Skip to content
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

Jump to bottom

Fix indices dim check in gather_update_outputs #2149

Merged
merged 1 commit into from
Aug 12, 2024
Merged

Fix indices dim check in gather_update_outputs #2149

Changes from all commits
Commits
Show all changes
1 commit
Select commit
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
13 changes: 7 additions & 6 deletions crates/onnx-ir/src/dim_inference.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -810,19 +810,20 @@ fn gather_update_outputs(node: &mut Node) {
panic!("Gather requires two inputs: data and indices");
}

let indices_tensor = match &node.inputs[1].ty {
ArgType::Tensor(tensor) => tensor,
_ => panic!("Only tensor indices is valid"),
let indices_dim = match &node.inputs[1].ty {
ArgType::Tensor(tensor) => tensor.dim,
ArgType::Scalar(_) => 0,
_ => panic!("Only tensor indices is valid, got {:?}", node.inputs[1].ty),
};

if indices_tensor.dim > 1 {
if indices_dim > 1 {
panic!("Gather: indices tensor rank above 1 not supported")
}

match &node.inputs[0].ty {
ArgType::Tensor(input_tensor) => {
// Output of rank q+(r-1), where q is rank of indices tensor and r is rank of input
let output_rank = indices_tensor.dim + input_tensor.dim - 1;
let output_rank = indices_dim + input_tensor.dim - 1;

node.outputs[0].ty = ArgType::Tensor(TensorType {
elem_type: input_tensor.elem_type.clone(),
Expand All @@ -833,7 +834,7 @@ fn gather_update_outputs(node: &mut Node) {
ArgType::Shape(_dim) => {
let shape_dim = 1;
// Output of rank q+(r-1), where q is rank of indices tensor and r is rank of input
let output_rank = indices_tensor.dim + shape_dim - 1;
let output_rank = indices_dim + shape_dim - 1;

node.outputs[0].ty = ArgType::Tensor(TensorType {
elem_type: ElementType::Int64,
Expand Down
Loading