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

[onnx] Fix onnx-to-torch lowering for flatten shape #2834

Merged
merged 5 commits into from
Feb 5, 2024
Merged

[onnx] Fix onnx-to-torch lowering for flatten shape #2834

Changes from 1 commit
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
fe38d06
[onnx] Fix `onnx-to-torch` lowering for flatten shape
rsuderman Jan 30, 2024
871e915
fix tests and reverted collapse removal
rsuderman Feb 1, 2024
f7cf28b
fix dynamic shape type compuptation
rsuderman Feb 1, 2024
ec949af
Fix up dynamic check
rsuderman Feb 5, 2024
47858b5
typo
rsuderman Feb 5, 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
24 changes: 14 additions & 10 deletions lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -486,7 +486,6 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
auto message = llvm::formatv("unimplemented support for the given "
"dtype conversion (onnx 'type' = {0})",
dtypeIntOnnx);
llvm::errs() << message << "\n";
auto y = rewriter.notifyMatchFailure(binder.op, message);

return y;
Expand Down Expand Up @@ -1412,16 +1411,24 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
binder.tensorResultType(resultType))
return failure();

auto operandTy = cast<Torch::ValueTensorType>(operand.getType());
llvm::SmallVector<int64_t> shape(operandTy.getSizes());
int64_t rank = shape.size();

// If axis is negative, count from the right instead of left
int64_t rank =
cast<Torch::ValueTensorType>(operand.getType()).getSizes().size();
if (axis < 0)
axis = rank + axis;

Value collapsedRight;
auto baseType = Torch::ValueTensorType::getWithLeastStaticInformation(
newling marked this conversation as resolved.
Show resolved Hide resolved
binder.op->getContext());
// We collapse in the dimensions to the right of the axis.
for (int i = axis + 1; i < rank; ++i) {
shape[axis] *= shape[i];
}

shape.resize(axis + 1, 1);

auto baseType = rewriter.getType<Torch::ValueTensorType>(
shape, operandTy.getDtype());
Value collapsedRight;
if (axis >= rank) {
// If the right range is empty, add a dim of size 1 to the
// right side of the shape:
Expand Down Expand Up @@ -1455,10 +1462,7 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(

// Otherwise, collapse the left range into a single dimension:
// torch._prims.collapse(cr, 0, axis - 1)
Value axisLess1Const = rewriter.create<Torch::ConstantIntOp>(
newling marked this conversation as resolved.
Show resolved Hide resolved
binder.getLoc(), rewriter.getI64IntegerAttr(axis - 1));
rewriter.replaceOpWithNewOp<Torch::PrimsCollapseOp>(
binder.op, resultType, collapsedRight, zero, axisLess1Const);
rewriter.replaceOp(binder.op, collapsedRight);
return success();
});
patterns.onOp("Floor", 13,
Expand Down
Loading