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fix: fix transpose empty iterable with zip(*nested) in transformations #145

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Merged
merged 10 commits into from
Mar 7, 2023
Merged

fix: fix transpose empty iterable with zip(*nested) in transformations #145

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6e1fa56
fix: fix transpose empty iterable with `zip(*nested)`
XuehaiPan Mar 3, 2023
fc02c54
test: add test for empty parameters
XuehaiPan Mar 3, 2023
95af6b1
style: use postional-only arguments
XuehaiPan Mar 3, 2023
e0c41cf
docs(CHANGELOG): update CHANGELOG.md
XuehaiPan Mar 3, 2023
fd1642c
test: add test for empty parameters
XuehaiPan Mar 3, 2023
f3d86ee
test: add more tests
XuehaiPan Mar 3, 2023
f450638
test: add more tests
XuehaiPan Mar 3, 2023
5ae44b5
chore: update codecov.yaml
XuehaiPan Mar 3, 2023
c014379
test: fix tests
XuehaiPan Mar 4, 2023
de6b176
lint: appease linters
XuehaiPan Mar 7, 2023
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style: use postional-only arguments
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@XuehaiPan
XuehaiPan committed Mar 3, 2023
commit 95af6b1e079630cdae8ce14fe19a95d4afcffa89
35 changes: 19 additions & 16 deletions torchopt/diff/implicit/nn/module.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,38 +36,40 @@


def _stateless_objective_fn(
__flat_params: TupleOfTensors,
__flat_meta_params: TupleOfTensors,
__params_names: Iterable[str],
__meta_params_names: Iterable[str],
flat_params: TupleOfTensors,
flat_meta_params: TupleOfTensors,
params_names: Iterable[str],
meta_params_names: Iterable[str],
self: ImplicitMetaGradientModule,
/,
*input: Any,
**kwargs: Any,
) -> torch.Tensor:
with reparametrize(
self,
itertools.chain(
zip(__params_names, __flat_params),
zip(__meta_params_names, __flat_meta_params),
zip(params_names, flat_params),
zip(meta_params_names, flat_meta_params),
),
):
return self.objective(*input, **kwargs)


def _stateless_optimality_fn(
__flat_params: TupleOfTensors,
__flat_meta_params: TupleOfTensors,
__params_names: Iterable[str],
__meta_params_names: Iterable[str],
flat_params: TupleOfTensors,
flat_meta_params: TupleOfTensors,
params_names: Iterable[str],
meta_params_names: Iterable[str],
self: ImplicitMetaGradientModule,
/,
*input: Any,
**kwargs: Any,
) -> TupleOfTensors:
with reparametrize(
self,
itertools.chain(
zip(__params_names, __flat_params),
zip(__meta_params_names, __flat_meta_params),
zip(params_names, flat_params),
zip(meta_params_names, flat_meta_params),
),
):
return self.optimality(*input, **kwargs)
Expand Down Expand Up @@ -121,12 +123,13 @@ def enable_implicit_gradients(
@custom_root(_stateless_optimality_fn, argnums=1, has_aux=True, **solve_kwargs)
def stateless_solver_fn(
# pylint: disable=unused-argument
__flat_params: TupleOfTensors,
__flat_meta_params: TupleOfTensors,
__params_names: Iterable[str],
__meta_params_names: Iterable[str],
flat_params: TupleOfTensors,
flat_meta_params: TupleOfTensors,
params_names: Iterable[str],
meta_params_names: Iterable[str],
# pylint: enable=unused-argument
self: ImplicitMetaGradientModule,
/,
*input: Any,
**kwargs: Any,
) -> tuple[TupleOfTensors, Any]:
Expand Down
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