coffezhou opened a new issue, #17744:
URL: https://github.com/apache/tvm/issues/17744
### Expected behavior
TVM should build the model correctly.
### Actual behavior
```c
Traceback (most recent call last):
File "/home/carla/Documents/test_tvm/0312/test_relax2.py", line 81, in
<module>
ex = relax.build(tvm_model, target="llvm")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/relax/vm_build.py", line 259,
in build
return _vmlink(
^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/relax/vm_build.py", line 154,
in _vmlink
lib = tvm.tir.build(tir_mod, target=target, pipeline=tir_pipeline)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/tir/build.py", line 173, in
build
mod = 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/tir/pipeline.py", line 122, in
_pipeline
mod = tvm.ir.transform.Sequential(passes)(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):
57:
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*)
56: tvm::transform::Pass::operator()(tvm::IRModule) const
55: tvm::transform::Pass::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
54: tvm::transform::SequentialNode::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
53: tvm::transform::Pass::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
52: tvm::tir::transform::PrimFuncPassNode::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
51: _ZN3tvm7runtime13PackedFuncObj
50: tvm::runtime::TypedPackedFunc<tvm::tir::PrimFunc (tvm::tir::PrimFunc,
tvm::IRModule,
tvm::transform::PassContext)>::AssignTypedLambda<tvm::tir::transform::Simplify()::{lambda(tvm::tir::PrimFunc,
tvm::IRModule,
tvm::transform::PassContext)#1}>(tvm::tir::transform::Simplify()::{lambda(tvm::tir::PrimFunc,
tvm::IRModule, tvm::transform::PassContext)#1})::{lambda(tvm::runtime::TVMArgs
const&, tvm::runtime::TVMRetValue*)#1}::operator()(tvm::runtime::TVMArgs
const&, tvm::runtime::TVMRetValue*) const
49: tvm::arith::StmtSimplifier::Apply(tvm::tir::PrimFunc,
tvm::arith::Analyzer*, tvm::runtime::Optional<tvm::arith::SimplifyConfig>)
48: tvm::arith::StmtSimplifier::VisitStmt(tvm::tir::Stmt const&)
47:
_ZZN3tvm3tir11StmtFunctorIFNS0_4StmtERKS2_EE10InitVTableEvENUlRKNS_7runtime9Ob
46: tvm::arith::StmtSimplifier::VisitStmt(tvm::tir::Stmt const&)
45:
_ZZN3tvm3tir11StmtFunctorIFNS0_4StmtERKS2_EE10InitVTableEvENUlRKNS_7runtime9Ob
44: tvm::arith::IRMutatorWithAnalyzer::VisitStmt_(tvm::tir::BlockNode
const*)
43: tvm::arith::StmtSimplifier::VisitStmt(tvm::tir::Stmt const&)
42:
_ZZN3tvm3tir11StmtFunctorIFNS0_4StmtERKS2_EE10InitVTableEvENUlRKNS_7runtime9Ob
41: tvm::runtime::ObjectPtr<tvm::runtime::Object>
tvm::runtime::Array<tvm::tir::Stmt,
void>::MapHelper<tvm::tir::StmtMutator::Internal::Mutate(tvm::tir::StmtMutator*,
tvm::runtime::Array<tvm::tir::Stmt, void> const&)::{lambda(tvm::tir::Stmt
const&)#1}, tvm::tir::Stmt>(tvm::runtime::ObjectPtr<tvm::runtime::Object>,
tvm::tir::StmtMutator::Internal::Mutate(tvm::tir::StmtMutator*,
tvm::runtime::Array<tvm::tir::Stmt, void> const&)::{lambda(tvm::tir::Stmt
const&)#1})
40: tvm::arith::StmtSimplifier::VisitStmt(tvm::tir::Stmt const&)
39:
_ZZN3tvm3tir11StmtFunctorIFNS0_4StmtERKS2_EE10InitVTableEvENUlRKNS_7runtime
38: tvm::arith::StmtSimplifier::VisitStmt_(tvm::tir::ForNode const*)
37: tvm::arith::IRMutatorWithAnalyzer::VisitStmt_(tvm::tir::ForNode const*)
36: tvm::arith::StmtSimplifier::VisitStmt(tvm::tir::Stmt const&)
35:
_ZZN3tvm3tir11StmtFunctorIFNS0_4StmtERKS2_EE10InitVTableEvENUlRKNS_7runtime
34: tvm::arith::StmtSimplifier::VisitStmt_(tvm::tir::ForNode const*)
33: tvm::arith::IRMutatorWithAnalyzer::VisitStmt_(tvm::tir::ForNode const*)
32: tvm::arith::StmtSimplifier::VisitStmt(tvm::tir::Stmt const&)
31:
_ZZN3tvm3tir11StmtFunctorIFNS0_4StmtERKS2_EE10InitVTableEvENUlRKNS_7runtime
30: tvm::arith::StmtSimplifier::VisitStmt_(tvm::tir::ForNode const*)
29: tvm::arith::IRMutatorWithAnalyzer::VisitStmt_(tvm::tir::ForNode const*)
28: tvm::arith::StmtSimplifier::VisitStmt(tvm::tir::Stmt const&)
27:
_ZZN3tvm3tir11StmtFunctorIFNS0_4StmtERKS2_EE10InitVTableEvENUlRKNS_7runtime
26: tvm::arith::StmtSimplifier::VisitStmt_(tvm::tir::ForNode const*)
25: tvm::arith::IRMutatorWithAnalyzer::VisitStmt_(tvm::tir::ForNode const*)
24: tvm::arith::StmtSimplifier::VisitStmt(tvm::tir::Stmt const&)
23:
_ZZN3tvm3tir11StmtFunctorIFNS0_4StmtERKS2_EE10InitVTableEvENUlRKNS_7runtime9Ob
22: tvm::arith::StmtSimplifier::VisitStmt(tvm::tir::Stmt const&)
21:
_ZZN3tvm3tir11StmtFunctorIFNS0_4StmtERKS2_EE10InitVTableEvENUlRKNS_7runtime9Ob
20: tvm::arith::IRMutatorWithAnalyzer::VisitStmt_(tvm::tir::BlockNode
const*)
19: tvm::arith::StmtSimplifier::VisitStmt(tvm::tir::Stmt const&)
18:
_ZZN3tvm3tir11StmtFunctorIFNS0_4StmtERKS2_EE10InitVTableEvENUlRKNS_7runtime
17: tvm::arith::StmtSimplifier::VisitStmt_(tvm::tir::BufferStoreNode
const*)
16: tvm::arith::StmtSimplifier::VisitExpr(tvm::PrimExpr const&)
15: tvm::arith::Analyzer::Simplify(tvm::PrimExpr const&, int)
14: tvm::arith::CanonicalSimplifier::operator()(tvm::PrimExpr const&)
13: non-virtual thunk to
tvm::arith::CanonicalSimplifier::Impl::VisitExpr(tvm::PrimExpr const&)
12: tvm::arith::RewriteSimplifier::Impl::VisitExpr(tvm::PrimExpr const&)
11:
_ZZN3tvm3tir11ExprFunctorIFNS_8PrimExprERKS2_EE10InitVTableEvENUlRKNS_7runt
10: tvm::arith::CanonicalSimplifier::Impl::VisitExpr_(tvm::tir::DivNode
const*)
9: tvm::arith::RewriteSimplifier::Impl::VisitExpr_(tvm::tir::DivNode
const*)
8: non-virtual thunk to
tvm::arith::CanonicalSimplifier::Impl::VisitExpr(tvm::PrimExpr const&)
7: tvm::arith::RewriteSimplifier::Impl::VisitExpr(tvm::PrimExpr const&)
6:
_ZZN3tvm3tir11ExprFunctorIFNS_8PrimExprERKS2_EE10InitVTableEvENUlRKNS_7runtime
5: tvm::arith::CanonicalSimplifier::Impl::VisitExpr_(tvm::tir::CastNode
const*)
4: tvm::arith::RewriteSimplifier::Impl::VisitExpr_(tvm::tir::CastNode
const*)
3: tvm::cast(tvm::runtime::DataType const&, tvm::PrimExpr, tvm::Span)
[clone .localalias]
2: tvm::PrimExpr tvm::tir::make_const<long, void>(tvm::runtime::DataType,
long, tvm::Span)
1: tvm::PrimExpr tvm::tir::MakeConstScalar<long>(tvm::runtime::DataType,
long, tvm::Span)
0: tvm::FloatImm::FloatImm(tvm::runtime::DataType, double, tvm::Span)
File "/home/carla/Documents/tvm/src/ir/expr.cc", line 127
InternalError: Check failed: value <= support::kMaxFloat16 (261121 vs.
65504) : ValueError: Literal value 261121 exceeds maximum of float16
```
### Environment
OS: Ubuntu 20.04
TVM: 0.20.dev0 (6e8c367)
### Steps to reproduce
This bug can be reproduced by the following code with the model in the
attachment. For the model, it can be correctly ran by onnxruntime. However, an
InternalError occurs when TVM build this model.
```python
from typing import Dict, List, Literal, Optional
import sys
import numpy as np
import onnx
import onnxruntime
from onnx import ModelProto, TensorProto, helper, mapping
import tvm
from tvm import relax
from tvm.relax.frontend.onnx import from_onnx
import argparse
bg = np.random.MT19937(0)
rg = np.random.Generator(bg)
def generate_random_inputs(
model: ModelProto, inputs: Optional[Dict[str, np.ndarray]] = None
) -> Dict[str, np.ndarray]:
input_values = {}
# Iterate through model inputs and extract their shape.
for i in model.graph.input:
if inputs is not None and i.name in inputs and inputs[i.name] is not
None:
input_values[i.name] = inputs[i.name]
continue
shape = []
for dim in i.type.tensor_type.shape.dim:
shape.append(dim.dim_value)
input_values[i.name] = generate_random_value(shape,
i.type.tensor_type.elem_type)
return input_values
def generate_random_value(shape, elem_type) -> np.ndarray:
# Extract datatype for the input.
if elem_type:
dtype = str(helper.tensor_dtype_to_np_dtype(elem_type))
else:
dtype = "float32"
# Generate random inputs for each input.
if dtype == "bool":
# random_value = np.random.choice(a=[False, True], size=shape)
random_value = rg.choice(a=[False, True], size=shape)
elif dtype.startswith("int"):
# Keep non-zero values
random_value = rg.integers(low=-63, high=63,
size=shape).astype(dtype)
random_value[random_value <= 0] -= 1
else:
random_value = rg.standard_normal(size=shape).astype(dtype)
return random_value
model_path = "./bugs/onnx_output3252/model.onnx"
model = onnx.load(model_path)
inputs: Optional[Dict[str, np.ndarray]] = None
inputs = generate_random_inputs(model, inputs)
try:
ort_session = onnxruntime.InferenceSession(
model.SerializeToString(), providers=["CPUExecutionProvider"]
)
ort_output = ort_session.run([], inputs)
except:
print("This model cannot be executed by onnxruntime!")
sys.exit(1)
print(ort_output)
tvm_model = from_onnx(model, keep_params_in_input=True)
tvm_model = relax.transform.DecomposeOpsForInference()(tvm_model)
tvm_model = relax.transform.LegalizeOps()(tvm_model)
tvm_model, params = relax.frontend.detach_params(tvm_model)
with tvm.transform.PassContext(opt_level=0):
ex = relax.build(tvm_model, target="llvm")
vm = relax.VirtualMachine(ex, tvm.cpu())
```
[model.zip](https://github.com/user-attachments/files/19221043/model.zip)
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