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87 lines
2.1 KiB
Python
87 lines
2.1 KiB
Python
import torch
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import refiners.fluxion.layers as fl
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def test_chain_remove_replace():
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chain = fl.Chain(
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fl.Linear(1, 1),
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fl.Linear(1, 1),
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fl.Chain(
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fl.Linear(1, 1),
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fl.Linear(1, 1),
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fl.Chain(fl.Linear(1, 1), fl.Linear(1, 1)),
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),
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fl.Conv2d(1, 1, 1),
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)
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assert len(chain) == 4
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assert len(chain.Chain) == 3
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chain.remove(chain[-1])
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assert len(chain) == 3
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assert len(chain.Chain) == 3
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assert isinstance(chain.Chain.Chain[1], fl.Linear)
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chain.Chain.Chain.replace(chain.Chain.Chain[1], fl.Conv2d(1, 1, 1))
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assert len(chain) == 3
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assert len(chain.Chain) == 3
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assert isinstance(chain.Chain.Chain[1], fl.Conv2d)
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def test_chain_structural_copy():
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m = fl.Chain(
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fl.Sum(
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fl.Linear(in_features=4, out_features=8),
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fl.Linear(in_features=4, out_features=8),
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),
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fl.Linear(in_features=8, out_features=12),
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)
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x = torch.randn(7, 4)
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y = m(x)
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assert y.shape == (7, 12)
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m2 = m.structural_copy()
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assert m.Linear == m2.Linear
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assert m.Sum.Linear_1 == m2.Sum.Linear_1
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assert m.Sum.Linear_2 == m2.Sum.Linear_2
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assert m.Sum != m2.Sum
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assert m != m2
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assert m.Sum.parent == m
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assert m2.Sum.parent == m2
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y2 = m2(x)
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assert y2.shape == (7, 12)
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torch.equal(y2, y)
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def test_chain_find():
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chain = fl.Chain(
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fl.Linear(1, 1),
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)
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assert isinstance(chain.find(fl.Linear), fl.Linear)
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assert chain.find(fl.Conv2d) is None
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def test_chain_slice() -> None:
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chain = fl.Chain(
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fl.Linear(in_features=1, out_features=1),
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fl.Linear(in_features=1, out_features=1),
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fl.Linear(in_features=1, out_features=1),
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fl.Chain(
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fl.Linear(in_features=1, out_features=1),
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fl.Linear(in_features=1, out_features=1),
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),
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fl.Linear(in_features=1, out_features=1),
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)
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x = torch.randn(1, 1)
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sliced_chain = chain[1:4]
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assert len(chain) == 5
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assert len(sliced_chain) == 3
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assert chain[:-1](x).shape == (1, 1)
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