no runnable sm_10x+ Flash Attention kernel is available."
+                    )
+                attention_backend_attempts.extend(CUDA_FLASH_ATTN_HUB_ATTEMPTS)
             case "FLASH_ATTN" | None:
                 if current_omni_platform.is_rocm():
                     attention_backend_attempts.append("aiter")
@@ -318,17 +358,31 @@ class DiffusersAdapterPipeline(nn.Module, DiffusionPipelineProfilerMixin):
                         "Unknown diffusers attention backend option for MUSA platform. Falling back to SDPA."
                     )
                     attention_backend_attempts.append("native")
+                elif self._is_blackwell_gpu():
+                    # Installed FA2/FA3 (and HF FA3 hub) wheels are typically Hopper-only.
+                    # set_attention_backend("_flash_3*") can succeed on import, then crash
+                    # at runtime with "no kernel image is available for execution on the device".
+                    if attention_backend_config is not None:
+                        raise ValueError(
+                            f"{attention_backend_config} was explicitly selected for a Diffusers adapter on "
+                            "Blackwell, but no runnable sm_10x+ Flash Attention kernel is available."
+                        )
+                    attention_backend_attempts.append("native")
                 else:
                     attention_backend_attempts.extend(CUDA_FLASH_ATTENTION_BACKEND_ATTEMPTS)
             case "SAGE_ATTN":
-                attention_backend_attempts.extend(["sage_hub", "sage", "sage", "sage_varlen"])
+                attention_backend_attempts.extend(["sage_hub", "sage", "sage_varlen"])
             case "ASCEND":
                 attention_backend_attempts.append("_native_npu")
             case "TORCH_SDPA":
                 attention_backend_attempts.append("native")
+            case "CUDNN_ATTN" | "FLASHINFER_ATTN" | "TRTLLM_ATTN":
+                raise ValueError(
+                    f"{attention_backend_config} was explicitly selected, but Diffusers adapters do not "
+                    "provide a binding for this vLLM-Omni backend. Select TORCH_SDPA or a Diffusers-native backend."
+                )
             case _:
-                logger.warning(f"Invalid attention backend: {attention_backend_config}. Falling back to SDPA.")
-                attention_backend_attempts.append("native")
+                raise ValueError(f"Invalid Diffusers attention backend: {attention_backend_config}.")
 
         attempt_errors: list[str] = []
         set_backend: str | None = None
@@ -340,8 +394,15 @@ class DiffusersAdapterPipeline(nn.Module, DiffusionPipelineProfilerMixin):
             except Exception as e:
                 attempt_errors.append(str(e))
 
-        # If all attempts fail, fallback to SDPA and warn the user about the failures
+        # Automatic selection may use native SDPA as its final safe choice. An
+        # explicitly configured backend must either be installed or raise.
         if len(attempt_errors) == len(attention_backend_attempts):
+            if attention_backend_config is not None:
+                raise RuntimeError(
+                    f"Failed to set explicitly selected attention backend '{attention_backend_config}' for "
+                    f"diffusers pipeline {self._pipeline.__class__.__name__}. Attempts: "
+                    f"{dict(zip(attention_backend_attempts, attempt_errors))}"
+                )
             self._pipeline.transformer.set_attention_backend("native")
             logger.warning(
                 f"Failed to set attention backend '{attention_backend_config}' for "