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cargo +nightly fmt #1017

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merged 17 commits into from
Dec 12, 2023
Merged

cargo +nightly fmt #1017

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9c8a40c
`cargo +nightly fmt --all --check` passes
AlexErrant Nov 28, 2023
d864317
switch between `max_width = 200` and `max_width = 100`
AlexErrant Nov 29, 2023
09abe77
Merge remote-tracking branch 'origin/main' into fmt_100
AlexErrant Nov 29, 2023
8c518cf
format_strings = true
AlexErrant Nov 29, 2023
58062bb
CI
AlexErrant Nov 29, 2023
2f06c02
whoops
AlexErrant Nov 29, 2023
b92c2c9
maybe?
AlexErrant Nov 29, 2023
5759aa9
maybe??
AlexErrant Nov 29, 2023
f06a892
Merge branch 'main' into fmt_100
AlexErrant Nov 30, 2023
ca31f5a
fix conflicts
AlexErrant Nov 30, 2023
06a49ea
pin to nightly-2023-11-05
AlexErrant Nov 30, 2023
8558f4a
Merge branch 'main' into fmt_100
AlexErrant Nov 30, 2023
0d8f213
fix conflicts
AlexErrant Nov 30, 2023
4111405
revert nightly
AlexErrant Nov 30, 2023
51076ac
Merge branch 'main' into fmt_100
AlexErrant Dec 9, 2023
5f9ee26
back to normal
AlexErrant Dec 9, 2023
3072806
drop #[rustfmt::skip]
AlexErrant Dec 9, 2023
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7 changes: 4 additions & 3 deletions burn-autodiff/src/graph/traversal.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -16,9 +16,10 @@ impl BreadthFirstSearch {
let mut visited = HashSet::with_capacity(root.order);
let mut parents = Vec::with_capacity(root.order);
let mut steps = graph.steps();
let root_step = steps
.remove(&root.id)
.expect("Root node should have a step registered, did you forget to call `Tensor::register_grad` on the tensor where you need gradients?");
let root_step = steps.remove(&root.id).expect(
"Root node should have a step registered, did you forget to call \
`Tensor::register_grad` on the tensor where you need gradients?",
);

visited.insert(root.id.clone());
parents.append(&mut root.parents.clone());
Expand Down
324 changes: 154 additions & 170 deletions burn-autodiff/src/ops/module.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -103,49 +103,45 @@ impl<B: Backend> ModuleOps<Autodiff<B>> for Autodiff<B> {
}

match bias {
Some(bias) => {
match Conv2DWithBias
.prepare(
[x.node, weight.node, bias.node],
[x.graph, weight.graph, bias.graph],
)
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
bias.primitive.clone(),
options.clone(),
),
B::conv2d(x.primitive, weight.primitive, Some(bias.primitive), options),
Some(bias) => match Conv2DWithBias
.prepare(
[x.node, weight.node, bias.node],
[x.graph, weight.graph, bias.graph],
)
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
bias.primitive.clone(),
options.clone(),
),
OpsKind::UnTracked(prep) => prep.finish(B::conv2d(
x.primitive,
weight.primitive,
Some(bias.primitive),
options,
)),
}
}
None => {
match Conv2DNoBias
.prepare([x.node, weight.node], [x.graph, weight.graph])
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
options.clone(),
),
B::conv2d(x.primitive, weight.primitive, None, options),
B::conv2d(x.primitive, weight.primitive, Some(bias.primitive), options),
),
OpsKind::UnTracked(prep) => prep.finish(B::conv2d(
x.primitive,
weight.primitive,
Some(bias.primitive),
options,
)),
},
None => match Conv2DNoBias
.prepare([x.node, weight.node], [x.graph, weight.graph])
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
options.clone(),
),
OpsKind::UnTracked(prep) => {
prep.finish(B::conv2d(x.primitive, weight.primitive, None, options))
}
B::conv2d(x.primitive, weight.primitive, None, options),
),
OpsKind::UnTracked(prep) => {
prep.finish(B::conv2d(x.primitive, weight.primitive, None, options))
}
}
},
}
}

Expand Down Expand Up @@ -211,57 +207,53 @@ impl<B: Backend> ModuleOps<Autodiff<B>> for Autodiff<B> {
}

match bias {
Some(bias) => {
match ConvTranspose2DWithBias
.prepare(
[x.node, weight.node, bias.node],
[x.graph, weight.graph, bias.graph],
)
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
bias.primitive.clone(),
options.clone(),
),
B::conv_transpose2d(
x.primitive,
weight.primitive,
Some(bias.primitive),
options,
),
Some(bias) => match ConvTranspose2DWithBias
.prepare(
[x.node, weight.node, bias.node],
[x.graph, weight.graph, bias.graph],
)
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
bias.primitive.clone(),
options.clone(),
),
OpsKind::UnTracked(prep) => prep.finish(B::conv_transpose2d(
B::conv_transpose2d(
x.primitive,
weight.primitive,
Some(bias.primitive),
options,
)),
}
}
None => {
match ConvTranspose2DNoBias
.prepare([x.node, weight.node], [x.graph, weight.graph])
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
options.clone(),
),
B::conv_transpose2d(x.primitive, weight.primitive, None, options),
),
OpsKind::UnTracked(prep) => prep.finish(B::conv_transpose2d(
x.primitive,
weight.primitive,
None,
options,
)),
}
}
),
OpsKind::UnTracked(prep) => prep.finish(B::conv_transpose2d(
x.primitive,
weight.primitive,
Some(bias.primitive),
options,
)),
},
None => match ConvTranspose2DNoBias
.prepare([x.node, weight.node], [x.graph, weight.graph])
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
options.clone(),
),
B::conv_transpose2d(x.primitive, weight.primitive, None, options),
),
OpsKind::UnTracked(prep) => prep.finish(B::conv_transpose2d(
x.primitive,
weight.primitive,
None,
options,
)),
},
}
}

Expand Down Expand Up @@ -322,49 +314,45 @@ impl<B: Backend> ModuleOps<Autodiff<B>> for Autodiff<B> {
}
}
match bias {
Some(bias) => {
match Conv1DWithBias
.prepare(
[x.node, weight.node, bias.node],
[x.graph, weight.graph, bias.graph],
)
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
bias.primitive.clone(),
options.clone(),
),
B::conv1d(x.primitive, weight.primitive, Some(bias.primitive), options),
Some(bias) => match Conv1DWithBias
.prepare(
[x.node, weight.node, bias.node],
[x.graph, weight.graph, bias.graph],
)
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
bias.primitive.clone(),
options.clone(),
),
OpsKind::UnTracked(prep) => prep.finish(B::conv1d(
x.primitive,
weight.primitive,
Some(bias.primitive),
options,
)),
}
}
None => {
match Conv1DNoBias
.prepare([x.node, weight.node], [x.graph, weight.graph])
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
options.clone(),
),
B::conv1d(x.primitive, weight.primitive, None, options),
B::conv1d(x.primitive, weight.primitive, Some(bias.primitive), options),
),
OpsKind::UnTracked(prep) => prep.finish(B::conv1d(
x.primitive,
weight.primitive,
Some(bias.primitive),
options,
)),
},
None => match Conv1DNoBias
.prepare([x.node, weight.node], [x.graph, weight.graph])
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
options.clone(),
),
OpsKind::UnTracked(prep) => {
prep.finish(B::conv1d(x.primitive, weight.primitive, None, options))
}
B::conv1d(x.primitive, weight.primitive, None, options),
),
OpsKind::UnTracked(prep) => {
prep.finish(B::conv1d(x.primitive, weight.primitive, None, options))
}
}
},
}
}

Expand Down Expand Up @@ -430,57 +418,53 @@ impl<B: Backend> ModuleOps<Autodiff<B>> for Autodiff<B> {
}

match bias {
Some(bias) => {
match ConvTranspose1DWithBias
.prepare(
[x.node, weight.node, bias.node],
[x.graph, weight.graph, bias.graph],
)
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
bias.primitive.clone(),
options.clone(),
),
B::conv_transpose1d(
x.primitive,
weight.primitive,
Some(bias.primitive),
options,
),
Some(bias) => match ConvTranspose1DWithBias
.prepare(
[x.node, weight.node, bias.node],
[x.graph, weight.graph, bias.graph],
)
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
bias.primitive.clone(),
options.clone(),
),
OpsKind::UnTracked(prep) => prep.finish(B::conv_transpose1d(
B::conv_transpose1d(
x.primitive,
weight.primitive,
Some(bias.primitive),
options,
)),
}
}
None => {
match ConvTranspose1DNoBias
.prepare([x.node, weight.node], [x.graph, weight.graph])
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
options.clone(),
),
B::conv_transpose1d(x.primitive, weight.primitive, None, options),
),
OpsKind::UnTracked(prep) => prep.finish(B::conv_transpose1d(
x.primitive,
weight.primitive,
None,
options,
)),
}
}
),
OpsKind::UnTracked(prep) => prep.finish(B::conv_transpose1d(
x.primitive,
weight.primitive,
Some(bias.primitive),
options,
)),
},
None => match ConvTranspose1DNoBias
.prepare([x.node, weight.node], [x.graph, weight.graph])
.stateful()
{
OpsKind::Tracked(prep) => prep.finish(
(
x.primitive.clone(),
weight.primitive.clone(),
options.clone(),
),
B::conv_transpose1d(x.primitive, weight.primitive, None, options),
),
OpsKind::UnTracked(prep) => prep.finish(B::conv_transpose1d(
x.primitive,
weight.primitive,
None,
options,
)),
},
}
}

Expand Down
5 changes: 4 additions & 1 deletion burn-core/src/nn/conv/checks.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,9 @@ pub(crate) fn checks_channels_div_groups(channels_in: usize, channels_out: usize
let channels_out_div_by_group = channels_out % groups == 0;

if !channels_in_div_by_group && !channels_out_div_by_group {
panic!("Both channels must be divisible by the number of groups. Got channels_in={channels_in}, channels_out={channels_out}, groups={groups}");
panic!(
"Both channels must be divisible by the number of groups. Got \
channels_in={channels_in}, channels_out={channels_out}, groups={groups}"
);
}
}
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