Embedl-optimized
- timm/dla60x.in1k
- INT8
- RTX 2080 Ti
- Labels
- Image
- Classification
- Build
- Embedl-optimized
- Precision
- INT8
- Runtime
- TensorRT 11.3.0.99 with Embedl optimizations
- Input size
- 224×224
dla60x.in1k is an image classifier from timm. It labels an image with one of the 1,000 ImageNet classes.
Methodology
- Latency: trtexec on the NVIDIA GeForce RTX 2080 Ti: batch 1, 500 warm-up runs, then 200 timed; GPU compute is the engine's time on the GPU, without copies to and from it.
- Accuracy: the ImageNet validation set, 50,000 images, on the L4 build's INT8 engine. This page's engine is compiled from the same quantized ONNX, so its accuracy is the same up to the device's kernels, which the self-test checks.
- Self-test: during the build, on the RTX 2080 Ti: the runtime's own `embedl info`, `benchmark`, `infer` and its KServe server, and on the L4 build's example images each engine's top class must be in the other's top 3 (they matched exactly on 3 of 3).
- Build: the L4 build's quantized ONNX (Embedl Deploy, INT8 Q/DQ), compiled with TensorRT 11.3.0.99 on the device itself.