---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
<timed exec> in <module>
~/run_singlecell_rapids/rapids-single-cell-examples/notebooks/coverage.py in atacworks_denoise(coverage, model, gpu, interval_size, pad)
353 input_arr = torch.tensor(input_arr, dtype=float)
354 input_arr = input_arr.unsqueeze(1)
--> 355 input_arr = input_arr.cuda(gpu, non_blocking=True).float()
356 # Run model inference
357 pred = model(input_arr)
RuntimeError: CUDA error: no kernel image is available for execution on the device
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
I tried to update the pytorch installation in the container by
Hi! I'm trying to run this notebook https://github.com/NVIDIA-Genomics-Research/rapids-single-cell-examples/blob/master/notebooks/5k_pbmc_coverage_gpu.ipynb within the container https://hub.docker.com/r/claraparabricks/single-cell-examples_rapids_cuda11.0 on A100 GPU.
Everything works until executing this line
which gives error:
I tried to update the pytorch installation in the container by
But it takes forever to solving environment. Any idea? Thanks!