Cookiee235 opened a new issue, #17217:
URL: https://github.com/apache/tvm/issues/17217
### Actual behavior
```
Traceback (most recent call last):
File "test_simple.py", line 46, in <module>
ex = relax.build(mod, target='llvm') # crash here!
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/software/tvm/python/tvm/relax/vm_build.py", line 335, in build
mod = pipeline(mod)
^^^^^^^^^^^^^
File "/software/tvm/python/tvm/ir/transform.py", line 265, in __call__
return _ffi_transform_api.RunPass(self, mod)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/software/tvm/python/tvm/_ffi/_ctypes/packed_func.py", line 239, in
__call__
raise_last_ffi_error()
File "/software/tvm/python/tvm/_ffi/base.py", line 481, in
raise_last_ffi_error
raise py_err
File "/software/tvm/python/tvm/relax/pipeline.py", line 101, in _pipeline
mod = seq(mod)
^^^^^^^^
File "/software/tvm/python/tvm/ir/transform.py", line 265, in __call__
return _ffi_transform_api.RunPass(self, mod)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/software/tvm/python/tvm/_ffi/_ctypes/packed_func.py", line 239, in
__call__
raise_last_ffi_error()
File "/software/tvm/python/tvm/_ffi/base.py", line 481, in
raise_last_ffi_error
raise py_err
tvm._ffi.base.TVMError: Traceback (most recent call last):
28:
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*,
std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char>
>, tvm::runtime::TVMRetValue)
27: tvm::transform::Pass::operator()(tvm::IRModule) const
26: tvm::transform::Pass::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
25: tvm::transform::SequentialNode::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
24: tvm::transform::Pass::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
23: tvm::relax::transform::FunctionPassNode::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
22: _ZN3tvm7runtime13PackedFuncObj9ExtractorINS0_1
21: tvm::runtime::TypedPackedFunc<tvm::relax::Function
(tvm::relax::Function, tvm::IRModule,
tvm::transform::PassContext)>::AssignTypedLambda<tvm::relax::transform::VMBuiltinLower()::{lambda(tvm::relax::Function,
tvm::IRModule,
tvm::transform::PassContext)#1}>(tvm::relax::transform::VMBuiltinLower()::{lambda(tvm::relax::Function,
tvm::IRModule, tvm::transform::PassContext)#1})::{lambda(tvm::runtime::TVMArgs
const&, tvm::runtime::TVMRetValue*)#1}::operator()(tvm::runtime::TVMArgs const,
tvm::runtime::TVMRetValue) const
20: tvm::relax::VMBuiltinLower(tvm::RelayExpr const&)
19: tvm::relax::ExprMutator::VisitExpr(tvm::RelayExpr const&)
18: tvm::relax::ExprFunctor<tvm::RelayExpr (tvm::RelayExpr
const&)>::VisitExpr(tvm::RelayExpr const&)
17:
_ZZN3tvm5relax11ExprFunctorIFNS_9RelayExprERKS2_EE10InitVTableEvENUlRKNS_7runtime9ObjectRef
16: tvm::relax::ExprMutator::VisitExpr_(tvm::relax::FunctionNode const*)
15: tvm::relax::ExprMutator::VisitWithNewScope(tvm::RelayExpr const&,
tvm::runtime::Optional<tvm::runtime::Array<tvm::relax::Var, void> >)
14: tvm::relax::ExprMutator::VisitExpr(tvm::RelayExpr const&)
13: tvm::relax::ExprFunctor<tvm::RelayExpr (tvm::RelayExpr
const&)>::VisitExpr(tvm::RelayExpr const&)
12:
_ZZN3tvm5relax11ExprFunctorIFNS_9RelayExprERKS2_EE10InitVTableEvENUlRKNS_7runtime9ObjectRef
11: tvm::relax::ExprMutator::VisitExpr_(tvm::relax::SeqExprNode const*)
10: tvm::relax::ExprMutator::VisitBindingBlock(tvm::relax::BindingBlock
const&)
9:
tvm::relax::ExprMutator::VisitBindingBlock_(tvm::relax::BindingBlockNode const*)
8: tvm::relax::ExprMutator::VisitBinding(tvm::relax::Binding const&)
7: tvm::relax::ExprMutator::VisitBinding_(tvm::relax::VarBindingNode
const*)
6: _ZZN3tvm5relax11ExprMutator22InitVisitBindingVTabl
5: tvm::relax::ExprMutator::VisitBinding_(tvm::relax::VarBindingNode
const*, tvm::relax::CallNode const*)
4: tvm::relax::ExprMutator::VisitExpr(tvm::RelayExpr const&)
3: tvm::relax::ExprFunctor<tvm::RelayExpr (tvm::RelayExpr
const&)>::VisitExpr(tvm::RelayExpr const&)
2:
_ZZN3tvm5relax11ExprFunctorIFNS_9RelayExprERKS2_EE10InitVTableEvENUlRKNS_7runtime9ObjectRef
1: tvm::relax::VMBuiltinLowerMutator::VisitExpr_(tvm::relax::CallNode
const*)
0: tvm::relax::VMBuiltinLowerMutator::Reshape(tvm::relax::Call const&)
File "/software/tvm/src/relax/backend/vm/vm_builtin_lower.cc", line 120
TVMError: Check failed: (bound_val->IsInstance<ShapeExprNode>()) is false:
VMBuiltinLower expects bound value to be a ShapeExpr
```
### Environment
### Steps to reproduce
```
import tvm
from tvm import relax
from tvm.script import ir as I
from tvm.script import tir as T
from tvm.script import relax as R
@I.ir_module
class Module:
@T.prim_func(private=True)
def add(c0: T.Buffer((T.int64(2),), "int64"), c0_1:
T.Buffer((T.int64(2),), "int64"), T_add: T.Buffer((T.int64(2),), "int64")):
T.func_attr({"tir.noalias": T.bool(True)})
# with T.block("root"):
for ax0 in range(T.int64(2)):
with T.block("T_add"):
v_ax0 = T.axis.spatial(T.int64(2), ax0)
T.reads(c0[v_ax0], c0_1[v_ax0])
T.writes(T_add[v_ax0])
T_add[v_ax0] = c0[v_ax0] + c0_1[v_ax0]
@T.prim_func(private=True)
def multiply(lv0: T.Buffer((T.int64(2),), "int64"), c1:
T.Buffer((T.int64(2),), "int64"), T_multiply: T.Buffer((T.int64(2),), "int64")):
T.func_attr({"tir.noalias": T.bool(True)})
# with T.block("root"):
for ax0 in range(T.int64(2)):
with T.block("T_multiply"):
v_ax0 = T.axis.spatial(T.int64(2), ax0)
T.reads(lv0[v_ax0], c1[v_ax0])
T.writes(T_multiply[v_ax0])
T_multiply[v_ax0] = lv0[v_ax0] * c1[v_ax0]
@R.function
def main(data: R.Tensor((256,), dtype="float32"), c0: R.Tensor((2,),
dtype="int64"), c1: R.Tensor((2,), dtype="int64")) -> R.Tensor(dtype="float32",
ndim=2):
cls = Module
with R.dataflow():
lv0 = R.call_tir(cls.add, (c0, c0), out_sinfo=R.Tensor((2,),
dtype="int64"))
target_shape = R.call_tir(cls.multiply, (lv0, c1),
out_sinfo=R.Tensor((2,), dtype="int64"))
lv2: R.Shape(ndim=2) = R.tensor_to_shape(target_shape)
gv: R.Tensor(dtype="float32", ndim=2) = R.reshape(data, lv2)
R.output(gv)
return gv
mod = Module
mod = tvm.relax.transform.LegalizeOps()(mod)
mod = relax.transform.FuseTIR()(mod)
mod = relax.transform.LambdaLift()(mod)
ex = relax.build(mod, target='llvm') # crash here!
```
cc @Lunderberg @junrushao
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