Lower FPS compared to the unpruned model for the pruned MaskRCNN model

Please use mask2former as mentioned in TAO5.5. mask2former - NVIDIA Docs.
You can get started with notebook or TAO user guide.
It has higher accuracy. Also some fps can be found in Mask2Former | NVIDIA NGC. You can train a model and run test.
For mask_rcnn, you can check if smaller backbone can help.

I cannot find the input size used for testing the inference FPS of the model for mask2former Mask2Former | NVIDIA NGC.
For mask_rcnn I already tested with ‘resnet18’ backbone, the accuracy is comparable to ‘resnet50’ but surprisingly the FPS was lower for the ‘resnet18’ model, the model training was done on tao3.22.05, I will run the training on the tao5.x container and check the results.

It is 800x800. You can find this info after checking the onnx file with Netron.

Yes, please have a try on tao5.x.
BTW, if you have bandwidth, you can run some benchmark against the tensort engine to profile the cost time of each layer, such as RoIAlign, etc.

can you guide me to any resource where I can learn to use this.

You can refer to utility tools – TREx, TensorRT engine explorer for profiling analysis
1)Exploring NVIDIA TensorRT Engines with TREx | NVIDIA Technical Blog,
2)TensorRT/tools/experimental/trt-engine-explorer at main · NVIDIA/TensorRT · GitHub.

or Performance profiling / analysis / debugging
Nsight Systems (application-level)
Nsight Compute (kernel-level)