vllm.compilation.monitor ¶

def end_monitoring_torch_compile(vllm_config: VllmConfig):
    compilation_config: CompilationConfig = vllm_config.compilation_config
    if compilation_config.mode == CompilationMode.VLLM_COMPILE:
        logger.info_once(
            "torch.compile takes %.2f s in total",
            compilation_config.compilation_time,
            scope="local",
        )
        global context_manager
        if context_manager is not None:
            context_manager.__exit__(None, None, None)
            context_manager = None

def set_cudagraph_capturing_enabled(enabled: bool):
    global cudagraph_capturing_enabled
    cudagraph_capturing_enabled = enabled

def start_monitoring_torch_compile(vllm_config: VllmConfig):
    global torch_compile_start_time
    torch_compile_start_time = time.time()

    compilation_config: CompilationConfig = vllm_config.compilation_config
    path = vllm_config.compile_debug_dump_path()
    if compilation_config.mode == CompilationMode.VLLM_COMPILE and path:
        import depyf

        path.mkdir(parents=True, exist_ok=True)
        logger.debug("Dumping depyf output to %s", path)
        global context_manager
        context_manager = depyf.prepare_debug(path.as_posix())
        context_manager.__enter__()

def validate_cudagraph_capturing_enabled():
    # used to monitor whether a cudagraph capturing is legal at runtime.
    # should be called before any cudagraph capturing.
    # if an illegal cudagraph capturing happens, raise an error.
    global cudagraph_capturing_enabled
    if not cudagraph_capturing_enabled:
        raise RuntimeError(
            "CUDA graph capturing detected at an inappropriate "
            "time. This operation is currently disabled."
        )