coffezhou opened a new issue, #18596: URL: https://github.com/apache/tvm/issues/18596
### Expected behavior TVM should compile the model correctly. ### Actual behavior For the following model, <img width="189" height="264" alt="Image" src="https://github.com/user-attachments/assets/43b0d4f1-3bbf-44bd-b506-539a55f29904"; /> TVM crashes: ``` Traceback (most recent call last): File "/home/ubuntu/Documents/DLCompiler-test/tvm/1126/bugs/onnx_output4/test1.py", line 52, in <module> test(onnx_model) File "/home/ubuntu/Documents/DLCompiler-test/tvm/1126/bugs/onnx_output4/test1.py", line 45, in test tvm_model = relax.transform.LegalizeOps()(tvm_model) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ubuntu/Documents/DLCompilers/tvm/python/tvm/ir/transform.py", line 167, in __call__ return _ffi_transform_api.RunPass(self, mod) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "python/tvm_ffi/cython/function.pxi", line 904, in tvm_ffi.core.Function.__call__ File "<unknown>", line 0, in tvm::transform::Pass::operator()(tvm::IRModule) const File "<unknown>", line 0, in tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext const&) const File "<unknown>", line 0, in tvm::transform::ModulePassNode::operator()(tvm::IRModule, tvm::transform::PassContext const&) const File "<unknown>", line 0, in std::_Function_handler<tvm::IRModule (tvm::IRModule, tvm::transform::PassContext), tvm::relax::transform::LegalizeOps(tvm::ffi::Optional<tvm::ffi::Map<tvm::ffi::String, tvm::ffi::Function, void>, void>, tvm::ffi::Optional<tvm::ffi::Array<tvm::ffi::String, void>, void>, bool)::{lambda(tvm::IRModule, tvm::transform::PassContext)#1}>::_M_invoke(std::_Any_data const&, tvm::IRModule&&, tvm::transform::PassContext&&) File "<unknown>", line 0, in tvm::relax::transform::LegalizeOps(tvm::ffi::Optional<tvm::ffi::Map<tvm::ffi::String, tvm::ffi::Function, void>, void>, tvm::ffi::Optional<tvm::ffi::Array<tvm::ffi::String, void>, void>, bool)::{lambda(tvm::IRModule, tvm::transform::PassContext)#1}::operator()(tvm::IRModule, tvm::transform::PassContext) const File "<unknown>", line 0, in tvm::relax::LegalizeMutator::Transform() File "<unknown>", line 0, in tvm::relax::ExprMutator::VisitExpr(tvm::RelaxExpr const&) File "<unknown>", line 0, in tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr const&)>::VisitExpr(tvm::RelaxExpr const&) File "<unknown>", line 0, in tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr const&)>::InitVTable()::{lambda(tvm::ffi::ObjectRef const&, tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr const&)>*)#8}::_FUN(tvm::ffi::ObjectRef const&, tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr const&)>*) File "<unknown>", line 0, in tvm::relax::ExprMutator::VisitExpr_(tvm::relax::FunctionNode const*) File "<unknown>", line 0, in tvm::relax::ExprMutator::VisitWithNewScope(tvm::RelaxExpr const&, tvm::ffi::Optional<tvm::ffi::Array<tvm::relax::Var, void>, void>) File "<unknown>", line 0, in tvm::relax::ExprMutator::VisitExpr(tvm::RelaxExpr const&) File "<unknown>", line 0, in tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr const&)>::VisitExpr(tvm::RelaxExpr const&) File "<unknown>", line 0, in tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr const&)>::InitVTable()::{lambda(tvm::ffi::ObjectRef const&, tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr const&)>*)#10}::_FUN(tvm::ffi::ObjectRef const&, tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr const&)>*) File "<unknown>", line 0, in tvm::relax::ExprMutator::VisitExpr_(tvm::relax::SeqExprNode const*) File "<unknown>", line 0, in tvm::relax::ExprMutator::VisitBindingBlock(tvm::relax::BindingBlock const&) File "<unknown>", line 0, in tvm::relax::ExprMutator::VisitBindingBlock_(tvm::relax::DataflowBlockNode const*) File "<unknown>", line 0, in tvm::relax::ExprMutator::VisitBinding(tvm::relax::Binding const&) File "<unknown>", line 0, in tvm::relax::ExprMutator::VisitBinding_(tvm::relax::VarBindingNode const*) File "<unknown>", line 0, in tvm::relax::ExprMutator::VisitBinding_(tvm::relax::VarBindingNode const*, tvm::relax::IfNode const*) File "<unknown>", line 0, in tvm::relax::ExprMutator::VisitExpr(tvm::RelaxExpr const&) File "<unknown>", line 0, in tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr const&)>::VisitExpr(tvm::RelaxExpr const&) File "<unknown>", line 0, in tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr const&)>::InitVTable()::{lambda(tvm::ffi::ObjectRef const&, tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr const&)>*)#9}::_FUN(tvm::ffi::ObjectRef const&, tvm::relax::ExprFunctor<tvm::RelaxExpr (tvm::RelaxExpr const&)>*) File "<unknown>", line 0, in tvm::relax::LegalizeMutator::VisitExpr_(tvm::relax::CallNode const*) File "python/tvm_ffi/cython/function.pxi", line 1058, in tvm_ffi.core.tvm_ffi_callback File "/home/ubuntu/Documents/DLCompilers/tvm/python/tvm/relax/transform/legalize_ops/nn.py", line 493, in _nn_prelu return bb.call_te(topi.nn.prelu, call.args[0], call.args[1], call.attrs.axis) File "/home/ubuntu/Documents/DLCompilers/tvm/python/tvm/relax/block_builder.py", line 361, in call_te tir_func, call_args, output_sinfo, tir_vars = gen_call_tir_inputs(func, *args, **kwargs) File "/home/ubuntu/Documents/DLCompilers/tvm/python/tvm/relax/utils.py", line 355, in gen_call_tir_inputs te_out = func(*te_args, **te_kwargs) File "/home/ubuntu/Documents/DLCompilers/tvm/python/tvm/te/tag.py", line 57, in tagged_fdecl return fdecl(*args, **kwargs) File "/home/ubuntu/Documents/DLCompilers/tvm/python/tvm/topi/nn/elemwise.py", line 130, in prelu assert len(slope.shape) == 1 AssertionError ``` I am not sure that this is a bug for TVM. This issue is same as the [question](https://discuss.tvm.apache.org/t/prelu-op-can-not-support-broadcast/7880) that has been fixed. ### Environment OS: Ubuntu 20.04 TVM: 0.23.dev0 (f4e28d315) onnxruntime: 1.23.2 ### 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. ```python from typing import Dict, List, Literal, Optional import sys import os import numpy as np import onnx import onnxruntime from onnx import ModelProto, TensorProto, helper import tvm import tvm.testing from tvm import relax from tvm.relax.frontend.onnx import from_onnx import argparse import pickle def test( model: ModelProto, inputs: Optional[Dict[str, np.ndarray]] = None, ir_version: int = 8, opset: int = 14, ) -> None: # Configure model format. if ir_version is not None: model.ir_version = ir_version if opset is not None: model.opset_import[0].version = opset with open("inputs.pkl", 'rb') as fp: inputs = pickle.load(fp) # Run the model through onnx to get the expected result. try: ort_session = onnxruntime.InferenceSession( model.SerializeToString(), providers=["CPUExecutionProvider"] ) ort_output = ort_session.run([], inputs) except Exception as e: print(e) print("This model cannot be executed by onnxruntime!") sys.exit(1) tvm_model = from_onnx(model, opset=opset, keep_params_in_input=True) tvm_model = relax.transform.DecomposeOpsForInference()(tvm_model) tvm_model = relax.transform.LegalizeOps()(tvm_model) if __name__ == "__main__": onnx_model = onnx.load("11.onnx") test(onnx_model) ``` [testcase.zip](https://github.com/user-attachments/files/24292044/testcase.zip) ### Triage Please refer to the list of label tags [here](https://github.com/apache/tvm/wiki/Issue-Triage-Labels) to find the relevant tags and add them below in a bullet format (example below). * needs-triage -- This is an automated message from the Apache Git Service. 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