when tuing model for mali G76 GPU following：
https://tvm.apache.org/docs/how_to/tune_with_autoscheduler/tune_network_mali.html?highlight=opencl
Get an error:
xgboost.core.XGBoostError: [14:40:16] …/src/data/data.cc:367: Check failed: valid: Label contains NaN, infinity or a value too large.
May you can check the label in your data.
Thanks for your answer， but there is no label data. I just tuning a resnet18 model following this guide:
https://tvm.apache.org/docs/how_to/tune_with_autoscheduler/tune_network_mali.html?highlight=mali
and this error will raise.
I just change another mali gpu. So could you give more guidance about that.
the whole traceback message:
[ERROR] 2023-06-10 10:40:52 : tunning failed: Traceback (most recent call last): 4: TVMFuncCall 3: tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::runtime::Array<tvm::runtime::ObjectRef, void> (tvm::auto_scheduler::SearchPolicy, int, tvm::auto_scheduler::ProgramMeasurer)>::AssignTypedLambda<tvm::auto_scheduler::{lambda(tvm::auto_scheduler::SearchPolicy, int, tvm::auto_scheduler::ProgramMeasurer)#2}>(tvm::auto_scheduler::{lambda(tvm::auto_scheduler::SearchPolicy, int, tvm::auto_scheduler::ProgramMeasurer)#2}, std::__cxx11::basic_string<char, std::char_traits, std::allocator >)::{lambda(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)#1}> >::Call(tvm::runtime::PackedFuncObj const*, std::__cxx11::basic_string<char, std::char_traits, std::allocator >, tvm::runtime::TVMRetValue) 2: tvm::auto_scheduler::SketchPolicyNode::ContinueSearchOneRound(int, tvm::auto_scheduler::ProgramMeasurer) 1: tvm::auto_scheduler::PythonBasedModelNode::Update(tvm::runtime::Array<tvm::auto_scheduler::MeasureInput, void> const&, tvm::runtime::Array<tvm::auto_scheduler::MeasureResult, void> const&) 0: tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<TVMFuncCreateFromCFunc::{lambda(tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*)#2}> >::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*) [clone .cold] File “/data/users/lcy/ref/tvm/python/tvm/_ffi/_ctypes/packed_func.py”, line 81, in cfun rv = local_pyfunc(*pyargs) File “/data/users/lcy/ref/tvm/python/tvm/auto_scheduler/cost_model/cost_model.py”, line 93, in update_func self.update(inputs, results) File “/data/users/lcy/ref/tvm/python/tvm/auto_scheduler/cost_model/xgb_model.py”, line 199, in update dtrain = pack_sum_xgbmatrix( File “/data/users/lcy/ref/tvm/python/tvm/auto_scheduler/cost_model/xgb_model.py”, line 427, in pack_sum_xgbmatrix ret = xgb.DMatrix(np.array(x_flatten), y_flatten) File “/data/users/lcy/conda/envs/tvm/lib/python3.8/site-packages/xgboost/core.py”, line 620, in inner_f return func(**kwargs) File “/data/users/lcy/conda/envs/tvm/lib/python3.8/site-packages/xgboost/core.py”, line 754, in init self.set_info( File “/data/users/lcy/conda/envs/tvm/lib/python3.8/site-packages/xgboost/core.py”, line 620, in inner_f return func(**kwargs) File “/data/users/lcy/conda/envs/tvm/lib/python3.8/site-packages/xgboost/core.py”, line 819, in set_info self.set_label(label) File “/data/users/lcy/conda/envs/tvm/lib/python3.8/site-packages/xgboost/core.py”, line 950, in set_label dispatch_meta_backend(self, label, ‘label’, ‘float’) File “/data/users/lcy/conda/envs/tvm/lib/python3.8/site-packages/xgboost/data.py”, line 1121, in dispatch_meta_backend _meta_from_list(data, name, dtype, handle) File “/data/users/lcy/conda/envs/tvm/lib/python3.8/site-packages/xgboost/data.py”, line 1060, in _meta_from_list _meta_from_numpy(data_np, field, dtype, handle) File “/data/users/lcy/conda/envs/tvm/lib/python3.8/site-packages/xgboost/data.py”, line 1050, in _meta_from_numpy _check_call(_LIB.XGDMatrixSetInfoFromInterface(handle, c_str(field), interface_str)) File “/data/users/lcy/conda/envs/tvm/lib/python3.8/site-packages/xgboost/core.py”, line 279, in _check_call raise XGBoostError(py_str(_LIB.XGBGetLastError())) [bt] (3) /data/users/lcy/conda/envs/tvm/lib/python3.8/site-packages/xgboost/lib/libxgboost.so(XGDMatrixSetInfoFromInterface+0xad) [0x7f1c05158f3d] [bt] (2) /data/users/lcy/conda/envs/tvm/lib/python3.8/site-packages/xgboost/lib/libxgboost.so(+0x2196b0) [0x7f1c052376b0] [bt] (1) /data/users/lcy/conda/envs/tvm/lib/python3.8/site-packages/xgboost/lib/libxgboost.so(+0x218175) [0x7f1c05236175] [bt] (0) /data/users/lcy/conda/envs/tvm/lib/python3.8/site-packages/xgboost/lib/libxgboost.so(+0x20b233) [0x7f1c05229233] xgboost.core.XGBoostError: [10:40:52] …/src/data/data.cc:461: Check failed: valid: Label contains NaN, infinity or a value too large.