wzh99 opened a new issue, #11697:
URL: https://github.com/apache/tvm/issues/11697
### Expected behavior
The following Relay program should be successfully executed:
```
def @main(%x: Tensor[(1, 4), float32] /* ty=Tensor[(1, 4), float32] */, %b:
Tensor[(4), float32] /* ty=Tensor[(4), float32] */) -> Tensor[(1, 4), float32] {
%0 = nn.bias_add(%x, %b) /* ty=Tensor[(1, 4), float32] */;
squeeze(%0, axis=[]) /* ty=Tensor[(1, 4), float32] */
}
```
### Actual behavior
An error is reported during graph execution:
```
Traceback (most recent call last):
File "/Users/wzh/tvm-bug/bug_squeeze_axis.py", line 21, in <module>
gmod.run(x=x_input, b=b_input)
File "/Users/wzh/tvm-dev/python/tvm/contrib/graph_executor.py", line 208,
in run
self._run()
File "/Users/wzh/tvm-dev/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):
[bt] (7) 8 ??? 0x00007ff7bbc612f0 0x0 +
140701983970032
[bt] (6) 7 _ctypes.cpython-38-darwin.so 0x000000010458dfb7
ffi_call_unix64 + 79
[bt] (5) 6 libtvm.dylib 0x0000000116eea24e
TVMFuncCall + 62
[bt] (4) 5 libtvm.dylib 0x0000000116fbf2ca
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::GraphExecutor::GetFunction(std::__1::basic_string<char,
std::__1::char_traits<char>, std::__1::allocator<char> > const&,
tvm::runtime::ObjectPtr<tvm::runtime::Object> const&)::$_12>
>::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*) + 106
[bt] (3) 4 libtvm.dylib 0x0000000116fbd331
std::__1::__function::__func<tvm::runtime::GraphExecutor::CreateTVMOp(tvm::runtime::TVMOpParam
const&, std::__1::vector<DLTensor, std::__1::allocator<DLTensor> >
const&)::$_2,
std::__1::allocator<tvm::runtime::GraphExecutor::CreateTVMOp(tvm::runtime::TVMOpParam
const&, std::__1::vector<DLTensor, std::__1::allocator<DLTensor> >
const&)::$_2>, void ()>::operator()() + 81
[bt] (2) 3 libtvm.dylib 0x0000000116f0625d
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::WrapPackedFunc(int
(*)(TVMValue*, int*, int, TVMValue*, int*, void*),
tvm::runtime::ObjectPtr<tvm::runtime::Object> const&)::$_0>
>::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*) + 397
[bt] (1) 2 libtvm.dylib 0x00000001154f9fc9
tvm::runtime::detail::LogFatal::Entry::Finalize() + 89
[bt] (0) 1 libtvm.dylib 0x0000000116f07328
tvm::runtime::Backtrace() + 24
File "/Users/wzh/tvm-dev/src/runtime/library_module.cc", line 80
TVMError:
---------------------------------------------------------------
An error occurred during the execution of TVM.
For more information, please see: https://tvm.apache.org/docs/errors.html
---------------------------------------------------------------
Check failed: ret == 0 (-1 vs. 0) : Assert fail: (1 ==
tir.tvm_struct_get(arg.T_squeeze, 0, 4)), arg.T_squeeze.ndim is expected to
equal 1
```
### Environment
macOS 12.4. Compiled using Clang 13.1.6 with LLVM support. TVM commit
[`8341e33`](https://github.com/apache/tvm/commit/8341e33d05868b7bb8496c913679b7951836f3b9).
### Steps to reproduce
```python
import numpy as np
from tvm import relay, transform, cpu, IRModule
from tvm.contrib.graph_executor import GraphModule
x_shape = (1, 4)
b_shape = (4,)
x = relay.var('x', shape=x_shape)
b = relay.var('b', shape=b_shape)
y = relay.nn.bias_add(x, b)
y = relay.squeeze(y, axis=[])
mod = IRModule.from_expr(y)
with transform.PassContext(opt_level=1):
lib = relay.build(mod, target='llvm')
gmod = GraphModule(lib['default'](cpu()))
x_input = np.zeros(shape=x_shape, dtype='float32')
b_input = np.zeros(shape=b_shape, dtype='float32')
gmod.run(x=x_input, b=b_input)
```
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