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Much Higher inference time using converted onnx model
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Question
I am converting tensorflow 1.14 trained tensorflow object detection model to onnx and running inference.
I am using tensorflow/tensorflow:1.14.0-gpu-py3 docker image.
using onnxruntime-gpu==1.1 or latest, in both I am getting 5x higher inference time than frozen_graph.pb.
Actuallly onnxruntime using cpu instead of Gpu. is this because of wrong onnxruntime-gpu version?
if yes, then which onnx version should I install? I already tested with 1.1 and latest release.
Further information
- Is this issue related to a specific model?
Model name: tensorflow1 object detection model
Model opset: 13
Notes
Could you please open an issue in onnxruntime repo for a suggestion about inference performance?