import torch
>>> torch.cuda.device_count()
5
>>> torch.tensor([1], device='cuda:0')
tensor([1], device='cuda:0')
>>> torch.tensor([1], device='cuda:1')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
RuntimeError: CUDA error: uncorrectable ECC error encountered
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
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.
>>> torch.tensor([1], device='cuda:2')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
RuntimeError: CUDA error: uncorrectable ECC error encountered
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
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.
>>> torch.tensor([1], device='cuda:3')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
RuntimeError: CUDA error: uncorrectable ECC error encountered
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
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.
>>> torch.tensor([1], device='cuda:4')
tensor([1], device='cuda:4')