Hello,
I reported your issue to OpenVINO developers. In the meantime, I can suggest a few workarounds:
a) retrying with OpenVINO 2025.0
b) using ONNX runtime until a permanent fix is found
import onnxruntime as ort
# Load the ONNX model
model_path = "owlv2-base-patch16-finetuned.onnx"
session = ort.InferenceSession(model_path)
# Prepare input data
input_name = session.get_inputs()[0].name
input_shape = session.get_inputs()[0].shape
input_data = ... # Replace with your input data as a numpy array
# Run inference
outputs = session.run(None, {input_name: input_data})
print(outputs)
c) Einsum replacement with MathMul or ReduceSum
import onnx
from onnx import helper
# Load the ONNX model
model_path = "owlv2-base-patch16-finetuned.onnx"
model = onnx.load(model_path)
# Find the Einsum node
einsum_node = next(node for node in model.graph.node if node.op_type == "Einsum")
# Replace the Einsum node with supported operations
# Example: Replace with MatMul and ReduceSum (this is just a placeholder; you need to implement the actual logic)
new_node_1 = helper.make_node(
'MatMul',
einsum_node.input,
['intermediate_output'],
name=einsum_node.name + '_matmul'
)
new_node_2 = helper.make_node(
'ReduceSum',
['intermediate_output'],
einsum_node.output,
name=einsum_node.name + '_reduce_sum'
)
# Remove the old Einsum node and add the new nodes
model.graph.node.remove(einsum_node)
model.graph.node.extend([new_node_1, new_node_2])
# Save the modified model
modified_model_path = "owlv2-base-patch16-finetuned_modified.onnx"
onnx.save(model, modified_model_path)
d) conversion with Model Optimizer
mo --input_model owlv2-base-patch16-finetuned.onnx
You're welcome to try one or more of those and let us know if it has worked for you.
