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Posted to commits@tvm.apache.org by "coffezhou (via GitHub)" <gi...@apache.org> on 2025/04/18 10:11:00 UTC
[I] [Bug] [FRONTEND][ONNX] failed to import TopK operator when K is a constant tensor: ValueError: TopK k must be a constant [tvm]
coffezhou opened a new issue, #17856:
URL: https://github.com/apache/tvm/issues/17856
### Expected behavior
The onnx frontend should import the model correctly.
### Actual behavior
When importing the following onnx model, tvm crashes as follows:
```c
Traceback (most recent call last):
File "/home/carla/Documents/test/test.py", line 189, in <module>
main()
File "/home/carla/Documents/test/test.py", line 178, in main
check_correctness(onnx_model)
File "/home/carla/Documents/test/test.py", line 104, in check_correctness
tvm_model = from_onnx(model, opset=opset, keep_params_in_input=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/relax/frontend/onnx/onnx_frontend.py", line 3690, in from_onnx
return g.from_onnx(graph, opset)
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/relax/frontend/onnx/onnx_frontend.py", line 3321, in from_onnx
self._construct_nodes(graph)
File "/home/carla/Documents/tvm/python/tvm/relax/frontend/onnx/onnx_frontend.py", line 3496, in _construct_nodes
op = self._convert_operator(op_name, inputs, attr, self.opset)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/relax/frontend/onnx/onnx_frontend.py", line 3596, in _convert_operator
sym = op_function(self.bb, inputs, attrs, [self._nodes, self._params])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/relax/frontend/onnx/onnx_frontend.py", line 2706, in _impl_v11
raise ValueError("TopK k must be a constant")
ValueError: TopK k must be a constant
[17:35:01] /home/carla/Documents/tvm/src/relax/ir/block_builder.cc:64: Warning: BlockBuilder destroyed with remaining blocks!
```
The attribute K of TopK should be a constant. In this model, K is a constant tensor, which meets the constraint of TopK. Thus, this may be a bug of the onnx frontend in TVM.
### 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.
```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("a157.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)
if __name__ == "__main__":
main()
```
[testcase.zip](https://github.com/user-attachments/files/19811321/testcase.zip)
### Triage
* needs-triage
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Re: [I] [Bug] [FRONTEND][ONNX] failed to import TopK operator when K is a constant tensor: ValueError: TopK k must be a constant [tvm]
Posted by "coffezhou (via GitHub)" <gi...@apache.org>.
coffezhou closed issue #17856: [Bug] [FRONTEND][ONNX] failed to import TopK operator when K is a constant tensor: ValueError: TopK k must be a constant
URL: https://github.com/apache/tvm/issues/17856
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Re: [I] [Bug] [FRONTEND][ONNX] failed to import TopK operator when K is a constant tensor: ValueError: TopK k must be a constant [tvm]
Posted by "erdayang (via GitHub)" <gi...@apache.org>.
erdayang commented on issue #17856:
URL: https://github.com/apache/tvm/issues/17856#issuecomment-2830697268
I have the same confusion. TVM's support for ONNX feels quite immature. I wonder if its support for other frontends is the same.
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Re: [I] [Bug] [FRONTEND][ONNX] failed to import TopK operator when K is a constant tensor: ValueError: TopK k must be a constant [tvm]
Posted by "coffezhou (via GitHub)" <gi...@apache.org>.
coffezhou commented on issue #17856:
URL: https://github.com/apache/tvm/issues/17856#issuecomment-2930022215
This issue is caused by the keep_params_in_input parameter.
If keep_params_in_input=True, parameters will be treated as input variables. If false, parameters are treated as constant and folded directly into the graph.
In this issue, for the TopK operator, if keep_params_in_input=True, the input 'k' cannot be treated as a constant.
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