[Relax][Backend] Implement R.call_py_func operator for calling Python functions from compiled TVM

[tlopex]

This PR implements the R.call_py_func operator that allows compiled TVM Relax modules to call Python functions at runtime. This enables integration between TVM's compiled code and Python through a robust VM backend implementation.

Simple Usage with BasePyModule

@I.ir_module
class MyModule(BasePyModule):
    @I.pyfunc
    def torch_relu(self, x):
        return torch.relu(x)
    
    @R.function
    def forward(x: R.Tensor((10,), "float32")) -> R.Tensor((10,), "float32"):
        return R.call_py_func("torch_relu", (x,), out_sinfo=R.Tensor((10,), "float32"))

Direct VM Backend Usage (Manual)

# Manually register Python function with VM backend
register_func = tvm.get_global_func("vm.builtin.register_py_func")
register_func("my_func", my_python_function)

# Use in Relax function (compiled to VM backend)
@R.function
def test(x: R.Tensor((5,), "float32")) -> R.Tensor((5,), "float32"):
    return R.call_py_func("my_func", (x,), out_sinfo=R.Tensor((5,), "float32"))

# Manual cleanup (required for direct VM backend usage)
clear_func = tvm.get_global_func("vm.builtin.clear_py_func_registry")
clear_func()

[tlopex]

cc @MasterJH5574

[MasterJH5574]

Looks great, thank you @tlopex!