timm_efficientdet: benchmark coverage for custom devices #2374
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Works for Roadmap #1293 to increase benchmark coverage.
This model implementation is hard-code with CUDA due to the 3rd-party repo dependency which makes that running on the custom devices except for CUDA(e.g. XPU) will raise the runtime error.
In this PR, we accept the device arg as a parameter within the training and inference processes, which will cover the model initializing and data transposition for these custom devices.