coffezhou opened a new issue, #17876:
URL: https://github.com/apache/tvm/issues/17876

   
   ### Expected behavior
   
   TVM should compile the model correctly with the default relax optimization 
pipeline.
   
   ### Actual behavior
   
   When compiling the model with the default relax optimization pipeline when 
opt_level=1, TVM crashes as follows:
   ```c
   Traceback (most recent call last):
     File "/home/carla/Documents/test/test.py", line 63, in <module>
       main()
     File "/home/carla/Documents/test/test.py", line 52, in main
       ex = relax.build(tvm_model, target="llvm", relax_pipeline=relax_pipeline)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
     File "/home/carla/Documents/tvm/python/tvm/relax/vm_build.py", line 253, 
in build
       mod = relax_pipeline(mod)
             ^^^^^^^^^^^^^^^^^^^
     File "/home/carla/Documents/tvm/python/tvm/ir/transform.py", line 238, in 
__call__
       return _ffi_transform_api.RunPass(self, mod)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
     File "tvm/_ffi/_cython/./packed_func.pxi", line 339, in 
tvm._ffi._cy3.core.PackedFuncBase.__call__
     File "tvm/_ffi/_cython/./packed_func.pxi", line 270, in 
tvm._ffi._cy3.core.FuncCall
     File "tvm/_ffi/_cython/./packed_func.pxi", line 259, in 
tvm._ffi._cy3.core.FuncCall3
     File "tvm/_ffi/_cython/./base.pxi", line 185, in 
tvm._ffi._cy3.core.CHECK_CALL
     File "/home/carla/Documents/tvm/python/tvm/_ffi/base.py", line 468, in 
raise_last_ffi_error
       raise py_err
     File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in 
tvm._ffi._cy3.core.tvm_callback
     File 
"/home/carla/Documents/tvm/python/tvm/relax/backend/cpu_generic/pipeline.py", 
line 73, in _pipeline
       mod = seq(mod)
             ^^^^^^^^
     File "/home/carla/Documents/tvm/python/tvm/ir/transform.py", line 238, in 
__call__
       return _ffi_transform_api.RunPass(self, mod)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
     File "tvm/_ffi/_cython/./packed_func.pxi", line 339, in 
tvm._ffi._cy3.core.PackedFuncBase.__call__
     File "tvm/_ffi/_cython/./packed_func.pxi", line 270, in 
tvm._ffi._cy3.core.FuncCall
     File "tvm/_ffi/_cython/./packed_func.pxi", line 259, in 
tvm._ffi._cy3.core.FuncCall3
     File "tvm/_ffi/_cython/./base.pxi", line 185, in 
tvm._ffi._cy3.core.CHECK_CALL
     File "/home/carla/Documents/tvm/python/tvm/_ffi/base.py", line 468, in 
raise_last_ffi_error
       raise py_err
   tvm.error.InternalError: Traceback (most recent call last):
     27: 
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::IRModule
 (tvm::transform::Pass, 
tvm::IRModule)>::AssignTypedLambda<tvm::transform::{lambda(tvm::transform::Pass,
 tvm::IRModule)#7}>(tvm::transform::{lambda(tvm::transform::Pass, 
tvm::IRModule)#7}, 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*)
     26: tvm::transform::Pass::operator()(tvm::IRModule) const
     25: tvm::transform::Pass::operator()(tvm::IRModule, 
tvm::transform::PassContext const&) const
     24: tvm::transform::SequentialNode::operator()(tvm::IRModule, 
tvm::transform::PassContext const&) const
     23: tvm::transform::Pass::operator()(tvm::IRModule, 
tvm::transform::PassContext const&) const
     22: tvm::transform::ModulePassNode::operator()(tvm::IRModule, 
tvm::transform::PassContext const&) const
     21: 
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::IRModule
 (tvm::IRModule, 
tvm::transform::PassContext)>::AssignTypedLambda<tvm::relax::transform::VMShapeLower(bool)::{lambda(tvm::IRModule,
 
tvm::transform::PassContext)#1}>(tvm::relax::transform::VMShapeLower(bool)::{lambda(tvm::IRModule,
 tvm::transform::PassContext)#1})::{lambda(tvm::runtime::TVMArgs const&, 
tvm::runtime::TVMRetValue*)#1}> >::Call(tvm::runtime::PackedFuncObj const*, 
tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*)
     20: tvm::relax::VMShapeLowerMutator::Lower(tvm::IRModule, bool)
     19: tvm::relax::VMShapeLowerMutator::Rewrite(tvm::GlobalVar, 
tvm::relax::Function)
     18: tvm::relax::ExprMutator::VisitWithNewScope(tvm::RelaxExpr const&, 
tvm::runtime::Optional<tvm::runtime::Array<tvm::relax::Var, void> >)
     17: tvm::relax::ExprMutator::VisitExpr(tvm::RelaxExpr const&)
     16: tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr 
const&)>::VisitExpr(tvm::RelaxExpr const&)
     15: 
_ZZN3tvm5relax11ExprFunctorIFNS_9RelaxExprERKS2_EE10InitVTableEvENUlRKNS_7r
     14: tvm::relax::ExprMutator::VisitExpr_(tvm::relax::SeqExprNode const*)
     13: tvm::relax::ExprMutator::VisitBindingBlock(tvm::relax::BindingBlock 
const&)
     12: 
tvm::relax::ExprMutator::VisitBindingBlock_(tvm::relax::BindingBlockNode const*)
     11: tvm::relax::ExprMutator::VisitBinding(tvm::relax::Binding const&)
     10: tvm::relax::ExprMutator::VisitBinding_(tvm::relax::VarBindingNode 
const*)
     9: tvm::relax::ExprMutator::VisitBinding_(tvm::relax::VarBindingNode 
const*, tvm::relax::ConstantNode const*)
     8: tvm::relax::ExprMutator::VisitExpr(tvm::RelaxExpr const&)
     7: tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr 
const&)>::VisitExpr(tvm::RelaxExpr const&)
     6: 
_ZZN3tvm5relax11ExprFunctorIFNS_9RelaxExprERKS2_EE10InitVTableEvENUlRKNS_7r
     5: tvm::relax::ExprMutatorBase::VisitExpr_(tvm::relax::CallNode const*)
     4: tvm::relax::ExprMutator::VisitExpr(tvm::RelaxExpr const&)
     3: tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr 
const&)>::VisitExpr(tvm::RelaxExpr const&)
     2: 
_ZZN3tvm5relax11ExprFunctorIFNS_9RelaxExprERKS2_EE10InitVTableEvENUlRKNS_7r
     1: tvm::relax::VMShapeLowerMutator::VisitExpr_(tvm::relax::ShapeExprNode 
const*)
     0: tvm::relax::VMShapeLowerMutator::MakeSymbolicShapeArg(tvm::PrimExpr 
const&)
     File "/home/carla/Documents/tvm/src/relax/backend/vm/vm_shape_lower.cc", 
line 365
   InternalError: Check failed: (slot->value_computed) is false: PrimExpr 
T.int64(4) * (x_0 * x_1 * x_2 * x_3) in function I.GlobalVar("main") has not 
been computed
   
   ```
   
   ### Environment
   
   OS: Ubuntu 20.04
   TVM: 0.21.dev0(c00f52a70)
   
   ### Steps to reproduce
   This bug can be reproduced by the following code with the model in the 
attachment. As shown in the code, the model can be executed by onnxruntime. 
However, tvm failed to the model with the default relax optimization pipeline 
when opt_level=1. If we set opt_level=0, this bug is gone.
   ```python
   import sys
   
   import numpy as np
   import onnx
   import onnxruntime
   
   import tvm
   from tvm import relax
   from tvm.relax.frontend.onnx import from_onnx
   
   import pickle
               
   def main():
       onnx_model = onnx.load("a240.onnx")
       
       with open("inputs.pkl", "rb") as fp:
           inputs = pickle.load(fp)
       
       try:
           ort_session = onnxruntime.InferenceSession(
               onnx_model.SerializeToString(), 
providers=["CPUExecutionProvider"]
           )
           ort_output = ort_session.run([], inputs)
       except Exception as e:
           print(e)
           sys.exit(1)
       
       # Convert the onnx model into relax through the onnx importer.
       tvm_model = from_onnx(onnx_model, keep_params_in_input=True)
       # Convert operators for inference mode.
       tvm_model = relax.transform.DecomposeOpsForInference()(tvm_model)
       # Legalize any relax ops into tensorir.
       tvm_model = relax.transform.LegalizeOps()(tvm_model)
   
       # Separate model from parameters.
       tvm_model, params = relax.frontend.detach_params(tvm_model)
   
       # Prepare inputs.
       input_list = [
           inputs[key.name_hint] for key in tvm_model["main"].params if 
key.name_hint in inputs
       ]
       if params:
           input_list += params["main"]
           
       # Compile the relax graph into a VM then run.
       #----------------------cpu-----------------------
       with tvm.transform.PassContext(opt_level=1):
           target = tvm.target.Target("llvm", host="llvm")
           relax_pipeline = relax.pipeline.get_default_pipeline(target)
           
           ex = relax.build(tvm_model, target="llvm", 
relax_pipeline=relax_pipeline)
           vm = relax.VirtualMachine(ex, tvm.cpu())
       
           # Run model and check outputs.
           vm.set_input("main", *input_list)
           vm.invoke_stateful("main")
           tvm_cpu_output = vm.get_outputs("main")
       #----------------------cpu-----------------------
       
   
   if __name__ == "__main__":    
       main()
   
   ```
   
   
[testcase.zip](https://github.com/user-attachments/files/19845075/testcase.zip)
   
   ### Triage
   
   * needs-triage
   


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