when i tested some images by the code， the usage is getting bigger。 I find the problem is caused by the line code（features = self(x)）：
def test_step(self, batch, batch_idx): # Nearest Neighbour Search
self.embedding_coreset = pickle.load(open(os.path.join(self.embedding_dir_path, 'embedding.pickle'), 'rb'))
x, gt, label, file_name, x_type = batch
extract embedding
features = self(x)
embeddings = []
for feature in features:
m = torch.nn.AvgPool2d(3, 1, 1)
embeddings.append(m(feature))
I used torch.no_gard() and torch.cuda.empty_cache(), but it is unuseful. why?
when i tested some images by the code， the usage is getting bigger。 I find the problem is caused by the line code（features = self(x)）： def test_step(self, batch, batch_idx): # Nearest Neighbour Search self.embedding_coreset = pickle.load(open(os.path.join(self.embedding_dir_path, 'embedding.pickle'), 'rb')) x, gt, label, file_name, x_type = batch
extract embedding
I used torch.no_gard() and torch.cuda.empty_cache(), but it is unuseful. why?