[JIT] Support overriding optimization flags in JIT (#3032)

This PR adds the optimization flags override (`"opt"`) for MLCEngine,
chat and serve when running JIT compilation. Prior to this PR,
the JIT compilation always uses O2 as the optimization flags.

Author: MasterJH5574

python/mlc_llm/cli/serve.py

@@ -31,6 +31,7 @@ class EngineConfigOverride:  # pylint: disable=too-many-instance-attributes
     attention_sink_size: Optional[int] = None
     tensor_parallel_shards: Optional[int] = None
     pipeline_parallel_stages: Optional[int] = None
+    opt: Optional[str] = None
 
     def __repr__(self) -> str:
         out = StringIO()
@@ -53,6 +54,7 @@ def __repr__(self) -> str:
         print(f";attention_sink_size={self.attention_sink_size}", file=out, end="")
         print(f";tensor_parallel_shards={self.tensor_parallel_shards}", file=out, end="")
         print(f";pipeline_parallel_stages={self.pipeline_parallel_stages}", file=out, end="")
+        print(f";opt={self.opt}", file=out, end="")
         return out.getvalue().rstrip()
 
     @staticmethod
@@ -75,6 +77,7 @@ def from_str(source: str) -> "EngineConfigOverride":
         parser.add_argument("--attention_sink_size", type=int, default=None)
         parser.add_argument("--tensor_parallel_shards", type=int, default=None)
         parser.add_argument("--pipeline_parallel_stages", type=int, default=None)
+        parser.add_argument("--opt", type=str, default=None)
         results = parser.parse_args([f"--{i}" for i in source.split(";") if i])
         return EngineConfigOverride(
             max_num_sequence=results.max_num_sequence,
@@ -92,6 +95,7 @@ def from_str(source: str) -> "EngineConfigOverride":
             attention_sink_size=results.attention_sink_size,
             tensor_parallel_shards=results.tensor_parallel_shards,
             pipeline_parallel_stages=results.pipeline_parallel_stages,
+            opt=results.opt,
         )
 
 
@@ -210,6 +214,7 @@ def main(argv):
         additional_models=additional_models,
         tensor_parallel_shards=parsed.overrides.tensor_parallel_shards,
         pipeline_parallel_stages=parsed.overrides.pipeline_parallel_stages,
+        opt=parsed.overrides.opt,
         speculative_mode=parsed.speculative_mode,
         prefix_cache_mode=parsed.prefix_cache_mode,
         max_num_sequence=parsed.overrides.max_num_sequence,

python/mlc_llm/interface/chat.py

@@ -89,13 +89,15 @@ class ModelConfigOverride(ConfigOverrideBase):  # pylint: disable=too-many-insta
     attention_sink_size: Optional[int] = None
     tensor_parallel_shards: Optional[int] = None
     pipeline_parallel_stages: Optional[int] = None
+    opt: Optional[str] = None
 
     @staticmethod
     def from_str(source: str) -> "ModelConfigOverride":
         """Parse model config override values from a string."""
         parser = argparse.ArgumentParser(description="model config override values")
         parser.add_argument("--tensor_parallel_shards", type=int, default=None)
         parser.add_argument("--pipeline_parallel_stages", type=int, default=None)
+        parser.add_argument("--opt", type=str, default=None)
         parser.add_argument("--context_window_size", type=int, default=None)
         parser.add_argument("--sliding_window_size", type=int, default=None)
         parser.add_argument("--prefill_chunk_size", type=int, default=None)
@@ -105,6 +107,7 @@ def from_str(source: str) -> "ModelConfigOverride":
         return ModelConfigOverride(
             tensor_parallel_shards=results.tensor_parallel_shards,
             pipeline_parallel_stages=results.pipeline_parallel_stages,
+            opt=results.opt,
             context_window_size=results.context_window_size,
             sliding_window_size=results.sliding_window_size,
             prefill_chunk_size=results.prefill_chunk_size,
@@ -294,6 +297,7 @@ def chat(
                 attention_sink_size=overrides.attention_sink_size,
                 tensor_parallel_shards=overrides.tensor_parallel_shards,
                 pipeline_parallel_stages=overrides.pipeline_parallel_stages,
+                opt=overrides.opt,
             ),
         )
     ).chat()

python/mlc_llm/interface/serve.py

@@ -28,6 +28,7 @@ def serve(
     additional_models: List[Union[str, Tuple[str, str]]],
     tensor_parallel_shards: Optional[int],
     pipeline_parallel_stages: Optional[int],
+    opt: Optional[str],
     max_num_sequence: Optional[int],
     max_total_sequence_length: Optional[int],
     max_single_sequence_length: Optional[int],
@@ -61,6 +62,7 @@ def serve(
             additional_models=additional_models,
             tensor_parallel_shards=tensor_parallel_shards,
             pipeline_parallel_stages=pipeline_parallel_stages,
+            opt=opt,
             max_num_sequence=max_num_sequence,
             max_total_sequence_length=max_total_sequence_length,
             max_single_sequence_length=max_single_sequence_length,

python/mlc_llm/serve/config.py

@@ -46,9 +46,22 @@ class EngineConfig:  # pylint: disable=too-many-instance-attributes
 
     tensor_parallel_shards : Optional[int]
         Number of shards to split the model into in tensor parallelism multi-gpu inference.
+        When "model_lib" is given, this field will be ignored, and the tensor_parallel_shards
+        in the model_lib metadata will be used.
 
     pipeline_parallel_stages : Optional[int]
         Number of pipeline stages to split the model layers for pipeline parallelism.
+        When "model_lib" is given, this field will be ignored, and the pipeline_parallel_stages
+        in the model_lib metadata will be used.
+
+    opt : Optional[str]
+        The optimization flags for JIT compilation.
+        When "model_lib" is given, this field will be ignored.
+        MLC LLM maintains a predefined set of optimization flags,
+        denoted as O0, O1, O2, O3, where O0 means no optimization, O2 means majority of them,
+        and O3 represents extreme optimization that could potentially break the system.
+        Meanwhile, optimization flags could be explicitly specified via details knobs, e.g.
+        "cublas_gemm=1;cudagraph=0".
 
     gpu_memory_utilization : Optional[float]
         A number in (0, 1) denoting the fraction of GPU memory used by the server in total.
@@ -127,6 +140,7 @@ class EngineConfig:  # pylint: disable=too-many-instance-attributes
     mode: Optional[Literal["local", "interactive", "server"]] = None
     tensor_parallel_shards: Optional[int] = None
     pipeline_parallel_stages: Optional[int] = None
+    opt: Optional[str] = None
     gpu_memory_utilization: Optional[float] = None
     kv_cache_page_size: int = 16
     max_num_sequence: Optional[int] = None

python/mlc_llm/serve/engine_base.py

@@ -159,6 +159,7 @@ def _convert_model_info(model: ModelInfo) -> Tuple[str, str]:
                 "tensor_parallel_shards": engine_config.tensor_parallel_shards,
                 "pipeline_parallel_stages": engine_config.pipeline_parallel_stages,
                 "max_batch_size": engine_config.max_num_sequence,
+                "opt": engine_config.opt,
             }
 
             model_lib = jit.jit(