Open
Description
openedon May 29, 2024
behavior
The sizes parameter computed on the fly works in onnxscript eager-mode. But the converted model run by onnxruntime complains
InvalidGraph: [ONNXRuntimeError] : 10 : INVALID_GRAPH : This is an invalid model. Type Error: Type 'tensor(int64)' of input parameter (new_shape) of operator (Resize) in node (n4) is invalid.
However, according to the doc of onnx, input sizes should indeed be a tensor(int64).
code to reproduce
import numpy as np
from onnxscript import script, FLOAT, opset20 as op
@script()
def test(data: FLOAT[None, None]) -> FLOAT[None, None]:
shape = op.Shape(data)
new_shape = shape/2
print(new_shape)
return op.Resize(data, sizes=new_shape)
data = np.random.randn(16, 32).astype(np.float32)
res_onnxscript = test(data)
model = test.to_model_proto()
from onnxruntime import InferenceSession
sess = InferenceSession(model.SerializeToString())
feeds = {'data': data,}
outpus_onnxruntime = sess.run(None, feeds)Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment