The from_onnx tutorial hosted here:
https://tvm.apache.org/docs/how_to/compile_models/from_onnx.html
Relies on a model that generate the following error using onnxruntime code:
```
from tvm.contrib.download import download_testdata
import onnxruntime as ort
model_url = "".join(
[
"https://gist.github.com/zhreshold/";,
"bcda4716699ac97ea44f791c24310193/raw/",
"93672b029103648953c4e5ad3ac3aadf346a4cdc/",
"super_resolution_0.2.onnx",
]
)
model_path = download_testdata(
model_url, "super_resolution.onnx", module="onnx"
)
ort_sess = ort.InferenceSession(model_path)
```
```
onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL
: Load model from /home/peter/.tvm_test_data/onnx/super_resolution.onnx
failed:/onnxruntime_src/onnxruntime/core/graph/model.cc:107
onnxruntime::Model::Model(onnx::ModelProto&&, const PathString&, const
IOnnxRuntimeOpSchemaRegistryList*, const onnxruntime::logging::Logger&) Missing
opset in the model. All ModelProtos MUST have at least one entry that specifies
which version of the ONNX OperatorSet is being imported.
```
Therefore the model hosted by @zhreshold should be updated or changed.
You can check the missing opset version using the following code:
```
import onnx
model_url = "".join(
[
"https://gist.github.com/zhreshold/";,
"bcda4716699ac97ea44f791c24310193/raw/",
"93672b029103648953c4e5ad3ac3aadf346a4cdc/",
"super_resolution_0.2.onnx",
]
)
model_path = download_testdata(
model_url, "super_resolution.onnx", module="onnx"
)
onnx_model = onnx.load(model_path)
print(onnx_model.opset_import)
```
This might not be an issue if the tutorial is only about the API usage but it
can be counterintuitive for someone wanting to test out tvm vs onnxruntime.
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