Making large AI models cheaper, faster and more accessible
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import torch
import torch.nn as nn
from colossalai.shardformer.shard.utils import set_tensors_to_none
class Net(nn.Module):
def __init__(self) -> None:
super().__init__()
self.layers = nn.Sequential(nn.Linear(1, 2), nn.Linear(2, 3))
self.out = nn.Linear(3, 1)
def test_release_layer():
orig_cuda_allocated = torch.cuda.memory_allocated()
model = Net().cuda()
set_tensors_to_none(model, exclude={model.layers[0]})
assert model.layers[1].weight is None
assert model.layers[1].bias is None
assert model.out.weight is None
assert model.out.bias is None
set_tensors_to_none(model)
assert model.layers[0].weight is None
assert model.layers[0].bias is None
assert len(list(model.parameters())) == 0
assert torch.cuda.memory_allocated() == orig_cuda_allocated