jikechao opened a new issue, #15174:
URL: https://github.com/apache/tvm/issues/15174
For the input:
```
keras.layers.Concatenate(axis=2)
input_shape1 =[1, 1, 4, 5]
input_shape2 = [1, 1, 8, 5]
```
The two input tensors have the same shape in non-concatenating axes(i.e.,
axis=2).
However, TVM threw an unexpected exception:
```
Traceback (most recent call last):
8: TVMFuncCall
7:
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::IRModule
(tvm::transform::Pass,
tvm::IRModule)>::AssignTypedLambda<tvm::transform::$_6>(tvm::transform::$_6,
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*)
6: tvm::transform::Pass::operator()(tvm::IRModule) const
5: tvm::transform::Pass::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
4: tvm::transform::ModulePassNode::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
3:
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::IRModule
(tvm::IRModule,
tvm::transform::PassContext)>::AssignTypedLambda<tvm::relay::transform::InferType()::$_2>(tvm::relay::transform::InferType()::$_2)::{lambda(tvm::runtime::TVMArgs
const&, tvm::runtime::TVMRetValue*)#1}> >::Call(tvm::runtime::PackedFuncObj
const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*)
2: tvm::relay::TypeInferencer::Infer(tvm::GlobalVar, tvm::relay::Function)
1: tvm::relay::TypeSolver::Solve()
0: _ZN3tvm7runtime6detail
File "/workplace/software/tvm/tvm/src/relay/analysis/type_solver.cc", line
643
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: relay.concatenate requires all tensors
have the same shape on non-concatenating axes
``
### Triage
* relay:analysis
* needs-triage
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