wzh99 commented on issue #11684:
URL: https://github.com/apache/tvm/issues/11684#issuecomment-1153146244
@lileidev Thanks for your participation in this issue. This test case is
invalid, so an error is actually expected. However, the type inference in Relay
does not report any error. This is somehow different from common bug issues,
where we typically expect no errors.
To actually reproduce an error, you can try the following code:
```python
from tvm import relay, transform, IRModule
x = relay.var('x', shape=(4,))
y = relay.nn.softmax(x, axis=1)
mod = IRModule.from_expr(y)
mod = relay.transform.InferType()(mod)
with transform.PassContext(opt_level=0):
lib = relay.build(mod, target='llvm')
```
And you may see the following error report:
```
Traceback (most recent call last):
File "/Users/wzh/tvm-bug/bug_softmax_axis.py", line 10, in <module>
lib = relay.build(mod, target='llvm')
File "/Users/wzh/tvm-dev/python/tvm/relay/build_module.py", line 416, in
build
graph_json, runtime_mod, params = bld_mod.build(
File "/Users/wzh/tvm-dev/python/tvm/relay/build_module.py", line 154, in
build
self._build(mod, raw_targets, executor, runtime, workspace_memory_pools,
mod_name)
File "/Users/wzh/tvm-dev/python/tvm/_ffi/_ctypes/packed_func.py", line
237, in __call__
raise get_last_ffi_error()
IndexError: Traceback (most recent call last):
[bt] (8) 9 libtvm.dylib 0x000000011443e8fa
tvm::relay::tec::ScheduleBuilder::Create(tvm::relay::Function const&,
std::__1::function<std::__1::basic_string<char, std::__1::char_traits<char>,
std::__1::allocator<char> > (std::__1::basic_string<char,
std::__1::char_traits<char>, std::__1::allocator<char> >)>) + 218
[bt] (7) 8 libtvm.dylib 0x0000000114445ae3
tvm::relay::tec::LowerToTECompute::Lower(tvm::relay::Function const&,
std::__1::function<std::__1::basic_string<char, std::__1::char_traits<char>,
std::__1::allocator<char> > (std::__1::basic_string<char,
std::__1::char_traits<char>, std::__1::allocator<char> >)>) + 1123
[bt] (6) 7 libtvm.dylib 0x000000011444bef2
tvm::relay::backend::MemoizedExprTranslator<tvm::runtime::Array<tvm::te::Tensor,
void> >::VisitExpr(tvm::RelayExpr const&) + 226
[bt] (5) 6 libtvm.dylib 0x000000011444c08e
tvm::relay::ExprFunctor<tvm::runtime::Array<tvm::te::Tensor, void>
(tvm::RelayExpr const&)>::VisitExpr(tvm::RelayExpr const&) + 222
[bt] (4) 5 libtvm.dylib 0x000000011444c3a8
tvm::NodeFunctor<tvm::runtime::Array<tvm::te::Tensor, void>
(tvm::runtime::ObjectRef const&,
tvm::relay::ExprFunctor<tvm::runtime::Array<tvm::te::Tensor, void>
(tvm::RelayExpr const&)>*)>::operator()(tvm::runtime::ObjectRef const&,
tvm::relay::ExprFunctor<tvm::runtime::Array<tvm::te::Tensor, void>
(tvm::RelayExpr const&)>*) const + 312
[bt] (3) 4 libtvm.dylib 0x000000011444df88
tvm::relay::ExprFunctor<tvm::runtime::Array<tvm::te::Tensor, void>
(tvm::RelayExpr const&)>::InitVTable()::'lambda4'(tvm::runtime::ObjectRef
const&, tvm::relay::ExprFunctor<tvm::runtime::Array<tvm::te::Tensor, void>
(tvm::RelayExpr const&)>*)::__invoke(tvm::runtime::ObjectRef const&,
tvm::relay::ExprFunctor<tvm::runtime::Array<tvm::te::Tensor, void>
(tvm::RelayExpr const&)>*) + 24
[bt] (2) 3 libtvm.dylib 0x0000000114451d98
tvm::relay::tec::LowerToTECompute::VisitExpr_(tvm::relay::CallNode const*) +
2232
[bt] (1) 2 libtvm.dylib 0x00000001146e5cfd
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<TVMFuncCreateFromCFunc::$_2>
>::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*) + 109
[bt] (0) 1 libtvm.dylib 0x0000000114700518
tvm::runtime::Backtrace() + 24
File "/Users/wzh/tvm-dev/python/tvm/_ffi/_ctypes/packed_func.py", line 81,
in cfun
rv = local_pyfunc(*pyargs)
File "/Users/wzh/tvm-dev/python/tvm/relay/backend/te_compiler.py", line
313, in lower_call
best_impl, outputs = select_implementation(op, call.attrs, inputs,
ret_type, target)
File "/Users/wzh/tvm-dev/python/tvm/relay/backend/te_compiler.py", line
203, in select_implementation
outs = impl.compute(attrs, inputs, out_type)
File "/Users/wzh/tvm-dev/python/tvm/relay/op/op.py", line 126, in compute
return _OpImplementationCompute(self, attrs, inputs, out_type)
File "/Users/wzh/tvm-dev/python/tvm/_ffi/_ctypes/packed_func.py", line
237, in __call__
raise get_last_ffi_error()
[bt] (6) 7 ??? 0x00007ff7be438320 0x0 +
140702025745184
[bt] (5) 6 _ctypes.cpython-38-darwin.so 0x0000000101ce3fb7
ffi_call_unix64 + 79
[bt] (4) 5 libtvm.dylib 0x00000001146e343e
TVMFuncCall + 62
[bt] (3) 4 libtvm.dylib 0x0000000114518ebe
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::relay::$_3>
>::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*) + 190
[bt] (2) 3 libtvm.dylib 0x000000011451754a
tvm::relay::OpImplementation::Compute(tvm::Attrs const&,
tvm::runtime::Array<tvm::te::Tensor, void> const&, tvm::Type const&) + 202
[bt] (1) 2 libtvm.dylib 0x00000001146e5cfd
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<TVMFuncCreateFromCFunc::$_2>
>::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*) + 109
[bt] (0) 1 libtvm.dylib 0x0000000114700518
tvm::runtime::Backtrace() + 24
File "/Users/wzh/tvm-dev/python/tvm/_ffi/_ctypes/packed_func.py", line 81,
in cfun
rv = local_pyfunc(*pyargs)
File "/Users/wzh/tvm-dev/python/tvm/relay/op/strategy/generic.py", line
153, in _compute_softmax
return [topi_compute(inputs[0], axis)]
File "<decorator-gen-77>", line 2, in softmax
File "/Users/wzh/tvm-dev/python/tvm/te/tag.py", line 56, in tagged_fdecl
return func(*args, **kwargs)
File "/Users/wzh/tvm-dev/python/tvm/topi/nn/softmax.py", line 41, in
softmax
return softmax_common(x, axis, False)
File "/Users/wzh/tvm-dev/python/tvm/topi/nn/softmax.py", line 73, in
softmax_common
k1 = te.reduce_axis((0, shape[axis]), name="k")
File "/Users/wzh/tvm-dev/python/tvm/ir/container.py", line 36, in
__getitem__
return getitem_helper(self, _ffi_api.ArrayGetItem, len(self), idx)
File "/Users/wzh/tvm-dev/python/tvm/runtime/container.py", line 57, in
getitem_helper
raise IndexError("Index out of range. size: {}, got index
{}".format(length, idx))
IndexError: Index out of range. size: 1, got index 1
```
This cause of this error is the invalid `axis=1` in the call to
`nn.softmax`. However, this error message does not clearly tell that `axis` is
invalid. I think the invalid `axis` should be reported immediately in Relay
type inference, instead of elsewhere after it in the compilation process.
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