Refactor building system and adding compiled products

Now, we can build Function, IRModule, Task and FlowGraph to CompiledFunction, CompiledModule, CompiledTask and CompiledModule. The compiled products can be saved on the disk and loaded for running.

The CompiledTask has a lib.so that contains all the scheduled kernels. So we will not have the problem of loading thousands of dynamic libraries when we support dynamic shape & kernel tuning (e.g., 100 operators * 200 schedules for each operator).

The CompiledGraph contains a C runtime that invokles the kernels and allocates memory. With this, we do not need CUDA graph to get rid of the framework overhead when inference. The CompiledGraph can be stored as a single file on the disk. Thus, we can compile one model on one machine and then tune & run the model on another machine.

Minors

• Add target argument to build_task and build_ir_module to specify the target for code generation and underlying compiler (e.g., nvcc vs. gcc)
• Move IRModule from hidet.ir.func to hidet.ir.module.
• Changed the format to define tuning space (may change again in the future).