[Multimodal][torch.compile] Add compilation config field for turning off ViT/MM compile (#28242)

Signed-off-by: Lucas Kabela <lucaskabela@meta.com>

tests/compile/test_multimodal_compile.py

@@ -3,10 +3,17 @@
 import pytest
 
 from vllm.compilation.counter import compilation_counter
+from vllm.config import VllmConfig
 from vllm.config.compilation import CompilationMode
 from vllm.platforms import current_platform
 
 
+def test_compile():
+    vllm_config = VllmConfig()
+    # Default configuration compiles mm encoder
+    assert vllm_config.compilation_config.compile_mm_encoder
+
+
 # forked needed to workaround https://github.com/vllm-project/vllm/issues/21073
 @pytest.mark.forked
 @pytest.mark.skipif(not current_platform.is_cuda(), reason="Skip if not cuda")
@@ -31,8 +38,33 @@ def test_qwen2_5_vl_compilation(vllm_runner, monkeypatch):
         vllm_runner(
             "Qwen/Qwen2.5-VL-3B-Instruct",
             max_model_len=2048,
-            gpu_memory_utilization=0.7,
+            gpu_memory_utilization=0.8,
             compilation_config={"mode": CompilationMode.VLLM_COMPILE},
         ) as _,
     ):
         pass
+
+
+# forked needed to workaround https://github.com/vllm-project/vllm/issues/21073
+@pytest.mark.forked
+@pytest.mark.skipif(not current_platform.is_cuda(), reason="Skip if not cuda")
+def test_qwen2_5_vl_no_vit_compilation(vllm_runner, monkeypatch):
+    """Test that Qwen2.5-VL vision submodules are not compiled when the
+    config is passed off
+    """
+    # Disable multiprocessing so that the counter is in the same process
+    monkeypatch.setenv("VLLM_ENABLE_V1_MULTIPROCESSING", "0")
+
+    with (
+        compilation_counter.expect(num_models_seen=1),
+        vllm_runner(
+            "Qwen/Qwen2.5-VL-3B-Instruct",
+            max_model_len=2048,
+            gpu_memory_utilization=0.8,
+            compilation_config={
+                "mode": CompilationMode.VLLM_COMPILE,
+                "compile_mm_encoder": False,
+            },
+        ) as _,
+    ):
+        pass

vllm/config/compilation.py

@@ -150,6 +150,7 @@ class CompilationConfig:
         - [`backend`][vllm.config.CompilationConfig.backend]
         - [`custom_ops`][vllm.config.CompilationConfig.custom_ops]
         - [`splitting_ops`][vllm.config.CompilationConfig.splitting_ops]
+        - [`compile_mm_encoder`][vllm.config.CompilationConfig.compile_mm_encoder]
     - CudaGraph capture:
         - [`use_cudagraph`][vllm.config.CompilationConfig.use_cudagraph]
         - [`cudagraph_mode`][vllm.config.CompilationConfig.cudagraph_mode]
@@ -250,6 +251,13 @@ class CompilationConfig:
     disabled when running with Inductor: mode>=VLLM_COMPILE and use_inductor=True.
     Inductor generates (fused) Triton kernels for disabled custom ops."""
     splitting_ops: list[str] | None = None
+
+    """
+    Provide control over whether to compile the multimodal encoder 
+    such as Qwen2_5_vl 
+    """
+    compile_mm_encoder: bool = True
+
     """A list of ops to exclude from cudagraphs, used in piecewise compilation.
 
     The behavior depends on use_inductor_graph_partition:

vllm/model_executor/models/qwen2_5_vl.py

@@ -67,6 +67,9 @@ from vllm.model_executor.layers.linear import (
 from vllm.model_executor.layers.quantization import QuantizationConfig
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 from vllm.model_executor.models.module_mapping import MultiModelKeys
+from vllm.model_executor.models.transformers.utils import (
+    should_torch_compile_mm_vit,
+)
 from vllm.multimodal import MULTIMODAL_REGISTRY
 from vllm.multimodal.evs import (
     compute_mrope_for_media,
@@ -464,6 +467,7 @@ class Qwen2_5_VisionAttention(nn.Module):
         "seqlens": 0,
     },
     mark_unbacked_dims={"seqlens": 0},
+    enable_if=should_torch_compile_mm_vit,
 )
 class Qwen2_5_VisionBlock(nn.Module):
     def __init__(
@@ -529,7 +533,8 @@ class Qwen2_5_VisionBlock(nn.Module):
 @support_torch_compile(
     dynamic_arg_dims={
         "x": 0,
-    }
+    },
+    enable_if=should_torch_compile_mm_vit,
 )
 class Qwen2_5_VisionPatchEmbed(nn.Module):
     def __init__(
@@ -560,7 +565,8 @@ class Qwen2_5_VisionPatchEmbed(nn.Module):
 @support_torch_compile(
     dynamic_arg_dims={
         "x": 0,
-    }
+    },
+    enable_if=should_torch_compile_mm_vit,
 )
 class Qwen2_5_VisionPatchMerger(nn.Module):
     def __init__(

vllm/model_executor/models/transformers/utils.py

@@ -205,3 +205,14 @@ def can_enable_torch_compile(vllm_config: "VllmConfig") -> bool:
     # Dynamic rope scaling is not compatible with torch.compile
     rope_scaling: dict = getattr(text_config, "rope_scaling", None) or {}
     return rope_scaling.get("rope_type") != "dynamic"
+
+
+def should_torch_compile_mm_vit(vllm_config: "VllmConfig") -> bool:
+    """
+    Callable to be passed to `@support_torch_compile`'s `enable_if` argument.
+
+    Defaults to `True` but is disabled in the following situations:
+
+    - The model uses dynamic rope scaling.
+    """
+    return vllm_config.compilation_config.compile_mm_encoder