[MLIR] Add allow Insert/extract slice option to pack/unpack op #117340
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@llvm/pr-subscribers-mlir Author: Zhuoran Yin (jerryyin) ChangesThis PR adds default option below. The new options will come as default to true and not change the original lowering behavior of pack and unpack op.
The motivation of the PR is finer granular control of the lowering of pack and unpack Ops. This is useful in particular when we want to guarantee that there's no additional insertslice and extractslice that interfere with tiling. With the original lowering pipeline, packOp and unPackOp may be lowered to insertslice and extractslice when the high dimensions are unit dimensions and no transpose is invovled. Under such circumstances, such insert and extract slice ops will block consumer fusion for TileAndFuse pipeline. With this PR, we will be able to disable such lowering path and allow consumer fusion to go through as expected. Full diff: https://github.com/llvm/llvm-project/pull/117340.diff 4 Files Affected:
diff --git a/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td b/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
index e3084530bd11b5..ea96da77b6c331 100644
--- a/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
+++ b/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
@@ -548,7 +548,8 @@ def LowerPackOp : Op<Transform_Dialect, "structured.lower_pack", [
Return handles to the newly produced pad, expand_shape and transpose ops.
}];
- let arguments = (ins Transform_ConcreteOpType<"tensor.pack">:$target);
+ let arguments = (ins Transform_ConcreteOpType<"tensor.pack">:$target,
+ DefaultValuedAttr<BoolAttr, "true">:$allowInsertSliceLowering);
let results = (outs Transform_ConcreteOpType<"tensor.pad">:$pad_op,
Transform_ConcreteOpType<"tensor.expand_shape">:$expand_shape_op,
Transform_ConcreteOpType<"linalg.transpose">:$transpose_op);
@@ -588,7 +589,8 @@ def LowerUnPackOp : Op<Transform_Dialect, "structured.lower_unpack", [
Return handles to the newly produced empty, transpose, collapse_shape and extract_slice ops.
}];
- let arguments = (ins Transform_ConcreteOpType<"tensor.unpack">:$target);
+ let arguments = (ins Transform_ConcreteOpType<"tensor.unpack">:$target,
+ DefaultValuedAttr<BoolAttr, "true">:$allowExtractSliceLowering);
let results = (outs Transform_ConcreteOpType<"tensor.empty">:$empty_op,
Transform_ConcreteOpType<"linalg.transpose">:$transpose_op,
Transform_ConcreteOpType<"tensor.collapse_shape">:$collapse_shape_op,
diff --git a/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h b/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
index 51967f83fee377..fd27e7929764d3 100644
--- a/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
+++ b/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
@@ -1121,7 +1121,8 @@ struct LowerPackResult {
/// Rewrite pack as pad + reshape + transpose.
FailureOr<LowerPackResult> lowerPack(RewriterBase &rewriter,
- tensor::PackOp packOp);
+ tensor::PackOp packOp,
+ bool allowInsertSliceLowering = true);
struct LowerUnPackOpResult {
tensor::EmptyOp emptyOp;
@@ -1131,8 +1132,9 @@ struct LowerUnPackOpResult {
};
/// Rewrite pack as empty + transpose + reshape + extract_slice.
-FailureOr<LowerUnPackOpResult> lowerUnPack(RewriterBase &rewriter,
- tensor::UnPackOp unPackOp);
+FailureOr<LowerUnPackOpResult>
+lowerUnPack(RewriterBase &rewriter, tensor::UnPackOp unPackOp,
+ bool allowExtractSliceLowering = true);
/// Struct to hold the result of a `pack` call.
struct PackResult {
diff --git a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
index ada80deacfdbfe..5117a5c58c381d 100644
--- a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
+++ b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
@@ -1171,7 +1171,9 @@ DiagnosedSilenceableFailure transform::LowerPackOp::applyToOne(
transform::ApplyToEachResultList &transformResults,
transform::TransformState &state) {
rewriter.setInsertionPoint(target);
- FailureOr<LowerPackResult> res = lowerPack(rewriter, target);
+ bool allowInsertSliceLowering = getAllowInsertSliceLowering();
+ FailureOr<LowerPackResult> res =
+ lowerPack(rewriter, target, allowInsertSliceLowering);
if (failed(res)) {
return mlir::emitSilenceableFailure(target->getLoc())
<< "cannot lower to pad + expand + transpose";
@@ -1191,7 +1193,9 @@ DiagnosedSilenceableFailure transform::LowerUnPackOp::applyToOne(
transform::ApplyToEachResultList &transformResults,
transform::TransformState &state) {
rewriter.setInsertionPoint(target);
- FailureOr<LowerUnPackOpResult> res = lowerUnPack(rewriter, target);
+ bool allowExtractSliceLowering = getAllowExtractSliceLowering();
+ FailureOr<LowerUnPackOpResult> res =
+ lowerUnPack(rewriter, target, allowExtractSliceLowering);
if (failed(res)) {
DiagnosedSilenceableFailure diag =
emitSilenceableError()
diff --git a/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp b/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
index d92543d7264625..0717dad4c2852f 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
@@ -217,7 +217,8 @@ struct PackedOperandsDimList {
} // namespace
FailureOr<LowerPackResult> linalg::lowerPack(RewriterBase &rewriter,
- tensor::PackOp packOp) {
+ tensor::PackOp packOp,
+ bool allowInsertSliceLowering) {
// 1. Filter out NYI cases.
auto packedTensorType =
cast<RankedTensorType>(packOp->getResultTypes().front());
@@ -295,7 +296,7 @@ FailureOr<LowerPackResult> linalg::lowerPack(RewriterBase &rewriter,
llvm::interleaveComma(stripMinedShape, DBGS() << "stripMinedShape: ");
DBGSNL(); DBGS() << "collapsed type: " << collapsed; DBGSNL(););
- if (packOp.isLikePad()) {
+ if (allowInsertSliceLowering && packOp.isLikePad()) {
// Pack ops which operate as simple pads may not produce legal
// tensor.insert_slice operations when the packed type does not rank reduce
// to the padded type.
@@ -351,8 +352,9 @@ FailureOr<LowerPackResult> linalg::lowerPack(RewriterBase &rewriter,
return LowerPackResult{padOp, reshapeOp, transposeOp};
}
-FailureOr<LowerUnPackOpResult> linalg::lowerUnPack(RewriterBase &rewriter,
- tensor::UnPackOp unPackOp) {
+FailureOr<LowerUnPackOpResult>
+linalg::lowerUnPack(RewriterBase &rewriter, tensor::UnPackOp unPackOp,
+ bool allowExtractSliceLowering) {
Location loc = unPackOp->getLoc();
OpBuilder::InsertionGuard g(rewriter);
rewriter.setInsertionPoint(unPackOp);
@@ -362,7 +364,7 @@ FailureOr<LowerUnPackOpResult> linalg::lowerUnPack(RewriterBase &rewriter,
OpFoldResult zero = rewriter.getIndexAttr(0), one = rewriter.getIndexAttr(1);
auto destTensorType = cast<RankedTensorType>(unPackOp.getDest().getType());
- if (unPackOp.isLikeUnPad()) {
+ if (allowExtractSliceLowering && unPackOp.isLikeUnPad()) {
// This unpack is just a plain unpad.
// Just extract the slice from the higher ranked tensor.
ArrayRef<int64_t> destShape = destTensorType.getShape();
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@llvm/pr-subscribers-mlir-linalg Author: Zhuoran Yin (jerryyin) ChangesThis PR adds default option below. The new options will come as default to true and not change the original lowering behavior of pack and unpack op.
The motivation of the PR is finer granular control of the lowering of pack and unpack Ops. This is useful in particular when we want to guarantee that there's no additional insertslice and extractslice that interfere with tiling. With the original lowering pipeline, packOp and unPackOp may be lowered to insertslice and extractslice when the high dimensions are unit dimensions and no transpose is invovled. Under such circumstances, such insert and extract slice ops will block consumer fusion for TileAndFuse pipeline. With this PR, we will be able to disable such lowering path and allow consumer fusion to go through as expected. Full diff: https://github.com/llvm/llvm-project/pull/117340.diff 4 Files Affected:
diff --git a/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td b/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
index e3084530bd11b5..ea96da77b6c331 100644
--- a/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
+++ b/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
@@ -548,7 +548,8 @@ def LowerPackOp : Op<Transform_Dialect, "structured.lower_pack", [
Return handles to the newly produced pad, expand_shape and transpose ops.
}];
- let arguments = (ins Transform_ConcreteOpType<"tensor.pack">:$target);
+ let arguments = (ins Transform_ConcreteOpType<"tensor.pack">:$target,
+ DefaultValuedAttr<BoolAttr, "true">:$allowInsertSliceLowering);
let results = (outs Transform_ConcreteOpType<"tensor.pad">:$pad_op,
Transform_ConcreteOpType<"tensor.expand_shape">:$expand_shape_op,
Transform_ConcreteOpType<"linalg.transpose">:$transpose_op);
@@ -588,7 +589,8 @@ def LowerUnPackOp : Op<Transform_Dialect, "structured.lower_unpack", [
Return handles to the newly produced empty, transpose, collapse_shape and extract_slice ops.
}];
- let arguments = (ins Transform_ConcreteOpType<"tensor.unpack">:$target);
+ let arguments = (ins Transform_ConcreteOpType<"tensor.unpack">:$target,
+ DefaultValuedAttr<BoolAttr, "true">:$allowExtractSliceLowering);
let results = (outs Transform_ConcreteOpType<"tensor.empty">:$empty_op,
Transform_ConcreteOpType<"linalg.transpose">:$transpose_op,
Transform_ConcreteOpType<"tensor.collapse_shape">:$collapse_shape_op,
diff --git a/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h b/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
index 51967f83fee377..fd27e7929764d3 100644
--- a/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
+++ b/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
@@ -1121,7 +1121,8 @@ struct LowerPackResult {
/// Rewrite pack as pad + reshape + transpose.
FailureOr<LowerPackResult> lowerPack(RewriterBase &rewriter,
- tensor::PackOp packOp);
+ tensor::PackOp packOp,
+ bool allowInsertSliceLowering = true);
struct LowerUnPackOpResult {
tensor::EmptyOp emptyOp;
@@ -1131,8 +1132,9 @@ struct LowerUnPackOpResult {
};
/// Rewrite pack as empty + transpose + reshape + extract_slice.
-FailureOr<LowerUnPackOpResult> lowerUnPack(RewriterBase &rewriter,
- tensor::UnPackOp unPackOp);
+FailureOr<LowerUnPackOpResult>
+lowerUnPack(RewriterBase &rewriter, tensor::UnPackOp unPackOp,
+ bool allowExtractSliceLowering = true);
/// Struct to hold the result of a `pack` call.
struct PackResult {
diff --git a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
index ada80deacfdbfe..5117a5c58c381d 100644
--- a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
+++ b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
@@ -1171,7 +1171,9 @@ DiagnosedSilenceableFailure transform::LowerPackOp::applyToOne(
transform::ApplyToEachResultList &transformResults,
transform::TransformState &state) {
rewriter.setInsertionPoint(target);
- FailureOr<LowerPackResult> res = lowerPack(rewriter, target);
+ bool allowInsertSliceLowering = getAllowInsertSliceLowering();
+ FailureOr<LowerPackResult> res =
+ lowerPack(rewriter, target, allowInsertSliceLowering);
if (failed(res)) {
return mlir::emitSilenceableFailure(target->getLoc())
<< "cannot lower to pad + expand + transpose";
@@ -1191,7 +1193,9 @@ DiagnosedSilenceableFailure transform::LowerUnPackOp::applyToOne(
transform::ApplyToEachResultList &transformResults,
transform::TransformState &state) {
rewriter.setInsertionPoint(target);
- FailureOr<LowerUnPackOpResult> res = lowerUnPack(rewriter, target);
+ bool allowExtractSliceLowering = getAllowExtractSliceLowering();
+ FailureOr<LowerUnPackOpResult> res =
+ lowerUnPack(rewriter, target, allowExtractSliceLowering);
if (failed(res)) {
DiagnosedSilenceableFailure diag =
emitSilenceableError()
diff --git a/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp b/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
index d92543d7264625..0717dad4c2852f 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
@@ -217,7 +217,8 @@ struct PackedOperandsDimList {
} // namespace
FailureOr<LowerPackResult> linalg::lowerPack(RewriterBase &rewriter,
- tensor::PackOp packOp) {
+ tensor::PackOp packOp,
+ bool allowInsertSliceLowering) {
// 1. Filter out NYI cases.
auto packedTensorType =
cast<RankedTensorType>(packOp->getResultTypes().front());
@@ -295,7 +296,7 @@ FailureOr<LowerPackResult> linalg::lowerPack(RewriterBase &rewriter,
llvm::interleaveComma(stripMinedShape, DBGS() << "stripMinedShape: ");
DBGSNL(); DBGS() << "collapsed type: " << collapsed; DBGSNL(););
- if (packOp.isLikePad()) {
+ if (allowInsertSliceLowering && packOp.isLikePad()) {
// Pack ops which operate as simple pads may not produce legal
// tensor.insert_slice operations when the packed type does not rank reduce
// to the padded type.
@@ -351,8 +352,9 @@ FailureOr<LowerPackResult> linalg::lowerPack(RewriterBase &rewriter,
return LowerPackResult{padOp, reshapeOp, transposeOp};
}
-FailureOr<LowerUnPackOpResult> linalg::lowerUnPack(RewriterBase &rewriter,
- tensor::UnPackOp unPackOp) {
+FailureOr<LowerUnPackOpResult>
+linalg::lowerUnPack(RewriterBase &rewriter, tensor::UnPackOp unPackOp,
+ bool allowExtractSliceLowering) {
Location loc = unPackOp->getLoc();
OpBuilder::InsertionGuard g(rewriter);
rewriter.setInsertionPoint(unPackOp);
@@ -362,7 +364,7 @@ FailureOr<LowerUnPackOpResult> linalg::lowerUnPack(RewriterBase &rewriter,
OpFoldResult zero = rewriter.getIndexAttr(0), one = rewriter.getIndexAttr(1);
auto destTensorType = cast<RankedTensorType>(unPackOp.getDest().getType());
- if (unPackOp.isLikeUnPad()) {
+ if (allowExtractSliceLowering && unPackOp.isLikeUnPad()) {
// This unpack is just a plain unpad.
// Just extract the slice from the higher ranked tensor.
ArrayRef<int64_t> destShape = destTensorType.getShape();
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jerryyin
changed the title
allowExtractSliceLowering
Why not add tests for that? I don't really know how fusion is tested, but this summary implies that we should be writing tests showing how these things compose? And demonstrating the impact of this new flag. On a different note, there's |
I agree it is good to unify and reduce the overall number of patterns, but just want to note that we should make sure we still have the same type of control over how/which patterns are applied (that's probably what you were suggesting anyway, but just wanted to add that comment). |
Agreed - we shouldn't bundle things pre-maturely. However, if these patterns effectively duplicate one another ... That's a topic for another PR though ;-) |
I'm not really sure where a test like this belongs. If you have a suggestion for where we could put it that would be very helpful! Here is an example case where this helps: %producer = tensor.pack %src into %dest ...
%consumer_loop = scf.for ... {
%slice = tensor.extract_slice %producer ...
%consumer = "some_op" %slice ...
...
}After decomposition this becomes one of 2 options: // With the slice lowering:
%pad = tensor.pad %src ...
%producer = tensor.insert_slice %pad into %dest ...
%consumer_loop = scf.for ... {
%slice = tensor.extract_slice %producer ...
%consumer = "some_op" %slice ...
...
}
// With the non-slice (expand_shape/transpose) lowering\
%pad = tensor.pad %src
%expand = tensor.expand_shape %pad ...
%producer = linalg.transpose ins(%expand ...
%consumer_loop = scf.for ... {
%slice = tensor.extract_slice %producer ...
%consumer = "some_op" %slice ...
...
}If we then want to run fusion of So if we want to test this specific case, then we would be testing the composition of these 2 transform ops, and I'm not sure where the correct test directory for this is. Alternatively, we can add a test for the fusion case above (which would be expected to fail fusion), but I'm not sure if that's a very useful test. |
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I see discussions converging here. My next commit is going to be:
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- Renamed allowInsertSliceLowering to lowerPadLikeWithInsertSlice - Renamed allowExtractSliceLowering to lowerUnpadLikeWithExtractSlice - Removed the redundant unit test since this is NFC change This reverts commit 46b7202.
It should be much easier than before today. People have filled the gaps in the past one year. |
I would keep the unit test. When I asked about the test that you added (and subsequently removed), it just wasn't clear to me what to look for and what the difference with the existing tests should be. The comment from @Max191 makes that very clear: // Current
func.func @pack_as_pad_default() {
%pad = tensor.pad %src ...
%producer = tensor.insert_slice %pad into %dest
}
// New
func.func @pack_as_pad_{disable|no|skip}_insert_slice() {
%pad = tensor.pad %src
%expand = tensor.expand_shape %pad ...
%producer = linalg.transpose ins(%expand ..
}Suggestion 1
I think that the following test would be sufficient and very illustrative (trimmed for brevity - feel free to re-use/expand): // CHECK-LABEL: func.func @pack_disallowed_as_pad(
func.func @pack_disallowed_as_pad(%arg0, %arg1) {
// CHECK: %[[PAD:.*]] = tensor.pad %[[SRC]]
// CHECK-NOT: %[[RES:.*]] = tensor.insert_slice %[[PAD]]
// CHECK: %[[PAD_EXPANDED:.*]] = tensor.expand_shape %[[PAD]]
// CHECK: %[[RES:.*]] = linalg.transpose %[[PAD_EXPANDED]]
%pack = tensor.pack %arg0 padding_value(%cst_0 : f32) inner_dims_pos = [0, 1, 2, 3] inner_tiles = [136, 64, 16, 16] into %arg1
: tensor<129x47x16x16xf32> -> tensor<1x1x1x1x136x64x16x16xf32>
return %pack : tensor<1x1x1x1x136x64x16x16xf32>
}IIUC, these are the existing tests that exercise similar path: llvm-project/mlir/test/Dialect/Linalg/transform-lower-pack.mlir Lines 3 to 60 in 1b2c8f1 Both of these tests are called Suggestion 2
Sure, happy to help! I see multiple options: Option 1: Add a test file in test/Dialect/Linalg (e.g. "transform-lower-pack-and-fuse.mlir") and test it there. Looks like there's already transform-tile-and-fuse.mlir, so use that as your source of inspiration :) Option 2: Some e2e tests exercise complex compilation pipelines, e.g. pack-dynamic-inner-tile.mlir. But that's quite a heavy hammer. Option 3: Add a bit more powerful TD Op that would include fusion and various related patterns that create fusion opportunities. I'd start with Option 1 and leave Option 2 and Option 3 for the future. On a related note, we should start creating sub-directories in test/Dialect/Linalg/ - there's too many tests prefixed "transform-{}.mlir" 😅 Hope this helps and thanks for working on this 🙏🏻 ! |
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@banach-space Thanks for the review and suggestions. It's very helpful to see so much details in your review! For suggestion 1, please see commit 671829e that adds back the unit test with attributes.
For suggestion 2, option 1, see commit 3ad8cd6 for your suggested test case to exercise consumer and producer fusion.
Thanks again for your suggestions. Please take a second look of the PR and let me know if you have additional questions/concerns. |
jerryyin
changed the title
|
Thanks for the updates! I've run out of cycles today, but this will be my priority for Monday morning. Apologies for the delay! |
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Thank you for addressing my comments so comprehensively and for splitting your replies into separate commits - makes reviewing so much easier 🙏🏻
I've left a few minor comments inline, otherwise looks good to me.
Under such circumstances, such insert and extract slice ops will block producer/consumer fusion tile + fuse transforms.
Somewhat tangential to this PR, but it would be good to document whether this limitation is meant to be lifted at some point?
mlir/test/Dialect/Linalg/transform-tile-and-fuse-pack-unpack.mlir
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- Added additional test cases to demonstrate insert/extract slice will block producer/consumer fusion - Readability enahncements
mlir/test/Dialect/Linalg/transform-tile-and-fuse-pack-unpack.mlir
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This help to clearly demonstrate the produer fusion in pack case and consumer fusion in unpack case.
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… shapes (#19484) This PR does two things 1. Allow all GEMM shapes to use padded TileAndFuse Matmul configuration. This is still behind the `iree-codegen-llvmgpu-test-tile-and-fuse-matmul=false` flag by default and does not change the default behavior. However following PRs that have landed in the past month make it possible to relax the guards we originally had on this. #19196 #19307 llvm/llvm-project#117340 2. Allow fused producers to use use padded TileAndFuse Matmul configuration. Following PRs make this possible now #19399 llvm/llvm-project#119039 Together this allows us to do padded IGEMM with intrinsics for shapes unaligned to intrinsic which we use by default. [Here](https://docs.google.com/spreadsheets/d/1O-SdUZCn5pHsxx7JTGjIIdH6PWCFnvlfe4XBbjEBaIM/edit?gid=0#gid=0) is the performance difference observed in conv cases in iree-kernel-benchmark-module that utilize this change. A median speedup of 2.26x was observed. The numeric changes I observed with enabling this path were the same between any aligned shape when comparing intrinsic vs no intrinsic use. Generally some differences are noticed for narrow types like f16 but they are within a relative error of 0.001 but since our tests use absolute errors we may have to change some test values to account for this change. The perf difference in CI seem to be within noise margin compared to main, https://github.com/iree-org/iree/actions/runs/12323399269/attempts/1#summary-34399247902 --------- Signed-off-by: Nirvedh <[email protected]>
…lt (#19590) This PR is a follow-up to llvm/llvm-project#117340. It disables `lowerPadLikeWithInsertSlice` and `lowerUnpadLikeWithExtractSlice` so `insertslice` or `extractslice` won't appear when high dimensions are unit dimensions. --------- Signed-off-by: jerryyin <[email protected]>
This PR adds default option below. The new options will come as default to true and not change the original lowering behavior of pack and unpack op.
The motivation of the PR is finer granular control of the lowering of pack and unpack Ops. This is useful in particular when we want to guarantee that there's no additional insertslice and extractslice that interfere with tiling. With the original lowering pipeline, packOp and unPackOp may be lowered to insertslice and extractslice when the high dimensions are unit dimensions and no transpose is invovled. Under such circumstances, such insert and extract slice ops will block producer/consumer fusion tile + fuse transforms. With this PR, we will be able to disable such lowering path and allow consumer fusion to go through as expected.