jikechao opened a new issue, #14615:
URL: https://github.com/apache/tvm/issues/14615
The ONNX model can be imported into Relay well but crashed when compiled. It
throws the following crash messages:
```
Traceback (most recent call last):
....
irmod, params = relay.frontend.from_onnx(model, {'x': (1, 1, 5, 5)},
freeze_params=True)
File "/workplace/software/tvm/tvm/python/tvm/relay/frontend/onnx.py", line
7346, in from_onnx
mod, params = g.from_onnx(graph, opset)
File "/workplace/software/tvm/tvm/python/tvm/relay/frontend/onnx.py", line
6963, in from_onnx
self._construct_nodes(graph)
File "/workplace/software/tvm/tvm/python/tvm/relay/frontend/onnx.py", line
7120, in _construct_nodes
len(node_output), outputs_num, op_name
AssertionError: Number of output mismatch 2 vs 1 in MaxPool.
(tf2) root@R730-3:/share_host/TVMFT/BorrowTests/ONNX/bugs# python
6_sorted.py
Traceback (most recent call last):
File "6_sorted.py", line 11, in <module>
graph, lib, params = relay.build_module.build(irmod, target='llvm
-mcpu=core-avx2', params=params)
File "/workplace/software/tvm/tvm/python/tvm/relay/build_module.py", line
372, in build
mod_name=mod_name,
File "/workplace/software/tvm/tvm/python/tvm/relay/build_module.py", line
169, in build
mod_name,
File "/workplace/software/tvm/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):
25: TVMFuncCall
24:
tvm::relay::backend::RelayBuildModule::GetFunction(std::__cxx11::basic_string<char,
std::char_traits<char>, std::allocator<char> > const&,
tvm::runtime::ObjectPtr<tvm::runtime::Object>
const&)::{lambda(tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*)#3}::operator()(tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*) const
23: tvm::relay::backend::RelayBuildModule::Build(tvm::IRModule,
tvm::runtime::Array<tvm::Target, void> const&, tvm::Target const&,
tvm::relay::Executor const&, tvm::relay::Runtime const&,
tvm::WorkspaceMemoryPools const&, tvm::ConstantMemoryPools const&,
tvm::runtime::String)
22: tvm::relay::backend::RelayBuildModule::BuildRelay(tvm::IRModule,
tvm::runtime::String const&)
21: tvm::relay::backend::ExecutorCodegen::Codegen(tvm::IRModule,
tvm::relay::Function const&, tvm::runtime::String)
20: void tvm::relay::backend::ExecutorCodegen::CallFunc<tvm::IRModule,
tvm::relay::Function, tvm::runtime::String>(std::__cxx11::basic_string<char,
std::char_traits<char>, std::allocator<char> > const&, tvm::IRModule,
tvm::relay::Function, tvm::runtime::String)
19:
tvm::relay::backend::GraphExecutorCodegenModule::GetFunction(std::__cxx11::basic_string<char,
std::char_traits<char>, std::allocator<char> > const&,
tvm::runtime::ObjectPtr<tvm::runtime::Object>
const&)::{lambda(tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*)#2}::operator()(tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*) const
18: tvm::relay::backend::GraphExecutorCodegen::Codegen(tvm::IRModule,
tvm::relay::Function, tvm::runtime::String)
17: tvm::relay::GraphPlanMemory(tvm::relay::Function const&)
16: tvm::relay::StorageAllocator::Plan(tvm::relay::Function const&)
15: tvm::relay::ExprVisitor::VisitExpr(tvm::RelayExpr const&)
14:
tvm::relay::transform::DeviceAwareExprVisitor::VisitExpr_(tvm::relay::FunctionNode
const*)
13:
tvm::relay::StorageAllocaBaseVisitor::DeviceAwareVisitExpr_(tvm::relay::FunctionNode
const*)
12: tvm::relay::StorageAllocaBaseVisitor::GetToken(tvm::RelayExpr const&)
11: tvm::relay::ExprVisitor::VisitExpr(tvm::RelayExpr const&)
10: tvm::relay::StorageAllocaBaseVisitor::VisitExpr_(tvm::relay::TupleNode
const*)
9: tvm::relay::StorageAllocaBaseVisitor::GetToken(tvm::RelayExpr const&)
8: tvm::relay::ExprVisitor::VisitExpr(tvm::RelayExpr const&)
7:
tvm::relay::transform::DeviceAwareExprVisitor::VisitExpr_(tvm::relay::CallNode
const*)
6:
tvm::relay::StorageAllocator::DeviceAwareVisitExpr_(tvm::relay::CallNode const*)
5: tvm::relay::StorageAllocaBaseVisitor::CreateToken(tvm::RelayExprNode
const*, bool)
4: tvm::relay::StorageAllocator::CreateTokenOnDevice(tvm::RelayExprNode
const*, tvm::VirtualDevice const&, bool)
3:
tvm::relay::StorageAllocator::TokenAllocator::Request(tvm::relay::StorageToken*)
2: tvm::relay::TokenAllocator1D::Request(tvm::relay::StorageToken*)
1: tvm::relay::TokenAllocator1D::GetMemorySize(tvm::relay::StorageToken*)
0: _ZN3tvm7runtime6detail
File "/workplace/software/tvm/tvm/src/relay/backend/token_allocator.cc",
line 41
TVMError:
---------------------------------------------------------------
An error occurred during the execution of TVM.
For more information, please see: https://tvm.apache.org/docs/errors.html
---------------------------------------------------------------
Check failed: (pval != nullptr) is false: Cannot allocate memory symbolic
tensor shape [T.Any()]
```
Although the shape is `T.Any()`, it's a static graph rather than. Thus this
crash is a bug, we should support the T.any() correctly.
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