Cookiee235 opened a new issue, #17934:
URL: https://github.com/apache/tvm/issues/17934
### Actual behavior
```
2025-05-09 18:24:12 [INFO] Logging directory: ./tune_tmp/logs
2025-05-09 18:24:15 [INFO] LocalBuilder: max_workers = 32
2025-05-09 18:24:16 [INFO] LocalRunner: max_workers = 1
2025-05-09 18:24:16 [INFO] [task_scheduler.cc:159] Initializing Task #0:
"main"
2025-05-09 18:24:18 [INFO] [task_scheduler.cc:320]
ID | Name | FLOP | Weight | Speed (GFLOPS) | Latency (us) | Weighted
Latency (us) | Trials | Done
-----------------------------------------------------------------------------------------------------
0 | main | 434176 | 1 | N/A | N/A |
N/A | 0 |
-----------------------------------------------------------------------------------------------------
Total trials: 0
Total latency (us): 0
2025-05-09 18:24:18 [INFO] [task_scheduler.cc:180] TaskScheduler picks Task
#0: "main"
Traceback (most recent call last):
File
"/data/qshenaf/remote_pc/TirFuzz/bugs/05-03_20-50/topi.nn.pool_grad_0.py", line
11, in <module>
database = ms.tir_integration.tune_tir(mod=sch.mod, target='llvm
--num-cores=16', work_dir='./tune_tmp', max_trials_global=1,
num_trials_per_iter=1)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/data/qshenaf/envs/tvm/python/tvm/meta_schedule/tir_integration.py",
line 146, in tune_tir
return tune_tasks(
^^^^^^^^^^^
File "/data/qshenaf/envs/tvm/python/tvm/meta_schedule/tune.py", line 122,
in tune_tasks
task_scheduler.tune(
File
"/data/qshenaf/envs/tvm/python/tvm/meta_schedule/task_scheduler/task_scheduler.py",
line 132, in tune
_ffi_api.TaskSchedulerTune( # type: ignore # pylint: disable=no-member
File "tvm/_ffi/_cython/./packed_func.pxi", line 339, in
tvm._ffi._cy3.core.PackedFuncBase.__call__
File "tvm/_ffi/_cython/./packed_func.pxi", line 284, in
tvm._ffi._cy3.core.FuncCall
File "tvm/_ffi/_cython/./base.pxi", line 185, in
tvm._ffi._cy3.core.CHECK_CALL
File "/data/qshenaf/envs/tvm/python/tvm/_ffi/base.py", line 468, in
raise_last_ffi_error
raise py_err
File
"/data/qshenaf/envs/tvm/src/meta_schedule/task_scheduler/gradient_based.cc",
line 54, in
tvm::meta_schedule::GradientBasedNode::Tune(tvm::runtime::Array<tvm::meta_schedule::TuneContext,
void>, tvm::runtime::Array<tvm::FloatImm, void>, int, int, int,
tvm::meta_schedule::Builder, tvm::meta_schedule::Runner,
tvm::runtime::Array<tvm::meta_schedule::MeasureCallback, void>,
tvm::runtime::Optional<tvm::meta_schedule::Database>,
tvm::runtime::Optional<tvm::meta_schedule::CostModel>)
TaskSchedulerNode::Tune(tasks, task_weights, max_trials_global,
max_trials_per_task,
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/data/qshenaf/envs/tvm/src/meta_schedule/task_scheduler/task_scheduler.cc",
line 190, in
tvm::meta_schedule::TaskSchedulerNode::Tune(tvm::runtime::Array<tvm::meta_schedule::TuneContext,
void>, tvm::runtime::Array<tvm::FloatImm, void>, int, int, int,
tvm::meta_schedule::Builder, tvm::meta_schedule::Runner,
tvm::runtime::Array<tvm::meta_schedule::MeasureCallback, void>,
tvm::runtime::Optional<tvm::meta_schedule::Database>,
tvm::runtime::Optional<tvm::meta_schedule::CostModel>)
task->ctx->search_strategy.value()->GenerateMeasureCandidates()) {
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/data/qshenaf/envs/tvm/src/meta_schedule/search_strategy/evolutionary_search.cc",
line 447, in
tvm::meta_schedule::EvolutionarySearchNode::GenerateMeasureCandidates()
return this->state_->GenerateMeasureCandidates();
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/data/qshenaf/envs/tvm/src/meta_schedule/search_strategy/evolutionary_search.cc",
line 717, in
tvm::meta_schedule::EvolutionarySearchNode::State::GenerateMeasureCandidates()
std::vector<Schedule> unmeasured = SampleInitPopulation(pop -
measured.size());
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/data/qshenaf/envs/tvm/src/meta_schedule/search_strategy/evolutionary_search.cc",
line 524, in
tvm::meta_schedule::EvolutionarySearchNode::State::SampleInitPopulation(int)
support::parallel_for_dynamic(0, num, self->ctx_->num_threads,
f_proc_unmeasured);
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/data/qshenaf/envs/tvm/src/support/parallel_for.cc", line 128, in
tvm::support::parallel_for_dynamic(int, int, int, std::function<void (int,
int)> const&)
LOG(FATAL) << "RuntimeError: parallel_for_dynamic error with " <<
e.what();
^^^^^^^^^^^^^^^^^^^^^^^^^^^
tvm._ffi.base.TVMError: Traceback (most recent call last):
5:
tvm::meta_schedule::GradientBasedNode::Tune(tvm::runtime::Array<tvm::meta_schedule::TuneContext,
void>, tvm::runtime::Array<tvm::FloatImm, void>, int, int, int,
tvm::meta_schedule::Builder, tvm::meta_schedule::Runner,
tvm::runtime::Array<tvm::meta_schedule::MeasureCallback, void>,
tvm::runtime::Optional<tvm::meta_schedule::Database>,
tvm::runtime::Optional<tvm::meta_schedule::CostModel>)
at
/data/qshenaf/envs/tvm/src/meta_schedule/task_scheduler/gradient_based.cc:54
4:
tvm::meta_schedule::TaskSchedulerNode::Tune(tvm::runtime::Array<tvm::meta_schedule::TuneContext,
void>, tvm::runtime::Array<tvm::FloatImm, void>, int, int, int,
tvm::meta_schedule::Builder, tvm::meta_schedule::Runner,
tvm::runtime::Array<tvm::meta_schedule::MeasureCallback, void>,
tvm::runtime::Optional<tvm::meta_schedule::Database>,
tvm::runtime::Optional<tvm::meta_schedule::CostModel>)
at
/data/qshenaf/envs/tvm/src/meta_schedule/task_scheduler/task_scheduler.cc:190
3: tvm::meta_schedule::EvolutionarySearchNode::GenerateMeasureCandidates()
at
/data/qshenaf/envs/tvm/src/meta_schedule/search_strategy/evolutionary_search.cc:447
2:
tvm::meta_schedule::EvolutionarySearchNode::State::GenerateMeasureCandidates()
at
/data/qshenaf/envs/tvm/src/meta_schedule/search_strategy/evolutionary_search.cc:717
1:
tvm::meta_schedule::EvolutionarySearchNode::State::SampleInitPopulation(int)
at
/data/qshenaf/envs/tvm/src/meta_schedule/search_strategy/evolutionary_search.cc:524
0: tvm::support::parallel_for_dynamic(int, int, int, std::function<void
(int, int)> const&)
at /data/qshenaf/envs/tvm/src/support/parallel_for.cc:128
File "/data/qshenaf/envs/tvm/src/support/parallel_for.cc", line 128
RuntimeError: parallel_for_dynamic error with ScheduleError: (not rendered)
```
### Environment
tvm-0.21.dev0'
### Steps to reproduce
```
import tvm
from tvm import te, topi, tir
from tvm import meta_schedule as ms
grads = te.placeholder((1, 16, 32, 32), dtype='float32', name='grads')
data = te.placeholder((1, 16, 32, 32), dtype='float32', name='data')
op_config = {'grads': grads, 'data': data, 'kernel': [3, 3], 'stride': [2,
2], 'padding': [1, 1, 1, 1], 'pool_type': 'max', 'ceil_mode': False,
'count_include_pad': False, 'layout': 'NCHW', }
op_output = topi.nn.pool_grad(**op_config)
sch = tir.Schedule(te.create_prim_func([grads, data,
op_output]).with_attr('target', tvm.target.Target('llvm')))
database = ms.tir_integration.tune_tir(mod=sch.mod, target='llvm
--num-cores=16', work_dir='./tune_tmp', max_trials_global=1,
num_trials_per_iter=1)
sch = ms.tir_integration.compile_tir(database, sch.mod, 'llvm
--num-cores=16')
```
### Triage
* needs-triage
* tune:meta_schedule
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
