How to free up all memory pytorch is taken from gpu memory : <p>I have some kind of high level code, so model training and etc. are wrapped by <code>pipeline_network</code> class. My main goal is to train new model every new fold.</p>

<pre><code>for train_idx, valid_idx in cv.split(meta_train[DEPTH_COLUMN].values.reshape(-1)):

        meta_train_split, meta_valid_split = meta_train.iloc[train_idx], meta_train.iloc[valid_idx]

        pipeline_network = unet(config=CONFIG, suffix = 'fold' + str(fold), train_mode=True)
</code></pre>

<p>But then I move on to 2nd fold everything fails out of gpu memory:</p>

<pre><code>RuntimeError: cuda runtime error (2) : out of memory at /pytorch/torch/lib/THC/generic/THCStorage.cu:58
</code></pre>

<p>At the end of epoch I tried to manually delete that pipeline with no luck:  </p>

<pre><code> def clean_object_from_memory(obj): #definition
    del obj
    gc.collect()
    torch.cuda.empty_cache()

clean_object_from_memory( clean_object_from_memory) # calling
</code></pre>

<p>Calling this didn't help as well:</p>

<pre><code>def dump_tensors(gpu_only=True):
        torch.cuda.empty_cache()
        total_size = 0
        for obj in gc.get_objects():
            try:
                if torch.is_tensor(obj):
                    if not gpu_only or obj.is_cuda:
                        del obj
                        gc.collect()
                elif hasattr(obj, "data") and torch.is_tensor(obj.data):
                    if not gpu_only or obj.is_cuda:
                        del obj
                        gc.collect()
            except Exception as e:
                pass
</code></pre>

<p>How can reset pytorch then I move on to the next fold?</p>
