TensorRT 2:4 sparsity is not applied with Q/DQ quantization

I’m testing INT8 quantization using ASP 2:4 sparse model.

• Case A: Export sparse FP32 ONNX without QuantizeLinear/DequantizeLinear(Q/DQ) and build INT8 model using Polygraphy (with sparsity enabled).
  -> TensorRT layer info indicates sparsity-enabled tactics/kernels are selected for some layers.

• Case B: Starting from the same sparse model, export an ONNX with Q/DQ using pytorch-quantization and build with: trtexec --int8 --sparsity=enable
  -> Layer info still shows HasSparseWeights=1 for some layers, but sparsity-enabled tactics/kernels do not appear to be selected.

Question:
Is this difference between no Q/DQ ONNX vs Q/DQ ONNX expected for 2:4 sparsity?
If not, are there recommended export/build settings for Q/DQ ONNX to enable sparsity tactics ?

Environment: Jetson (JetPack 6.1.2 / TensorRT 8.6.1)

Start by reproducing Case A and Case B with the stated JetPack 6.1.2 and TensorRT 8.6.1 environment, using Polygraphy for the sparse FP32 ONNX model and trtexec --int8 --sparsity=enable for the Q/DQ model. Compare the layer information and selected tactics; the issue is resolved when the expected relationship between Q/DQ quantization and 2:4 sparsity tactics, or the required export/build settings, is established.