mkroening opened a new issue #9657:
URL: https://github.com/apache/tvm/issues/9657
### Expected behavior
No issue when running
```console
tvmc tune --target llvm --output autotuner_records.json model.onnx
```
with the ONNX model only being an addition of two single values.
Note that compiling the model without tuning works and produces valid
results.
Model:
```onnx
ir_version: 8
graph {
node {
input: "A"
input: "B"
output: "C"
op_type: "Add"
}
name: "test-model"
input {
name: "A"
type {
tensor_type {
elem_type: 1
shape {
dim {
dim_value: 1
}
}
}
}
}
input {
name: "B"
type {
tensor_type {
elem_type: 1
shape {
dim {
dim_value: 1
}
}
}
}
}
output {
name: "C"
type {
tensor_type {
elem_type: 1
shape {
dim {
dim_value: 1
}
}
}
}
}
}
opset_import {
version: 15
}
```
### Actual behavior
```
# [..]
Traceback (most recent call last):
File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/usr/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/mkroening/Development/tvm/python/tvm/driver/tvmc/__main__.py",
line 24, in <module>
tvmc.main.main()
File "/home/mkroening/Development/tvm/python/tvm/driver/tvmc/main.py",
line 100, in main
sys.exit(_main(sys.argv[1:]))
File "/home/mkroening/Development/tvm/python/tvm/driver/tvmc/main.py",
line 93, in _main
return args.func(args)
File
"/home/mkroening/Development/tvm/python/tvm/driver/tvmc/autotuner.py", line
266, in drive_tune
tune_model(
File
"/home/mkroening/Development/tvm/python/tvm/driver/tvmc/autotuner.py", line
472, in tune_model
trials = int(trials / len(tasks))
ZeroDivisionError: division by zero
```
### Environment
Operating System: Ubuntu 20.04.3 LTS
TVM version: ccd59e89d21cc81cc06f2a16cddcc1ffeed1e2a1
### Steps to reproduce
Create `model.onnx` with:
```python
import onnx
from onnx import helper
from onnx import TensorProto
l = 1
A = helper.make_tensor_value_info('A', TensorProto.FLOAT, [l])
B = helper.make_tensor_value_info('B', TensorProto.FLOAT, [l])
C = helper.make_tensor_value_info('C', TensorProto.FLOAT, [l])
node_def = helper.make_node(
'Add', # name
['A', 'B'], # inputs
['C'], # outputs
)
graph_def = helper.make_graph(
[node_def], # nodes
'test-model', # name
[A, B], # inputs
[C], # outputs
)
model_def = helper.make_model(graph_def)
print('The model is:\n{}'.format(model_def))
onnx.checker.check_model(model_def)
print('The model is checked!')
onnx.save(model_def, 'model.onnx')
```
Thanks a lot for your help! :)
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