Image classification models don't support batching, batch size fixed at 1
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Description
For example, if I look at the resnet50 model I see an input shape like this: [ 1, 3, 224, 224 ].
Why is the batch dimension fixed at 1 instead of being -1? Batching often provides large speedups when running these models so by limiting these examples to batch-size 1 you are not showing off the performance potential of ONNX (and runtimes like ONNXRuntime). Is it possible to regenerate or modify the existing models so that they support batching?
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Research direction
Start by inspecting the existing image classification models, including ResNet-50, and checking their input shapes in ONNXRuntime. Determine which models use a fixed batch dimension and what changes are needed for variable batching. Done means the relevant models accept batch sizes greater than one and their batching behavior is demonstrated.
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Assessment
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100