Skip to content

Repeat operation #2090

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 17 commits into from
Aug 3, 2024
Merged

Repeat operation #2090

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
17 commits
Select commit Hold shift + click to select a range
a549dfb
renaming repeat to repeat_dim
mepatrick73 Jul 31, 2024
7de6351
implementing repeat function
mepatrick73 Jul 31, 2024
2515cc7
renaming repeat files to repeat_dim
mepatrick73 Jul 31, 2024
54ebece
renaming part 2
mepatrick73 Jul 31, 2024
b109b8a
renaming part 3
mepatrick73 Jul 31, 2024
a29f288
renaming part 4
mepatrick73 Jul 31, 2024
fb6a517
renaming part 5
mepatrick73 Jul 31, 2024
479b5cd
Merge branch 'main' into repeat-operation
mepatrick73 Jul 31, 2024
b2ca244
adding test file
mepatrick73 Jul 31, 2024
8e33609
adding unit test
mepatrick73 Aug 1, 2024
61e990a
Merge branch 'main' into repeat-operation
mepatrick73 Aug 1, 2024
0c417f6
adding rust book documentation
mepatrick73 Aug 2, 2024
0c9f81d
adding function args doc
mepatrick73 Aug 2, 2024
2dfd870
fixing tests
mepatrick73 Aug 2, 2024
64371e1
Merge branch 'main' into repeat-operation
mepatrick73 Aug 2, 2024
6ffbb89
changing repeat api to match pytorch equivalent
mepatrick73 Aug 2, 2024
cef1084
fixing clippy error
mepatrick73 Aug 2, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
69 changes: 35 additions & 34 deletions burn-book/src/building-blocks/tensor.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -131,40 +131,41 @@ for the sake of simplicity, we ignore type signatures. For more details, refer t

Those operations are available for all tensor kinds: `Int`, `Float`, and `Bool`.

| Burn | PyTorch Equivalent |
| ------------------------------------- | ------------------------------------ |
| `Tensor::cat(tensors, dim)` | `torch.cat(tensors, dim)` |
| `Tensor::empty(shape, device)` | `torch.empty(shape, device=device)` |
| `Tensor::from_primitive(primitive)` | N/A |
| `Tensor::stack(tensors, dim)` | `torch.stack(tensors, dim)` |
| `tensor.all()` | `tensor.all()` |
| `tensor.all_dim(dim)` | `tensor.all(dim)` |
| `tensor.any()` | `tensor.any()` |
| `tensor.any_dim(dim)` | `tensor.any(dim)` |
| `tensor.chunk(num_chunks, dim)` | `tensor.chunk(num_chunks, dim)` |
| `tensor.device()` | `tensor.device` |
| `tensor.dims()` | `tensor.size()` |
| `tensor.equal(other)` | `x == y` |
| `tensor.expand(shape)` | `tensor.expand(shape)` |
| `tensor.flatten(start_dim, end_dim)` | `tensor.flatten(start_dim, end_dim)` |
| `tensor.flip(axes)` | `tensor.flip(axes)` |
| `tensor.into_data()` | N/A |
| `tensor.into_primitive()` | N/A |
| `tensor.into_scalar()` | `tensor.item()` |
| `tensor.narrow(dim, start, length)` | `tensor.narrow(dim, start, length)` |
| `tensor.not_equal(other)` | `x != y` |
| `tensor.permute(axes)` | `tensor.permute(axes)` |
| `tensor.movedim(src, dst)` | `tensor.movedim(src, dst)` |
| `tensor.repeat(2, 4)` | `tensor.repeat([1, 1, 4])` |
| `tensor.reshape(shape)` | `tensor.view(shape)` |
| `tensor.shape()` | `tensor.shape` |
| `tensor.slice(ranges)` | `tensor[(*ranges,)]` |
| `tensor.slice_assign(ranges, values)` | `tensor[(*ranges,)] = values` |
| `tensor.squeeze(dim)` | `tensor.squeeze(dim)` |
| `tensor.to_data()` | N/A |
| `tensor.to_device(device)` | `tensor.to(device)` |
| `tensor.unsqueeze()` | `tensor.unsqueeze(0)` |
| `tensor.unsqueeze_dim(dim)` | `tensor.unsqueeze(dim)` |
| Burn | PyTorch Equivalent |
| ------------------------------------- | ------------------------------------------------------------------------ |
| `Tensor::cat(tensors, dim)` | `torch.cat(tensors, dim)` |
| `Tensor::empty(shape, device)` | `torch.empty(shape, device=device)` |
| `Tensor::from_primitive(primitive)` | N/A |
| `Tensor::stack(tensors, dim)` | `torch.stack(tensors, dim)` |
| `tensor.all()` | `tensor.all()` |
| `tensor.all_dim(dim)` | `tensor.all(dim)` |
| `tensor.any()` | `tensor.any()` |
| `tensor.any_dim(dim)` | `tensor.any(dim)` |
| `tensor.chunk(num_chunks, dim)` | `tensor.chunk(num_chunks, dim)` |
| `tensor.device()` | `tensor.device` |
| `tensor.dims()` | `tensor.size()` |
| `tensor.equal(other)` | `x == y` |
| `tensor.expand(shape)` | `tensor.expand(shape)` |
| `tensor.flatten(start_dim, end_dim)` | `tensor.flatten(start_dim, end_dim)` |
| `tensor.flip(axes)` | `tensor.flip(axes)` |
| `tensor.into_data()` | N/A |
| `tensor.into_primitive()` | N/A |
| `tensor.into_scalar()` | `tensor.item()` |
| `tensor.narrow(dim, start, length)` | `tensor.narrow(dim, start, length)` |
| `tensor.not_equal(other)` | `x != y` |
| `tensor.permute(axes)` | `tensor.permute(axes)` |
| `tensor.movedim(src, dst)` | `tensor.movedim(src, dst)` |
| `tensor.repeat_dim(dim, times)` | `tensor.repeat(*[times if i == dim else 1 for i in range(tensor.dim())])`|
| `tensor.repeat(sizes)` | `tensor.repeat(sizes)` |
| `tensor.reshape(shape)` | `tensor.view(shape)` |
| `tensor.shape()` | `tensor.shape` |
| `tensor.slice(ranges)` | `tensor[(*ranges,)]` |
| `tensor.slice_assign(ranges, values)` | `tensor[(*ranges,)] = values` |
| `tensor.squeeze(dim)` | `tensor.squeeze(dim)` |
| `tensor.to_data()` | N/A |
| `tensor.to_device(device)` | `tensor.to(device)` |
| `tensor.unsqueeze()` | `tensor.unsqueeze(0)` |
| `tensor.unsqueeze_dim(dim)` | `tensor.unsqueeze(dim)` |

### Numeric Operations

Expand Down
4 changes: 2 additions & 2 deletions crates/burn-autodiff/src/ops/bool_tensor.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -132,11 +132,11 @@ impl<B: Backend, C: CheckpointStrategy> BoolTensorOps<Self> for Autodiff<B, C> {
B::bool_expand(tensor, shape)
}

fn bool_repeat<const D: usize>(
fn bool_repeat_dim<const D: usize>(
tensor: BoolTensor<B, D>,
dim: usize,
times: usize,
) -> BoolTensor<B, D> {
B::bool_repeat(tensor, dim, times)
B::bool_repeat_dim(tensor, dim, times)
}
}
4 changes: 2 additions & 2 deletions crates/burn-autodiff/src/ops/int_tensor.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -162,12 +162,12 @@ impl<B: Backend, C: CheckpointStrategy> IntTensorOps<Self> for Autodiff<B, C> {
B::int_mean_dim(tensor, dim)
}

fn int_repeat<const D: usize>(
fn int_repeat_dim<const D: usize>(
tensor: IntTensor<B, D>,
dim: usize,
times: usize,
) -> IntTensor<B, D> {
B::int_repeat(tensor, dim, times)
B::int_repeat_dim(tensor, dim, times)
}

fn int_greater<const D: usize>(lhs: IntTensor<B, D>, rhs: IntTensor<B, D>) -> BoolTensor<B, D> {
Expand Down
10 changes: 6 additions & 4 deletions crates/burn-autodiff/src/ops/tensor.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2418,7 +2418,7 @@ impl<B: Backend, C: CheckpointStrategy> FloatTensorOps<Self> for Autodiff<B, C>
B::float_argsort(tensor.primitive, dim, descending)
}

fn float_repeat<const D: usize>(
fn float_repeat_dim<const D: usize>(
tensor: FloatTensor<Self, D>,
dim: usize,
times: usize,
Expand All @@ -2437,7 +2437,7 @@ impl<B: Backend, C: CheckpointStrategy> FloatTensorOps<Self> for Autodiff<B, C>
impl<B: Backend, const D: usize> RetroForward for RetroRepeat<B, D> {
fn forward(&self, states: &mut BackwardStates, out_node: NodeID) {
let tensor = states.get_state::<B::FloatTensorPrimitive<D>>(&self.tensor_id);
let out = B::float_repeat(tensor, self.dim, self.times);
let out = B::float_repeat_dim(tensor, self.dim, self.times);
states.save(out_node, out)
}
}
Expand Down Expand Up @@ -2467,9 +2467,11 @@ impl<B: Backend, C: CheckpointStrategy> FloatTensorOps<Self> for Autodiff<B, C>
.stateful()
{
OpsKind::Tracked(prep) => {
prep.finish(dim, B::float_repeat(tensor.primitive, dim, times))
prep.finish(dim, B::float_repeat_dim(tensor.primitive, dim, times))
}
OpsKind::UnTracked(prep) => {
prep.finish(B::float_repeat_dim(tensor.primitive, dim, times))
}
OpsKind::UnTracked(prep) => prep.finish(B::float_repeat(tensor.primitive, dim, times)),
}
}

Expand Down
4 changes: 2 additions & 2 deletions crates/burn-autodiff/src/tests/mod.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,7 @@ mod permute;
mod pow;
mod recip;
mod relu;
mod repeat;
mod repeat_dim;
mod reshape;
mod select;
mod sigmoid;
Expand Down Expand Up @@ -133,6 +133,6 @@ macro_rules! testgen_all {
burn_autodiff::testgen_ad_sign!();
burn_autodiff::testgen_ad_expand!();
burn_autodiff::testgen_ad_sort!();
burn_autodiff::testgen_ad_repeat!();
burn_autodiff::testgen_ad_repeat_dim!();
};
}
4 changes: 2 additions & 2 deletions crates/burn-autodiff/src/tests/repeat.rs → crates/burn-autodiff/src/tests/repeat_dim.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
#[burn_tensor_testgen::testgen(ad_repeat)]
#[burn_tensor_testgen::testgen(ad_repeat_dim)]
mod tests {
use super::*;
use burn_tensor::{activation, TensorData};
Expand All @@ -12,7 +12,7 @@ mod tests {
let tensor_1 = TestAutodiffTensor::<2>::from_data(data_1, &device).require_grad();
let tensor_2 = TestAutodiffTensor::from_data(data_2, &device).require_grad();

let tensor_3 = tensor_2.clone().repeat(1, 3);
let tensor_3 = tensor_2.clone().repeat_dim(1, 3);

let tensor_3 = tensor_1.matmul(tensor_3);
let grads = tensor_3.backward();
Expand Down
2 changes: 1 addition & 1 deletion crates/burn-candle/src/lib.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -94,7 +94,7 @@ mod tests {
// burn_tensor::testgen_powf!();

burn_tensor::testgen_random!();
burn_tensor::testgen_repeat!();
burn_tensor::testgen_repeat_dim!();
burn_tensor::testgen_reshape!();
burn_tensor::testgen_select!();
burn_tensor::testgen_sin!();
Expand Down
2 changes: 1 addition & 1 deletion crates/burn-core/src/nn/attention/mask.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,7 @@ pub fn generate_autoregressive_mask<B: Backend>(
mask = mask.slice_assign([0..1, i..i + 1, i + 1..seq_length], values);
}

mask = mask.repeat(0, batch_size);
mask = mask.repeat_dim(0, batch_size);

mask.equal_elem(1_i64.elem::<i64>())
}
Expand Down
6 changes: 3 additions & 3 deletions crates/burn-core/src/nn/loss/cross_entropy.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -152,7 +152,7 @@ impl<B: Backend> CrossEntropyLoss<B> {
* weights
.clone()
.reshape([1, nr_classes])
.repeat(0, batch_size);
.repeat_dim(0, batch_size);
let weights = weights.clone().gather(0, targets);
let tensor = Self::apply_mask_2d(tensor, mask);
tensor.sum().neg() / weights.sum()
Expand Down Expand Up @@ -224,7 +224,7 @@ impl<B: Backend> CrossEntropyLoss<B> {
fn apply_mask_2d(mut tensor: Tensor<B, 2>, mask: Option<Tensor<B, 1, Bool>>) -> Tensor<B, 2> {
if let Some(mask) = mask {
let [batch_size, nr_classes] = tensor.dims();
tensor = tensor.mask_fill(mask.reshape([batch_size, 1]).repeat(1, nr_classes), 0);
tensor = tensor.mask_fill(mask.reshape([batch_size, 1]).repeat_dim(1, nr_classes), 0);
}

tensor
Expand Down Expand Up @@ -312,7 +312,7 @@ mod tests {
* targets_logits
* Tensor::<TestBackend, 1>::from_floats(weights.as_slice(), &device)
.unsqueeze()
.repeat(0, 4);
.repeat_dim(0, 4);
let loss_2 = loss_2.sum().neg() / (1. + 2. + 3. + 5.);
loss_1.into_data().assert_approx_eq(&loss_2.into_data(), 3);
}
Expand Down
4 changes: 2 additions & 2 deletions crates/burn-core/src/nn/rope_encoding.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -58,7 +58,7 @@ impl RotaryEncodingConfig {
.float()
.unsqueeze()
.transpose()
.repeat(1, self.d_model / 2)
.repeat_dim(1, self.d_model / 2)
* theta_i.unsqueeze();

// Convert frequency values to complex numbers (polar form)
Expand All @@ -71,7 +71,7 @@ impl RotaryEncodingConfig {
.reshape([self.max_sequence_length, 2, self.d_model / 2])
.transpose()
.unsqueeze_dim::<4>(2)
.repeat(2, 2)
.repeat_dim(2, 2)
.reshape([self.max_sequence_length, self.d_model, 2]);

RotaryEncoding {
Expand Down
18 changes: 9 additions & 9 deletions crates/burn-fusion/src/ops/boolean.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@ use burn_tensor::{
BaseOperationDescription, BinaryOperationDescription, BoolOperationDescription,
CatOperationDescription, ExpandOperationDescription, FlipOperationDescription,
HandleContainer, OperationDescription, PermuteOperationDescription,
RepeatOperationDescription, ReshapeDescription, SliceAssignOperationDescription,
RepeatDimOperationDescription, ReshapeDescription, SliceAssignOperationDescription,
SliceOperationDescription, SwapDimsDescription, UnaryOperationDescription,
},
Device, Shape,
Expand Down Expand Up @@ -575,22 +575,22 @@ impl<B: FusionBackend> BoolTensorOps<Self> for Fusion<B> {
out
}

fn bool_repeat<const D: usize>(
fn bool_repeat_dim<const D: usize>(
tensor: BoolTensor<Self, D>,
dim: usize,
times: usize,
) -> BoolTensor<Self, D> {
#[derive(new)]
struct RepeatOps<B: FusionBackend, const D: usize> {
desc: RepeatOperationDescription,
struct RepeatDimOps<B: FusionBackend, const D: usize> {
desc: RepeatDimOperationDescription,
_b: PhantomData<B>,
}

impl<const D: usize, B: FusionBackend> Operation<B::FusionRuntime> for RepeatOps<B, D> {
impl<const D: usize, B: FusionBackend> Operation<B::FusionRuntime> for RepeatDimOps<B, D> {
fn execute(self: Box<Self>, handles: &mut HandleContainer<B::Handle>) {
let tensor = handles.get_bool_tensor::<B, D>(&self.desc.tensor);

let output = B::bool_repeat::<D>(tensor, self.desc.dim, self.desc.times);
let output = B::bool_repeat_dim::<D>(tensor, self.desc.dim, self.desc.times);

handles.register_bool_tensor::<B, D>(&self.desc.out.id, output);
}
Expand All @@ -601,16 +601,16 @@ impl<B: FusionBackend> BoolTensorOps<Self> for Fusion<B> {
shape[dim] *= times;
let out = tensor.client.tensor_uninitialized(shape, DType::Bool);

let desc = RepeatOperationDescription {
let desc = RepeatDimOperationDescription {
tensor: tensor.into_description(),
dim,
times,
out: out.to_description_out(),
};
out.client.register(
vec![stream],
OperationDescription::BaseBool(BaseOperationDescription::Repeat(desc.clone())),
RepeatOps::<B, D>::new(desc),
OperationDescription::BaseBool(BaseOperationDescription::RepeatDim(desc.clone())),
RepeatDimOps::<B, D>::new(desc),
);

out
Expand Down
16 changes: 8 additions & 8 deletions crates/burn-fusion/src/ops/float.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1696,22 +1696,22 @@ impl<B: FusionBackend> FloatTensorOps<Self> for Fusion<B> {
out
}

fn float_repeat<const D: usize>(
fn float_repeat_dim<const D: usize>(
tensor: FloatTensor<Self, D>,
dim: usize,
times: usize,
) -> FloatTensor<Self, D> {
#[derive(new)]
struct RepeatOps<B: FusionBackend, const D: usize> {
desc: RepeatOperationDescription,
struct RepeatDimOps<B: FusionBackend, const D: usize> {
desc: RepeatDimOperationDescription,
_b: PhantomData<B>,
}

impl<const D: usize, B: FusionBackend> Operation<B::FusionRuntime> for RepeatOps<B, D> {
impl<const D: usize, B: FusionBackend> Operation<B::FusionRuntime> for RepeatDimOps<B, D> {
fn execute(self: Box<Self>, handles: &mut HandleContainer<B::Handle>) {
let tensor = handles.get_float_tensor::<B, D>(&self.desc.tensor);

let output = B::float_repeat::<D>(tensor, self.desc.dim, self.desc.times);
let output = B::float_repeat_dim::<D>(tensor, self.desc.dim, self.desc.times);

handles.register_float_tensor::<B, D>(&self.desc.out.id, output);
}
Expand All @@ -1724,16 +1724,16 @@ impl<B: FusionBackend> FloatTensorOps<Self> for Fusion<B> {
.client
.tensor_uninitialized(shape, B::FloatElem::dtype());

let desc = RepeatOperationDescription {
let desc = RepeatDimOperationDescription {
tensor: tensor.into_description(),
dim,
times,
out: out.to_description_out(),
};
out.client.register(
vec![stream],
OperationDescription::BaseFloat(BaseOperationDescription::Repeat(desc.clone())),
RepeatOps::<B, D>::new(desc),
OperationDescription::BaseFloat(BaseOperationDescription::RepeatDim(desc.clone())),
RepeatDimOps::<B, D>::new(desc),
);

out
Expand Down
16 changes: 8 additions & 8 deletions crates/burn-fusion/src/ops/int.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1755,22 +1755,22 @@ impl<B: FusionBackend> IntTensorOps<Self> for Fusion<B> {
out
}

fn int_repeat<const D: usize>(
fn int_repeat_dim<const D: usize>(
tensor: IntTensor<Self, D>,
dim: usize,
times: usize,
) -> IntTensor<Self, D> {
#[derive(new)]
struct RepeatOps<B: FusionBackend, const D: usize> {
desc: RepeatOperationDescription,
struct RepeatDimOps<B: FusionBackend, const D: usize> {
desc: RepeatDimOperationDescription,
_b: PhantomData<B>,
}

impl<const D: usize, B: FusionBackend> Operation<B::FusionRuntime> for RepeatOps<B, D> {
impl<const D: usize, B: FusionBackend> Operation<B::FusionRuntime> for RepeatDimOps<B, D> {
fn execute(self: Box<Self>, handles: &mut HandleContainer<B::Handle>) {
let tensor = handles.get_int_tensor::<B, D>(&self.desc.tensor);

let output = B::int_repeat::<D>(tensor, self.desc.dim, self.desc.times);
let output = B::int_repeat_dim::<D>(tensor, self.desc.dim, self.desc.times);

handles.register_int_tensor::<B, D>(&self.desc.out.id, output);
}
Expand All @@ -1783,16 +1783,16 @@ impl<B: FusionBackend> IntTensorOps<Self> for Fusion<B> {
.client
.tensor_uninitialized(shape, B::IntElem::dtype());

let desc = RepeatOperationDescription {
let desc = RepeatDimOperationDescription {
tensor: tensor.into_description(),
dim,
times,
out: out.to_description_out(),
};
out.client.register(
vec![stream],
OperationDescription::BaseInt(BaseOperationDescription::Repeat(desc.clone())),
RepeatOps::<B, D>::new(desc),
OperationDescription::BaseInt(BaseOperationDescription::RepeatDim(desc.clone())),
RepeatDimOps::<B, D>::new(desc),
);

out
Expand Down
Loading
Loading