Relax support auto tune for opencl

#1

Dear I am using this branch TVM:

And I want to auto tune my tir using meta_schedule.tune_tir but I got below error

Traceback (most recent call last):
  File "/mnt/e/ubuntu_code/relax/apps/relax_examples/my_test.py", line 154, in <module>
    database = ms.tune_tir(
  File "/mnt/e/ubuntu_code/relax/python/tvm/meta_schedule/tir_integration.py", line 134, in tune_tir
    TuneContext(
  File "/mnt/e/ubuntu_code/relax/python/tvm/meta_schedule/tune_context.py", line 149, in __init__
    _ffi_api.TuneContextInitialize(self)  # type: ignore # pylint: disable=no-member
  File "/mnt/e/ubuntu_code/relax/python/tvm/_ffi/_ctypes/packed_func.py", line 238, in __call__
    raise get_last_ffi_error()
tvm._ffi.base.TVMError: Traceback (most recent call last):
  5: TVMFuncCall
  4: tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<void (tvm::meta_schedule::TuneContext)>::AssignTypedLambda<tvm::runtime::Registry::set_body_method<tvm::meta_schedule::TuneContext, tvm::meta_schedule::TuneContextNode, void, , void>(void (tvm::meta_schedule::TuneContextNode::*)())::{lambda(tvm::meta_schedule::TuneContext)#1}>(tvm::runtime::Registry::set_body_method<tvm::meta_schedule::TuneContext, tvm::meta_schedule::TuneContextNode, void, , void>(void (tvm::meta_schedule::TuneContextNode::*)())::{lambda(tvm::meta_schedule::TuneContext)#1}, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >)::{lambda(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)#1}> >::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*)
  3: tvm::meta_schedule::TuneContextNode::Initialize()
  2: tvm::meta_schedule::PostOrderApplyNode::InitializeWithTuneContext(tvm::meta_schedule::TuneContext const&)
  1: tvm::meta_schedule::SpaceGeneratorNode::InitializeWithTuneContext(tvm::meta_schedule::TuneContext const&)
  0: tvm::meta_schedule::GetRuleKindFromTarget(tvm::Target const&)
  File "/mnt/e/ubuntu_code/relax/src/meta_schedule/space_generator/space_generator.cc", line 82
TVMError: Unsupported target: opencl -keys=opencl,gpu -max_num_threads=256 -max_shared_memory_per_block=16384 -max_threads_per_block=256 -texture_spatial_limit=16384 -thread_warp_size=1

I checked the file “https://github.com/mlc-ai/relax/blob/mlc/src/meta_schedule/space_generator/space_generator.cc” Seems relax auto tune does not support OpenCL

Anyone knows how to tune opencl with relax branch? thanks

#2

Can you try adding "opencl" to this line?

#5

Thanks for your reply. I modify as you said. I want to tune opencl on my android mobile phone via RPC. my code is below

rpc_host = "127.0.0.1"
rpc_port = 9190
rpc_key = "android"

my_rpc_config = ms.runner.RPCConfig(
            tracker_host=rpc_host,
            tracker_port=rpc_port,
            tracker_key=rpc_key,
            session_timeout_sec=180,
        )
my_workers = my_rpc_config.count_num_servers(allow_missing=False)

def get_runner():
    runner_config = {
        "evaluator_config": ms.runner.EvaluatorConfig(
            number=3,
            repeat=1,
            min_repeat_ms=100,
            enable_cpu_cache_flush=False,
        ),
        "alloc_repeat": 5,
    }
    runner = ms.runner.RPCRunner(
        rpc_config=my_rpc_config, max_workers=my_workers, **runner_config
    )

    return runner

database = ms.tune_tir(
    mod=MyModule,
    target="opencl",
    max_trials_global=1280,
    num_trials_per_iter=64,
    work_dir="./tune_tmp",
    runner=get_runner(),
)
print(type(database))
sch = ms.tir_integration.compile_tir(database, MyModule, "opencl")

but got another error as below

2023-06-06 08:32:58 [INFO] [task_scheduler.cc:121] [Task #0: main] Trial #1: Error in running:
RPCRunner: An exception occurred
Traceback (most recent call last):
  File "/mnt/e/ubuntu_code/relax/python/tvm/exec/popen_worker.py", line 87, in main
    result = fn(*args, **kwargs)
  File "/mnt/e/ubuntu_code/relax/python/tvm/meta_schedule/runner/rpc_runner.py", line 392, in _worker_func
    rt_mod: Module = f_upload_module(session, local_path, remote_path)
  File "/mnt/e/ubuntu_code/relax/python/tvm/meta_schedule/runner/rpc_runner.py", line 451, in default_upload_module
    rt_mod: Module = session.load_module(remote_path)
  File "/mnt/e/ubuntu_code/relax/python/tvm/rpc/client.py", line 161, in load_module
    return _ffi_api.LoadRemoteModule(self._sess, path)
  File "/mnt/e/ubuntu_code/relax/python/tvm/_ffi/_ctypes/packed_func.py", line 238, in __call__
    raise get_last_ffi_error()
tvm.error.RPCError: Traceback (most recent call last):
  10: TVMFuncCall
  9: _ZN3tvm7runtime13PackedFun
  8: tvm::runtime::TypedPackedFunc<tvm::runtime::Module (tvm::runtime::Module, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >)>::AssignTypedLambda<tvm::runtime::__mk_TVM4::{lambda(tvm::runtime::Module, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >)#1}>(tvm::runtime::__mk_TVM4::{lambda(tvm::runtime::Module, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >)#1}, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >)::{lambda(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)#1}::operator()(tvm::runtime::TVMArgs const, tvm::runtime::TVMRetValue) const
  7: tvm::runtime::RPCWrappedFunc::operator()(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) const
  6: tvm::runtime::RPCClientSession::CallFunc(void*, TVMValue const*, int const*, int, std::function<void (tvm::runtime::TVMArgs)> const&)
  5: tvm::runtime::RPCEndpoint::CallFunc(void*, TVMValue const*, int const*, int, std::function<void (tvm::runtime::TVMArgs)>)
  4: tvm::runtime::RPCEndpoint::HandleUntilReturnEvent(bool, std::function<void (tvm::runtime::TVMArgs)>)
  3: tvm::runtime::RPCEndpoint::EventHandler::HandleNextEvent(bool, bool, std::function<void (tvm::runtime::TVMArgs)>)
  2: tvm::runtime::RPCEndpoint::EventHandler::HandleProcessPacket(std::function<void (tvm::runtime::TVMArgs)>)
  1: tvm::runtime::RPCEndpoint::EventHandler::HandleReturn(tvm::runtime::RPCCode, std::function<void (tvm::runtime::TVMArgs)>)
  0: _ZN3tvm7runtime6detail8LogFatalD2Ev.
  File "/mnt/e/ubuntu_code/relax/src/runtime/rpc/rpc_endpoint.cc", line 376
RPCError: Error caught from RPC call:
[16:32:46] /mnt/e/ubuntu_code/relax/apps/cpp_rpc/rpc_env.cc:247: sh: g++: inaccessible or not found

Do you have any idea about this error ? Thanks

#6

先试试CUDA呢，毕竟是主流。relax还在开发中，肯定先支持cuda。

#7

主要是给手机端用的，android手机只有opencl，没有cuda

#8

Hello, have the Android tuning issues been resolved? I am meeting the same problem