Skip to content

address uneccessary dynamic shapes in argmax decomposition #3889

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 2 commits into from
Nov 23, 2024
Merged

address uneccessary dynamic shapes in argmax decomposition #3889

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
a8a6815
Cleanup artificial dynamic shapes in argmax decomposition
zjgarvey Nov 22, 2024
71e66a0
address new xpasses
zjgarvey Nov 22, 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: 15 additions & 9 deletions lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2593,16 +2593,22 @@ class DecomposeAtenArgMinMaxOp : public OpRewritePattern<OpTy> {
// first the input tensor is flattened to 1d tensor and then the reduction
// happens on the 0th dimension.
if (isa<Torch::NoneType>(dim.getType())) {
BaseTensorType flattenType =
cast<BaseTensorType>(inputType.getWithSizesAndDtype(
{kUnknownSize}, inputType.getOptionalDtype()));
Value zero =
rewriter.create<ConstantIntOp>(loc, rewriter.getI64IntegerAttr(0));
Value end = rewriter.create<ConstantIntOp>(
loc, rewriter.getI64IntegerAttr(inputRank - 1));
Value zero = rewriter.create<ConstantIntOp>(loc, 0);
Value falseValue = rewriter.create<ConstantBoolOp>(loc, false);
input = rewriter.create<AtenFlattenUsingIntsOp>(loc, flattenType, input,
zero, end);
if (inputType.getSizes().size() > 1) {
int64_t flattenSize = Torch::kUnknownSize;
if (inputType.areAllSizesKnown()) {
flattenSize = 1;
for (int64_t sze : inputType.getSizes())
flattenSize *= sze;
}
auto flattenType = cast<BaseTensorType>(inputType.getWithSizesAndDtype(
{flattenSize}, inputType.getOptionalDtype()));
Value end = rewriter.create<ConstantIntOp>(
loc, rewriter.getI64IntegerAttr(inputRank - 1));
input = rewriter.create<AtenFlattenUsingIntsOp>(loc, flattenType, input,
zero, end);
}
Value resultIndices =
rewriter
.create<DecompOpTy>(
Expand Down
7 changes: 0 additions & 7 deletions projects/pt1/e2e_testing/xfail_sets.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -545,10 +545,6 @@

FX_IMPORTER_STABLEHLO_XFAIL_SET = {
"AddFloatIntModule_basic",
"ArgmaxIntModule_basic",
"ArgmaxIntModule_multiple_maxs",
"ArgmaxKeepdimModule_basic",
"ArgmaxModule_basic",
"AtenKthvalueDynamicDimsModule_basic",
"AtenKthvalueFloat64DynamicDimsModule_basic",
"AtenKthvalueFloat64Module_basic",
Expand Down Expand Up @@ -618,9 +614,6 @@
"AnyBoolFalseModule_basic",
"AnyBoolTrueModule_basic",
"ArangeStartOutViewModule_basic",
"ArgminIntModule_basic",
"ArgminIntModule_multiple_mins",
"ArgminModule_basic",
"AtenComplexImagModule_basic",
"AtenComplexRealModule_basic",
"AtenComplexViewModule_basic",
Expand Down
13 changes: 13 additions & 0 deletions test/Dialect/Torch/decompose-complex-ops.mlir
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,19 @@ func.func @matmul_decompose_3d(%arg0: !torch.vtensor<[?,?,?],f32>, %arg1: !torch
return %0 : !torch.tensor
}

// -----
// CHECK-LABEL: func.func @argmax_rank_1
// CHECK: %[[I0:.*]] = torch.constant.int 0
// CHECK: %[[FALSE:.*]] = torch.constant.bool false
// CHECK: %[[VALUES:.*]], %[[INDICES:.*]] = torch.aten.max.dim %arg0, %[[I0]], %[[FALSE]] : !torch.vtensor<[20],si32>, !torch.int, !torch.bool -> !torch.vtensor<[],si32>, !torch.vtensor<[],si64>
// CHECK: return %[[INDICES]] : !torch.vtensor<[],si64>
func.func @argmax_rank_1(%arg0: !torch.vtensor<[20],si32>) -> !torch.vtensor<[],si64> {
%none = torch.constant.none
%false = torch.constant.bool false
%7 = torch.aten.argmax %arg0, %none, %false : !torch.vtensor<[20],si32>, !torch.none, !torch.bool -> !torch.vtensor<[],si64>
return %7 : !torch.vtensor<[],si64>
}

// -----
// CHECK-LABEL: func.func @torch.aten.type_as$basic(
// CHECK-SAME: %[[ARG_0:.*]]: !torch.tensor, %[[ARG_1:.*]]: !torch.tensor) -> !torch.tensor {
Expand Down
Loading