Thrsu opened a new issue, #15393:
URL: https://github.com/apache/tvm/issues/15393
When the `beta` parameter of `torch.nn.Softplus` is set to 0, the TVMError:
"Check failed: fb->value != 0 (0 vs. 0) : Divide by zero" is raised.
### Expected behavior
TVM get the same output with the PyTorch output, PyTorch output is as below:
```
tensor([[inf, inf, inf, inf, inf, inf, inf],
[inf, inf, inf, inf, inf, inf, inf],
[inf, inf, inf, inf, inf, inf, inf],
[inf, inf, inf, inf, inf, inf, inf],
[inf, inf, inf, inf, inf, inf, inf],
[inf, inf, inf, inf, inf, inf, inf],
[inf, inf, inf, inf, inf, inf, inf],
[inf, inf, inf, inf, inf, inf, inf],
[inf, inf, inf, inf, inf, inf, inf],
[inf, inf, inf, inf, inf, inf, inf],
[inf, inf, inf, inf, inf, inf, inf],
[inf, inf, inf, inf, inf, inf, inf],
[inf, inf, inf, inf, inf, inf, inf],
[inf, inf, inf, inf, inf, inf, inf]], dtype=torch.float64)
```
### Actual behavior
```
Traceback (most recent call last):
File "1_repro.py", line 20, in <module>
exe = relay.create_executor('graph', mod=mod, params=params,
device=tvm.device('llvm', 0), target='llvm').evaluate()
File
"/workplace/software/tvm/tvm_/python/tvm/relay/backend/interpreter.py", line
171, in evaluate
return self._make_executor()
File "/workplace/software/tvm/tvm_/python/tvm/relay/build_module.py", line
519, in _make_executor
mod = build(self.mod, target=self.target)
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):
78: TVMFuncCall
77:
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
76: 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)
75: tvm::relay::backend::RelayBuildModule::BuildRelay(tvm::IRModule,
tvm::runtime::String const&)
74: tvm::relay::backend::ExecutorCodegen::Codegen(tvm::IRModule,
tvm::relay::Function const&, tvm::runtime::String)
73: 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)
72:
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
71: tvm::relay::backend::GraphExecutorCodegen::Codegen(tvm::IRModule,
tvm::relay::Function, tvm::runtime::String)
70: tvm::transform::Pass::operator()(tvm::IRModule) const
69: tvm::transform::Pass::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
68: tvm::transform::SequentialNode::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
67: tvm::transform::Pass::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
66: tvm::transform::ModulePassNode::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
65:
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::IRModule
(tvm::IRModule,
tvm::transform::PassContext)>::AssignTypedLambda<tvm::relay::tec::LowerTE(tvm::runtime::String,
tvm::CompilationConfig, std::function<void
(tvm::BaseFunc)>)::$_8>(tvm::relay::tec::LowerTE(tvm::runtime::String,
tvm::CompilationConfig, std::function<void
(tvm::BaseFunc)>)::$_8)::{lambda(tvm::runtime::TVMArgs const&,
tvm::runtime::TVMRetValue*)#1}> >::Call(tvm::runtime::PackedFuncObj const*,
tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*)
64: tvm::relay::tec::LowerTE(tvm::IRModule const&, tvm::runtime::String
const&, std::function<void (tvm::BaseFunc)>, tvm::CompilationConfig)
63: tvm::transform::Pass::operator()(tvm::IRModule) const
62: tvm::transform::Pass::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
61: tvm::relay::transform::FunctionPassNode::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
60:
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::relay::Function
(tvm::relay::Function, tvm::IRModule,
tvm::transform::PassContext)>::AssignTypedLambda<tvm::relay::tec::LowerTensorExpr(tvm::relay::tec::TECompiler,
std::function<void (tvm::BaseFunc)>,
tvm::CompilationConfig)::$_7>(tvm::relay::tec::LowerTensorExpr(tvm::relay::tec::TECompiler,
std::function<void (tvm::BaseFunc)>,
tvm::CompilationConfig)::$_7)::{lambda(tvm::runtime::TVMArgs const&,
tvm::runtime::TVMRetValue*)#1}> >::Call(tvm::runtime::PackedFuncObj const*,
tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*)
59: tvm::relay::ExprMutator::VisitExpr(tvm::RelayExpr const&)
58: tvm::relay::ExprFunctor<tvm::RelayExpr (tvm::RelayExpr
const&)>::VisitExpr(tvm::RelayExpr const&)
57: tvm::NodeFunctor<tvm::RelayExpr (tvm::runtime::ObjectRef const&,
tvm::relay::ExprFunctor<tvm::RelayExpr (tvm::RelayExpr
const&)>*)>::operator()(tvm::runtime::ObjectRef const&,
tvm::relay::ExprFunctor<tvm::RelayExpr (tvm::RelayExpr const&)>*) const
56: _ZZN3tvm5relay11ExprFunc
55:
tvm::relay::transform::DeviceAwareExprMutator::VisitExpr_(tvm::relay::FunctionNode
const*)
54:
tvm::relay::tec::LowerTensorExprMutator::DeviceAwareVisitExpr_(tvm::relay::FunctionNode
const*)
53: _ZN3tvm5relay9
52: tvm::relay::ExprMutator::VisitExpr_(tvm::relay::FunctionNode const*)
51: tvm::relay::ExprMutator::VisitExpr(tvm::RelayExpr const&)
50: tvm::relay::ExprFunctor<tvm::RelayExpr (tvm::RelayExpr
const&)>::VisitExpr(tvm::RelayExpr const&)
49: tvm::NodeFunctor<tvm::RelayExpr (tvm::runtime::ObjectRef const&,
tvm::relay::ExprFunctor<tvm::RelayExpr (tvm::RelayExpr
const&)>*)>::operator()(tvm::runtime::ObjectRef const&,
tvm::relay::ExprFunctor<tvm::RelayExpr (tvm::RelayExpr const&)>*) const
48: _ZZN3tvm5relay11ExprFunc
47:
tvm::relay::transform::DeviceAwareExprMutator::VisitExpr_(tvm::relay::CallNode
const*)
46:
tvm::relay::tec::LowerTensorExprMutator::DeviceAwareVisitExpr_(tvm::relay::CallNode
const*)
45: tvm::relay::tec::TECompilerImpl::Lower(tvm::relay::tec::CCacheKey
const&)
44:
tvm::relay::tec::TECompilerImpl::LowerInternal(tvm::relay::tec::CCacheKey
const&, tvm::GlobalVarSupply)
43: tvm::LowerSchedule(tvm::te::Schedule,
tvm::runtime::Array<tvm::te::Tensor, void> const&,
std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >
const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer,
std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>,
std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&,
tvm::GlobalVarSupply, bool)
42: tvm::LowerSchedule(tvm::te::Schedule,
tvm::runtime::Array<tvm::runtime::ObjectRef, void> const&,
std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >
const&, std::unordered_map<tvm::te::Tensor, tvm::tir::Buffer,
std::hash<tvm::te::Tensor>, std::equal_to<tvm::te::Tensor>,
std::allocator<std::pair<tvm::te::Tensor const, tvm::tir::Buffer> > > const&,
tvm::GlobalVarSupply, bool)
41: tvm::LowerWithPassList(tvm::IRModule,
tvm::runtime::Array<tvm::transform::Pass, void>)
40: tvm::transform::Pass::operator()(tvm::IRModule) const
39: tvm::transform::Pass::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
38: tvm::transform::SequentialNode::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
37: tvm::transform::Pass::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
36: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
35:
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc
(tvm::tir::PrimFunc, tvm::IRModule,
tvm::transform::PassContext)>::AssignTypedLambda<tvm::tir::transform::Simplify()::$_1>(tvm::tir::transform::Simplify()::$_1)::{lambda(tvm::runtime::TVMArgs
const&, tvm::runtime::TVMRetValue*)#1}> >::Call(tvm::runtime::PackedFuncObj
const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*)
34: tvm::arith::StmtSimplifier::Apply(tvm::tir::Stmt,
tvm::arith::Analyzer*, tvm::runtime::Optional<tvm::arith::SimplifyConfig>)
33: tvm::arith::StmtSimplifier::VisitStmt(tvm::tir::Stmt const&)
32: tvm::tir::StmtFunctor<tvm::tir::Stmt (tvm::tir::Stmt
const&)>::VisitStmt(tvm::tir::Stmt const&)
31: tvm::NodeFunctor<tvm::tir::Stmt (tvm::runtime::ObjectRef const&,
tvm::tir::StmtFunctor<tvm::tir::Stmt (tvm::tir::Stmt
const&)>*)>::operator()(tvm::runtime::ObjectRef const&,
tvm::tir::StmtFunctor<tvm::tir::Stmt (tvm::tir::Stmt const&)>*) const
30: _ZZN3tvm3tir11StmtFuncto
29: tvm::arith::StmtSimplifier::VisitStmt_(tvm::tir::ForNode const*)
28: tvm::arith::IRMutatorWithAnalyzer::VisitStmt_(tvm::tir::ForNode const*)
27: tvm::tir::StmtMutator::VisitStmt_(tvm::tir::ForNode const*)
26: tvm::arith::StmtSimplifier::VisitStmt(tvm::tir::Stmt const&)
25: tvm::tir::StmtFunctor<tvm::tir::Stmt (tvm::tir::Stmt
const&)>::VisitStmt(tvm::tir::Stmt const&)
24: tvm::NodeFunctor<tvm::tir::Stmt (tvm::runtime::ObjectRef const&,
tvm::tir::StmtFunctor<tvm::tir::Stmt (tvm::tir::Stmt
const&)>*)>::operator()(tvm::runtime::ObjectRef const&,
tvm::tir::StmtFunctor<tvm::tir::Stmt (tvm::tir::Stmt const&)>*) const
23: _ZZN3tvm3tir11StmtFuncto
22: tvm::arith::StmtSimplifier::VisitStmt_(tvm::tir::ForNode const*)
21: tvm::arith::IRMutatorWithAnalyzer::VisitStmt_(tvm::tir::ForNode const*)
20: tvm::tir::StmtMutator::VisitStmt_(tvm::tir::ForNode const*)
19: tvm::arith::StmtSimplifier::VisitStmt(tvm::tir::Stmt const&)
18: tvm::tir::StmtFunctor<tvm::tir::Stmt (tvm::tir::Stmt
const&)>::VisitStmt(tvm::tir::Stmt const&)
17: tvm::NodeFunctor<tvm::tir::Stmt (tvm::runtime::ObjectRef const&,
tvm::tir::StmtFunctor<tvm::tir::Stmt (tvm::tir::Stmt
const&)>*)>::operator()(tvm::runtime::ObjectRef const&,
tvm::tir::StmtFunctor<tvm::tir::Stmt (tvm::tir::Stmt const&)>*) const
16: _ZZN3tvm3tir11StmtFuncto
15: tvm::arith::StmtSimplifier::VisitStmt_(tvm::tir::BufferStoreNode
const*)
14: tvm::tir::StmtMutator::VisitStmt_(tvm::tir::BufferStoreNode const*)
13: tvm::arith::StmtSimplifier::VisitExpr(tvm::PrimExpr const&)
12: tvm::arith::Analyzer::Simplify(tvm::PrimExpr const&, int)
11: tvm::arith::CanonicalSimplifier::operator()(tvm::PrimExpr const&)
10: tvm::arith::CanonicalSimplifier::Impl::CanonicalSimplify(tvm::PrimExpr)
9: _ZThn16_N3tvm5arit
8: tvm::arith::CanonicalSimplifier::Impl::VisitExpr(tvm::PrimExpr const&)
7: tvm::tir::ExprFunctor<tvm::PrimExpr (tvm::PrimExpr
const&)>::VisitExpr(tvm::PrimExpr const&)
6: tvm::NodeFunctor<tvm::PrimExpr (tvm::runtime::ObjectRef const&,
tvm::tir::ExprFunctor<tvm::PrimExpr (tvm::PrimExpr
const&)>*)>::operator()(tvm::runtime::ObjectRef const&,
tvm::tir::ExprFunctor<tvm::PrimExpr (tvm::PrimExpr const&)>*) const
5: _ZZN3tvm3tir11ExprFuncto
4: _ZThn16_N3tvm5arit
3: tvm::arith::CanonicalSimplifier::Impl::VisitExpr_(tvm::tir::DivNode
const*)
2: tvm::arith::RewriteSimplifier::Impl::VisitExpr_(tvm::tir::DivNode
const*)
1: tvm::runtime::Optional<tvm::PrimExpr>
tvm::arith::TryConstFold<tvm::tir::Div>(tvm::PrimExpr, tvm::PrimExpr)
0: _ZN3tvm7runtime6detail
File "/workplace/software/tvm/tvm_/src/arith/const_fold.h", line 245
TVMError:
---------------------------------------------------------------
An error occurred during the execution of TVM.
For more information, please see: https://tvm.apache.org/docs/errors.html
---------------------------------------------------------------
Check failed: fb->value != 0 (0 vs. 0) : Divide by zero
```
### Environment
- TVM: latest
- Pytorch: 1.13.1+cu117
### Steps to reproduce
```Python
import torch
from tvm import relay
import tvm
import numpy as np
m = torch.nn.Softplus(beta=0,)
input_data = torch.tensor(torch.randn([14, 7], dtype=torch.float64))
torch_outputs = m(input_data)
trace = torch.jit.trace(m, input_data)
input_shapes = [('input0', torch.Size([14, 7]))]
mod, params = relay.frontend.from_pytorch(trace, input_shapes)
input_data_np = input_data.numpy()
with tvm.transform.PassContext(opt_level=3):
exe = relay.create_executor('graph', mod=mod, params=params,
device=tvm.device('llvm', 0), target='llvm').evaluate()
input_tvm = {'input0': tvm.nd.array(input_data_np.astype(np.float64))}
tvm_outputs = exe(**input_tvm).asnumpy()
np.testing.assert_allclose(torch_outputs, tvm_outputs, rtol=1e-3, atol=1e-3)
```
### Triage
* needs-triage
* frontend:torch
Is this a bug in TVM?
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