An ONNX model containing the following cov2d operator will crash in relay.frontend.from_onnx().
As a contract, an equivalent Keras model including the below Conv2D can run well.
Convolution2D(32, 5, 5, border_mode='valid', input_shape=(60, 200, 1), name='conv1')
The Traceback at from_onnx() is following:
Traceback
File "test_onnx_model.py", line 83, in <module>
relay_mod_onnx, params = relay.frontend.from_onnx(onnx_model, shape_dict)
File "/softwares/tvm/python/tvm/relay/frontend/onnx.py", line 7188, in from_onnx
mod, params = g.from_onnx(graph, opset)
File "/softwares/tvm/python/tvm/relay/frontend/onnx.py", line 6805, in from_onnx
self._construct_nodes(graph)
File "/softwares/tvm/python/tvm/relay/frontend/onnx.py", line 6920, in _construct_nodes
op = self._convert_operator(op_name, inputs, attr, self.opset)
File "/softwares/tvm/python/tvm/relay/frontend/onnx.py", line 7046, in _convert_operator
sym = convert_map[op_name](inputs, attrs, self._params)
File "/softwares/tvm/python/tvm/relay/frontend/onnx.py", line 812, in _impl_v1
input_shape = infer_shape(data)
File "/softwares/tvm/python/tvm/relay/frontend/common.py", line 530, in infer_shape
out_type = infer_type(inputs, mod=mod)
File "/softwares/tvm/python/tvm/relay/frontend/common.py", line 505, in infer_type
new_mod = _transform.InferType()(new_mod)
File "/softwares/tvm/python/tvm/ir/transform.py", line 161, in __call__
return _ffi_transform_api.RunPass(self, mod)
File "/softwares/tvm/python/tvm/_ffi/_ctypes/packed_func.py", line 237, in __call__
raise get_last_ffi_error()
tvm._ffi.base.TVMError: Traceback (most recent call last):
7: TVMFuncCall
6: tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::IRModule (tvm::transform::Pass, tvm::IRModule)>::AssignTypedLambda<tvm::transform::{lambda(tvm::transform::Pass, tvm::IRModule)#7}>(tvm::transform::{lambda(tvm::transform::Pass, tvm::IRModule)#7}, 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*)
5: tvm::transform::Pass::operator()(tvm::IRModule) const
4: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
3: tvm::transform::ModulePassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
2: tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::IRModule (tvm::IRModule, tvm::transform::PassContext)>::AssignTypedLambda<tvm::relay::transform::InferType()::{lambda(tvm::IRModule, tvm::transform::PassContext const&)#1}>(tvm::relay::transform::InferType()::{lambda(tvm::IRModule, tvm::transform::PassContext const&)#1})::{lambda(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)#1}> >::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*)
1: tvm::relay::TypeInferencer::Infer(tvm::GlobalVar, tvm::relay::Function)
0: tvm::relay::TypeSolver::Solve()
10: TVMFuncCall
9: tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::IRModule (tvm::transform::Pass, tvm::IRModule)>::AssignTypedLambda<tvm::transform::{lambda(tvm::transform::Pass, tvm::IRModule)#7}>(tvm::transform::{lambda(tvm::transform::Pass, tvm::IRModule)#7}, 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*)
8: tvm::transform::Pass::operator()(tvm::IRModule) const
7: tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
6: tvm::transform::ModulePassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const
5: tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::IRModule (tvm::IRModule, tvm::transform::PassContext)>::AssignTypedLambda<tvm::relay::transform::InferType()::{lambda(tvm::IRModule, tvm::transform::PassContext const&)#1}>(tvm::relay::transform::InferType()::{lambda(tvm::IRModule, tvm::transform::PassContext const&)#1})::{lambda(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)#1}> >::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*)
4: tvm::relay::TypeInferencer::Infer(tvm::GlobalVar, tvm::relay::Function)
3: tvm::relay::TypeSolver::Solve()
2: _ZN3tvm7runtime13PackedFun
1: tvm::runtime::TypedPackedFunc<bool (tvm::runtime::Array<tvm::Type, void> const&, int, tvm::Attrs const&, tvm::TypeReporter const&)>::AssignTypedLambda<bool (*)(tvm::runtime::Array<tvm::Type, void> const&, int, tvm::Attrs const&, tvm::TypeReporter const&)>(bool (*)(tvm::runtime::Array<tvm::Type, void> const&, int, tvm::Attrs const&, tvm::TypeReporter const&))::{lambda(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)#1}::operator()(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*) const
0: tvm::relay::TransposeRel(tvm::runtime::Array<tvm::Type, void> const&, int, tvm::Attrs const&, tvm::TypeReporter const&)
File "/softwares/tvm/src/relay/analysis/type_solver.cc", line 624
TVMError:
---------------------------------------------------------------
An error occurred during the execution of TVM.
For more information, please see: https://tvm.apache.org/docs/errors.html
---------------------------------------------------------------
Check failed: (false) is false: [17:17:39] /softwares/tvm/src/relay/op/tensor/transform.cc:462:
---------------------------------------------------------------
An error occurred during the execution of TVM.
For more information, please see: https://tvm.apache.org/docs/errors.html
---------------------------------------------------------------
Check failed: (!axes.defined() || static_cast<int>(axes.size()) == ndim) is false: Dimension mismatch: axes has 4 elements, but data.ndim = 3