mirror of
https://github.com/finegrain-ai/refiners.git
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311 lines
8 KiB
Python
311 lines
8 KiB
Python
import pytest
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import torch
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import refiners.fluxion.layers as fl
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from refiners.fluxion.context import Contexts
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class ContextChain(fl.Chain):
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def init_context(self) -> Contexts:
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return {"foo": {"bar": [42]}}
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def module_keys(chain: fl.Chain) -> list[str]:
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return list(chain._modules.keys()) # type: ignore[reportPrivateUsage]
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def test_chain_find() -> None:
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chain = fl.Chain(fl.Linear(1, 1))
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assert chain.find(fl.Linear) == chain.Linear
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assert chain.find(fl.Conv2d) is None
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def test_chain_getitem_accessor() -> None:
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chain = fl.Chain(fl.Linear(1, 1), fl.Linear(1, 1))
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assert chain["Linear_2"] == chain.Linear_2
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with pytest.raises(KeyError):
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chain["Linear_3"]
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def test_chain_find_parent():
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chain = fl.Chain(fl.Chain(fl.Linear(1, 1)))
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subchain = chain.layer("Chain", fl.Chain)
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assert chain.find_parent(subchain.layer("Linear", fl.Linear)) == subchain
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assert chain.find_parent(fl.Linear(1, 1)) is None
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def test_chain_slice() -> None:
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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.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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),
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fl.Linear(1, 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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def test_chain_walk() -> None:
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chain = fl.Chain(
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fl.Sum(
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fl.Chain(fl.Linear(1, 1)),
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fl.Linear(1, 1),
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),
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fl.Chain(),
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)
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sum_ = chain.layer("Sum", fl.Sum)
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sum_chain = sum_.layer("Chain", fl.Chain)
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assert list(chain.walk()) == [(sum_, chain), (chain.Chain, chain)]
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assert list(chain.walk(fl.Linear)) == [
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(sum_chain.Linear, sum_chain),
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(sum_.Linear, sum_),
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]
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assert list(chain.walk(recurse=True)) == [
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(sum_, chain),
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(sum_chain, sum_),
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(sum_chain.Linear, sum_chain),
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(sum_.Linear, sum_),
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(chain.Chain, chain),
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]
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def test_chain_walk_stop_iteration() -> None:
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chain = fl.Chain(
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fl.Sum(
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fl.Chain(fl.Linear(1, 1)),
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fl.Linear(1, 1),
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),
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fl.Chain(),
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fl.Linear(1, 1),
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)
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def predicate(m: fl.Module, p: fl.Chain) -> bool:
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if isinstance(m, fl.Sum):
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raise StopIteration
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return isinstance(m, fl.Linear)
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assert len(list(chain.walk(fl.Linear))) == 3
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assert len(list(chain.walk(predicate))) == 1
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def test_chain_layer() -> None:
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chain = fl.Chain(
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fl.Sum(fl.Chain(), fl.Chain()),
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)
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sum_ = chain.layer(0, fl.Sum)
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assert chain.layer("Sum", fl.Sum) == sum_
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assert chain.layer("Sum", fl.Chain) == sum_
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chain_2 = chain.layer((0, 1), fl.Chain)
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assert chain.layer((0, 1)) == chain_2
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assert chain.layer((0, "Chain_2"), fl.Chain) == chain_2
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assert chain.layer(("Sum", "Chain_2"), fl.Chain) == chain_2
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assert chain.layer((), fl.Chain) == chain
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with pytest.raises(AssertionError):
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chain.layer((0, 1), fl.Sum)
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with pytest.raises(AssertionError):
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chain.layer((), fl.Sum)
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def test_chain_layers() -> None:
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chain = fl.Chain(
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fl.Chain(fl.Chain(fl.Chain())),
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fl.Chain(),
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fl.Linear(1, 1),
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)
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assert len(list(chain.layers(fl.Chain))) == 2
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assert len(list(chain.layers(fl.Chain, recurse=True))) == 4
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def test_chain_insert() -> None:
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parent = ContextChain(fl.Linear(1, 1), fl.Linear(1, 1))
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child = fl.Chain()
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parent.insert(1, child)
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assert module_keys(parent) == ["Linear_1", "Chain", "Linear_2"]
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assert child.parent == parent
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assert child.provider.get_context("foo") == {"bar": [42]}
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def test_chain_insert_negative() -> None:
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parent = fl.Chain(fl.Linear(1, 1), fl.Linear(1, 1))
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child = fl.Chain()
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parent.insert(-2, child)
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assert module_keys(parent) == ["Linear_1", "Chain", "Linear_2"]
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def test_chain_insert_after_type() -> None:
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child = fl.Chain()
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parent_1 = fl.Chain(fl.Linear(1, 1), fl.Linear(1, 1))
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parent_1.insert_after_type(fl.Linear, child)
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assert module_keys(parent_1) == ["Linear_1", "Chain", "Linear_2"]
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parent_2 = fl.Chain(fl.Conv2d(1, 1, 1), fl.Linear(1, 1))
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parent_2.insert_after_type(fl.Linear, child)
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assert module_keys(parent_2) == ["Conv2d", "Linear", "Chain"]
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def test_chain_insert_before_type() -> None:
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child = fl.Chain()
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parent_1 = fl.Chain(fl.Linear(1, 1), fl.Linear(1, 1))
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parent_1.insert_before_type(fl.Linear, child)
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assert module_keys(parent_1) == ["Chain", "Linear_1", "Linear_2"]
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parent_2 = fl.Chain(fl.Conv2d(1, 1, 1), fl.Linear(1, 1))
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parent_2.insert_before_type(fl.Linear, child)
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assert module_keys(parent_2) == ["Conv2d", "Chain", "Linear"]
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def test_chain_insert_overflow() -> None:
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# This behaves as insert() in lists in Python.
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child = fl.Chain()
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parent_1 = fl.Chain(fl.Linear(1, 1), fl.Linear(1, 1))
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parent_1.insert(42, child)
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assert module_keys(parent_1) == ["Linear_1", "Linear_2", "Chain"]
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parent_2 = fl.Chain(fl.Linear(1, 1), fl.Linear(1, 1))
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parent_2.insert(-42, child)
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assert module_keys(parent_2) == ["Chain", "Linear_1", "Linear_2"]
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def test_chain_append() -> None:
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child = fl.Chain()
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parent = fl.Chain(fl.Linear(1, 1), fl.Linear(1, 1))
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parent.append(child)
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assert module_keys(parent) == ["Linear_1", "Linear_2", "Chain"]
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def test_chain_pop() -> None:
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chain = fl.Chain(fl.Linear(1, 1), fl.Conv2d(1, 1, 1), fl.Chain())
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with pytest.raises(IndexError):
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chain.pop(3)
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with pytest.raises(IndexError):
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chain.pop(-4)
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assert module_keys(chain) == ["Linear", "Conv2d", "Chain"]
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chain.pop(1)
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assert module_keys(chain) == ["Linear", "Chain"]
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chain.pop(-2)
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assert module_keys(chain) == ["Chain"]
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def test_chain_remove() -> None:
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child = fl.Linear(1, 1)
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parent = fl.Chain(
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fl.Linear(1, 1),
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child,
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fl.Chain(fl.Linear(1, 1), fl.Linear(1, 1)),
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)
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assert child in parent
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assert module_keys(parent) == ["Linear_1", "Linear_2", "Chain"]
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parent.remove(child)
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assert child not in parent
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assert module_keys(parent) == ["Linear", "Chain"]
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def test_chain_replace() -> None:
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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(fl.Linear(1, 1), fl.Linear(1, 1)),
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)
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subchain = chain.layer("Chain", fl.Chain)
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assert isinstance(subchain[1], fl.Linear)
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subchain.replace(subchain[1], fl.Conv2d(1, 1, 1))
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assert len(chain) == 3
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assert isinstance(subchain[1], fl.Conv2d)
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def test_chain_structural_copy() -> None:
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m = fl.Chain(
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fl.Sum(
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fl.Linear(4, 8),
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fl.Linear(4, 8),
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),
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fl.Linear(8, 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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m_sum = m.layer("Sum", fl.Sum)
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m2_sum = m2.layer("Sum", fl.Sum)
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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_setattr_dont_register() -> None:
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chain = fl.Chain(fl.Linear(in_features=1, out_features=1), fl.Linear(in_features=1, out_features=1))
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with pytest.raises(expected_exception=ValueError):
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chain.foo = fl.Linear(in_features=1, out_features=1)
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assert module_keys(chain=chain) == ["Linear_1", "Linear_2"]
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EXPECTED_TREE = """
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(CHAIN)
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├── Linear(in_features=1, out_features=1, device=cpu, dtype=float32) (x2)
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└── (CHAIN)
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├── Linear(in_features=1, out_features=1, device=cpu, dtype=float32) #1
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└── Linear(in_features=2, out_features=1, device=cpu, dtype=float32) #2
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""".strip()
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def test_debug_print() -> None:
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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(fl.Linear(1, 1), fl.Linear(2, 1)),
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)
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assert chain._show_error_in_tree("Chain.Linear_2") == EXPECTED_TREE # type: ignore[reportPrivateUsage]
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