use torch.cuda.mem_get_info() instead of nvidia-smi to get free mem gpu #132
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Use torch instead of nvidia-smi to get free mem gpu
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This function queries the available GPUs on the system and determines which one has
the highest amount of free memory. It uses PyTorch's CUDA APIs instead of nvidia-smi,
ensuring better compatibility with the rest of the code and reliability when
environment variables like CUDA_VISIBLE_DEVICES are used.
Using nvidia-smi together with CUDA_VISIBLE_DEVICES can lead to errors like this:
torch._C._cuda_setDevice(device)
RuntimeError: CUDA error: invalid device ordinal
because nvidia-smi shows all GPUs visible to the system, while CUDA_VISIBLE_DEVICES only limits the GPUs visible at the CUDA API level.