[XPU] update bagel modeling to remove cuda hardcode, add xpu stage_config (#1931)

Signed-off-by: Chendi Xue <chendi.xue@intel.com>
Signed-off-by: Hongsheng Liu <liuhongsheng4@huawei.com>
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>

examples/offline_inference/bagel/end2end.py

@@ -34,7 +34,14 @@ def parse_args():
         help="Path to input image for img2img.",
     )
 
-    # Omni runtime init args
+    parser.add_argument(
+        "--output",
+        type=str,
+        default=".",
+        help="Output directory to save images.",
+    )
+
+    # OmniLLM init args
     parser.add_argument("--log-stats", action="store_true", default=False)
     parser.add_argument("--init-sleep-seconds", type=int, default=20)
     parser.add_argument("--batch-timeout", type=int, default=5)
@@ -70,6 +77,7 @@ def parse_args():
 
 def main():
     args = parse_args()
+    os.makedirs(args.output, exist_ok=True)
     model_name = args.model
     prompts: list[OmniPromptType] = []
     try:
@@ -172,13 +180,13 @@ def main():
     img_idx = 0
     for req_output in omni_outputs:
         images = getattr(req_output, "images", None)
+
         if not images:
             continue
 
         for j, img in enumerate(images):
-            save_path = f"output_{img_idx}_{j}.png"
+            save_path = os.path.join(args.output, f"output_{img_idx}_{j}.png")
             img.save(save_path)
-            print(f"[Info] Saved image to {save_path}")
         img_idx += 1
 
     print(omni_outputs)

vllm_omni/model_executor/models/bagel/bagel.py

@@ -41,6 +41,7 @@ from vllm.multimodal.processing import (
 )
 from vllm.transformers_utils.processors.bagel import BagelProcessor
 
+from vllm_omni.diffusion.distributed.utils import get_local_device
 from vllm_omni.diffusion.models.bagel.autoencoder import (
     AutoEncoderParams,
     DiagonalGaussian,
@@ -439,7 +440,7 @@ class OmniBagelForConditionalGeneration(BagelForConditionalGeneration):
         self._end_of_image_id = int(_tok.convert_tokens_to_ids("<|vision_end|>"))
 
         self._vae_token_mask: torch.Tensor | None = None
-
+        self.device = get_local_device()
         self._install_mot_modules(config)
 
     def _install_mot_modules(self, config):
@@ -627,7 +628,7 @@ class OmniBagelForConditionalGeneration(BagelForConditionalGeneration):
             )
             pos_embed = self.latent_pos_embed([vae_position_ids])
             packed_timesteps = torch.tensor([timestep], device=padded_latent.device)
-            with torch.amp.autocast("cuda", dtype=torch.bfloat16):
+            with torch.amp.autocast(self.device.type, dtype=torch.bfloat16):
                 timestep_embeds = self.time_embedder(packed_timesteps.to(padded_latent))
             vae_embeds = self.vae2llm(latent) + timestep_embeds + pos_embed
 

vllm_omni/platforms/xpu/stage_configs/bagel.yaml

@@ -0,0 +1,86 @@
+# stage config for running bagel-7b-mot with architecture of OmniLLM.
+
+stage_args:
+  - stage_id: 0
+    stage_type: llm
+    prompt_expand_func: vllm_omni.model_executor.stage_input_processors.bagel.expand_cfg_prompts
+    runtime:
+      devices: "0"
+      # 3 = 1 user prompt + 2 CFG companions (text-unconditional + image-unconditional).
+      max_batch_size: 3
+    engine_args:
+      model_stage: thinker
+      model_arch: OmniBagelForConditionalGeneration
+      worker_type: ar
+      scheduler_cls: vllm_omni.core.sched.omni_ar_scheduler.OmniARScheduler
+      gpu_memory_utilization: 0.9
+      enforce_eager: true
+      trust_remote_code: true
+      engine_output_type: text
+      distributed_executor_backend: "mp"
+      enable_prefix_caching: false
+      max_num_batched_tokens: 16384
+      tensor_parallel_size: 1
+      quantization: fp8
+      omni_kv_config:
+        need_send_cache: true
+        kv_transfer_criteria:
+          type: prefill_finished #or special token generated
+    final_output: true
+    final_output_type: text
+    is_comprehension: true
+    default_sampling_params:
+      temperature: 0.4
+      top_p: 0.9
+      top_k: 1
+      max_tokens: 2048
+      seed: 52
+      detokenize: True
+      repetition_penalty: 1.05
+
+  - stage_id: 1
+    stage_type: diffusion
+    cfg_kv_collect_func: vllm_omni.model_executor.stage_input_processors.bagel.collect_cfg_kv_caches
+    runtime:
+      devices: "1"
+      max_batch_size: 1
+    engine_args:
+      model_stage: dit
+      gpu_memory_utilization: 0.9
+      enforce_eager: true
+      trust_remote_code: true
+      engine_output_type: image
+      distributed_executor_backend: "mp"
+      enable_prefix_caching: false
+      max_num_batched_tokens: 32768
+      tensor_parallel_size: 1
+      omni_kv_config:
+        need_recv_cache: true
+    engine_input_source: [0]
+
+    final_output: true
+    final_output_type: image
+    is_comprehension: false
+    default_sampling_params:
+      seed: 52
+
+# Runtime edges
+runtime:
+  enabled: true
+  defaults:
+    window_size: -1
+    max_inflight: 1
+
+  # Distributed connectors configuration (optional)
+  # More connectors will be supported in the future.
+  connectors:
+    shared_memory_connector:
+      name: SharedMemoryConnector
+      extra:
+        shm_threshold_bytes: 65536 # 64KB threshold
+
+
+  edges:
+    - from: 0
+      to: 1
+      window_size: -1