Closed
Description
Expected behavior
The onnx frontend should import the model correctly.
Actual behavior
When importing the following onnx model, tvm crashes as follows:
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(c00f52a)
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.
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()Triage
- needs-triage