Cookiee235 opened a new issue, #17231:
URL: https://github.com/apache/tvm/issues/17231
### Actual behavior
```
Traceback (most recent call last):
File "/share_container/optfuzz/res/bugs/simple/res_undefined.py", line 49,
in <module>
compiled_after = compile_mod(relax.transform.LiftTransformParams()(mod))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/share_container/optfuzz/res/bugs/simple/res_undefined.py", line 41,
in compile_mod
ex = relax.build(mod, target="llvm")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/software/tvm-lunder/python/tvm/relax/vm_build.py", line 340, in
build
mod = _vmcodegen(builder, mod, exec_mode)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/software/tvm-lunder/python/tvm/relax/vm_build.py", line 176, in
_vmcodegen
return _ffi_api.VMCodeGen(builder, mod) # type:ignore
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/software/tvm-lunder/python/tvm/_ffi/_ctypes/packed_func.py", line
240, in __call__
raise_last_ffi_error()
File "/software/tvm-lunder/python/tvm/_ffi/base.py", line 481, in
raise_last_ffi_error
raise py_err
tvm.error.InternalError: Traceback (most recent call last):
7:
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::IRModule
(tvm::relax::ExecBuilder, tvm::IRModule)>::AssignTypedLambda<tvm::IRModule
(*)(tvm::relax::ExecBuilder, tvm::IRModule)>(tvm::IRModule
(*)(tvm::relax::ExecBuilder, tvm::IRModule), 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*)
6: tvm::relax::relax_vm::VMCodeGen(tvm::relax::ExecBuilder, tvm::IRModule)
5: tvm::relax::relax_vm::CodeGenVM::Run(tvm::relax::ExecBuilder,
tvm::IRModule)
4: tvm::relax::relax_vm::CodeGenVM::Codegen(tvm::relax::Function const&)
3: tvm::relax::ExprFunctor<tvm::runtime::relax_vm::Instruction::Arg
(tvm::RelayExpr const&)>::VisitExpr(tvm::RelayExpr const&)
2: tvm::relax::relax_vm::CodeGenVM::VisitExpr_(tvm::relax::SeqExprNode
const*)
1: tvm::relax::ExprFunctor<tvm::runtime::relax_vm::Instruction::Arg
(tvm::RelayExpr const&)>::VisitExpr(tvm::RelayExpr const&)
0: tvm::relax::relax_vm::CodeGenVM::VisitExpr_(tvm::relax::VarNode const*)
File "/software/tvm-lunder/src/relax/backend/vm/codegen_vm.cc", line 232
InternalError: Check failed: (it != this->var_arg_map_.end()) is false: Var
w1_t is not defined
```
### Steps to reproduce
```
import tvm
from tvm import relax
import numpy as np
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 transpose(w1: T.Buffer((T.int64(256), T.int64(256)), "float32"),
T_transpose: T.Buffer((T.int64(256), T.int64(256)), "float32")):
T.func_attr({"tir.noalias": T.bool(True)})
# with T.block("root"):
for ax0, ax1 in T.grid(T.int64(256), T.int64(256)):
with T.block("T_transpose"):
v_ax0, v_ax1 = T.axis.remap("SS", [ax0, ax1])
T.reads(w1[v_ax1, v_ax0])
T.writes(T_transpose[v_ax0, v_ax1])
T_transpose[v_ax0, v_ax1] = w1[v_ax1, v_ax0]
@R.function(private=False)
def main(x: R.Tensor((256, 256), dtype="float32"), w1: R.Tensor((256,
256), dtype="float32")) -> R.Tensor((256, 256), dtype="float32"):
R.func_attr({"num_input": 1})
cls = Module
with R.dataflow():
w1_t = R.call_tir(cls.transpose, (w1,), out_sinfo=R.Tensor((256,
256), dtype="float32"))
R.output(w1_t)
return w1_t
mod = Module
mod.show()
mod = tvm.relax.transform.LegalizeOps()(mod)
input_0 = tvm.nd.array(10 * np.random.random([256, 256]).astype('float32'))
input_1 = tvm.nd.array(10 * np.random.random([256, 256]).astype('float32'))
def compile_mod(mod):
mod = relax.transform.FuseTIR()(mod)
mod = relax.transform.LambdaLift()(mod)
ex = relax.build(mod, target="llvm")
vm = relax.VirtualMachine(ex, tvm.cpu())
return vm
compiled_before = compile_mod(mod)
before_outputs = compiled_before["main"](input_0, input_1)
compiled_after = compile_mod(relax.transform.LiftTransformParams()(mod))
transformed_weights = compiled_after["main_transform_params"]([input_1])
after_outputs = compiled_after["main"](input_0, *transformed_weights)
```
cc @Lunderberg @junrushao
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