[FEA]: Generalize autotuning to dynamically generated kernels

首先阅读 issue 中描述的 exhaustive_search 入口点以及 _TimingCandidate 的使用方式，然后跟踪当前配置如何生成 kernel、grid、hint 和参数。当 exhaustive_search 能够支持由每个配置生成的 kernel 和参数，同时保留现有的固定 kernel 行为和 autotuning 候选项时，这项工作就完成了。

Is this a new feature, an improvement, or a change to existing functionality?

Improvement

How would you describe the priority of this feature request?

Low (would be nice)

Please provide a clear description of problem this feature solves

Currently, exhaustive_search takes a single fixed kernel and construct arguments from an arbitrary sequence of configurations. That it takes a fixed kernel makes it unusable in its current form if the config objects themselves generates the kernel.

Feature Description

I'm currently using cutile and metaprogramming to generate kernels, with much better success and less pain than other frameworks. However, I can't use exhaustive_search in its current form, but need to modify it to take kernel generating functions.

Describe your ideal solution

The proposal is essentially to change exhaustive_search, or add a separate case, where we generate the kernel candidate from a config, i.e:

    ... 
    for i, cfg in enumerate(search_space):
        if not quiet and isatty:
            progress(0, i, total, len(errors))
        grid = grid_fn(cfg)
        kernel = kernel_fn(cfg)
        hints = hints_fn(cfg) if hints_fn is not None else {}
        updated_kernel = kernel.replace_hints(**hints)
        candidate = _TimingCandidate(
            config=cfg,
            grid=grid,
            kernel=updated_kernel,
            get_args=lambda _cfg=cfg: args_fn(_cfg),
        )
     ...

Describe any alternatives you have considered

No response

Additional context

No response

Contributing Guidelines

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• I have searched the open feature requests and have found no duplicates for this feature request