'How to clean garbage from CUDA in Pytorch?

I teached my neural nets and realized that even after torch.cuda.empty_cache() and gc.collect() my cuda-device memory is filled. In Colab Notebooks we can see the current variables in memory, but even I delete every variable and clean the garbage gpu-memory is busy. I heard it's because python garbage collector can't work on cuda-device. Please explain me, what should I do?

Solution 1:^[1]

For me I have to delete the model before emptying the cache:

del model
gc.collect()
torch.cuda.empty_cache()

then you can check memory is freed using 'nvidia-smi'.

Solution 2:^[2]

You can do this:

import gc
import torch
gc.collect()
torch.cuda.empty_cache()

Sources

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Source: Stack Overflow

Solution	Source
Solution 1	DvdG
Solution 2	razimbres

'How to clean garbage from CUDA in Pytorch?

Solution 1:[1]

Solution 2:[2]

Sources

Related Questions

Solution 1:^[1]

Solution 2:^[2]