Hi,
We check this issue with tensorflow-2.5.0+nv21.8 on both Nano and Xavier.
The sample can work well on Xavier but meet an “too many resources requested for launch” error on Nano.
Do you also observe the same error as below?
2021-09-07 10:45:22.596081: F tensorflow/core/kernels/roll_op_gpu.cu.cc:84] Non-OK-status: GpuLaunchKernel(RollKernel<T>, cfg.block_count, cfg.thread_per_block, 0, d.stream(), cfg.virtual_thread_count, num_dims, input, output, reinterpret_cast<const int32*>(dim_buf), reinterpret_cast<const int32*>(thres_buf), reinterpret_cast<const int64*>(range_buf)) status: Internal: too many resources requested for launch
If yes, this is a known issue and we are still working on this.
You can find more details in the below topic:
Thanks.