Error - Some tactics do not have sufficient workspace memory to run

This is the exact error that I am getting. For workspace size, I have tried 8000, 3000, 4718592000, and 1000000000 -

$ sudo ./tlt-converter -k cXQ2bXFpNzN1bnQzNGhpZnR0b2ExNGs4dXI6ZWRiZGIyMzQtZmYyZS00ZmMwLTk4NTItOGZhMjMzZDc1OTM1 -d 3,720,1280 -o output_bbox/BiasAdd,output_cov/Sigmoid -i nchw -m 64 -t int8 -e ~/resnet18_detector.trt -c ~/calibration.bin ~/resnet18_detector.etlt -w 1000000000
[INFO] Reading Calibration Cache for calibrator: EntropyCalibration2
[INFO] Generated calibration scales using calibration cache. Make sure that calibration cache has latest scales.
[INFO] To regenerate calibration cache, please delete the existing one. TensorRT will generate a new calibration cache.
[INFO] --------------- Layers running on DLA:
[INFO] --------------- Layers running on GPU:
[INFO] conv1/convolution + activation_1/Relu, block_1a_conv_1/convolution + block_1a_relu_1/Relu, block_1a_conv_2/convolution, block_1a_conv_shortcut/convolution + add_1/add + block_1a_relu/Relu, block_1b_conv_1/convolution + block_1b_relu_1/Relu, block_1b_conv_2/convolution + add_2/add + block_1b_relu/Relu, block_2a_conv_1/convolution + block_2a_relu_1/Relu, block_2a_conv_2/convolution, block_2a_conv_shortcut/convolution + add_3/add + block_2a_relu/Relu, block_2b_conv_1/convolution + block_2b_relu_1/Relu, block_2b_conv_2/convolution + add_4/add + block_2b_relu/Relu, block_3a_conv_1/convolution + block_3a_relu_1/Relu, block_3a_conv_2/convolution, block_3a_conv_shortcut/convolution + add_5/add + block_3a_relu/Relu, block_3b_conv_1/convolution + block_3b_relu_1/Relu, block_3b_conv_2/convolution + add_6/add + block_3b_relu/Relu, block_4a_conv_1/convolution + block_4a_relu_1/Relu, block_4a_conv_2/convolution, block_4a_conv_shortcut/convolution + add_7/add + block_4a_relu/Relu, block_4b_conv_1/convolution + block_4b_relu_1/Relu, block_4b_conv_2/convolution + add_8/add + block_4b_relu/Relu, output_cov/convolution, output_cov/Sigmoid, output_bbox/convolution,
[INFO] Some tactics do not have sufficient workspace memory to run. Increasing workspace size may increase performance, please check verbose output.

I referenced these posts, but for some reason I am still getting the error-



Device I am working with is Xavier NX
Jetpack 4.4
Deepstream 5.0
Swapfile increased by 8GB set per this instruction (total of 12GB) - Creating a Swap file
And I am trying to follow this - Deploying to Deepstream — Transfer Learning Toolkit 2.0 documentation

If I am missing something here, I would appreciate any pointer.

Thank you,

solved by lowering the batch size