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Differential D93180

[mlir][Linalg] Account for the case where loop bounds depend on output shape.
AbandonedPublic

Authored by mravishankar on Dec 13 2020, 9:26 AM.

Details

Reviewers
nicolasvasilache
pifon2a
Summary

Depends On D93076

Diff Detail

Unit TestsFailed

TimeTest
110 msx64 windows > LLVM.CodeGen/XCore::threads.ll

Event Timeline

mravishankar created this revision.Dec 13 2020, 9:26 AM
Herald added subscribers: teijeong, rdzhabarov, tatianashp and 14 others. · View Herald TranscriptDec 13 2020, 9:26 AM
mravishankar requested review of this revision.Dec 13 2020, 9:26 AM
Herald added a reviewer: nicolasvasilache. · View Herald TranscriptDec 13 2020, 9:26 AM
Herald added a project: Restricted Project. · View Herald Transcript
Herald added subscribers: limo1996, stephenneuendorffer, nicolasvasilache. · View Herald Transcript
Harbormaster completed remote builds in B82186: Diff 311453.Dec 13 2020, 9:42 AM
mravishankar mentioned this in D93077: [mlir][Linalg] NFC: Verify tiling on linalg.generic operation on tensors..Dec 13 2020, 10:03 AM
mravishankar updated this revision to Diff 312121.Dec 15 2020, 11:21 PM

Rebase. This might not be necessary after
https://llvm.discourse.group/t/linalg-and-shapes/2421 is resolved.

mravishankar added a child revision: D93374: [mlir][Linalg] Define a linalg.init_tensor operation..Dec 15 2020, 11:21 PM
Harbormaster completed remote builds in B82588: Diff 312121.Dec 15 2020, 11:22 PM
pifon2a accepted this revision.Dec 17 2020, 9:46 AM
This revision is now accepted and ready to land.Dec 17 2020, 9:46 AM
hanchung added a subscriber: hanchung.Dec 21 2020, 12:22 AM
hanchung added inline comments.
mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
74

no need for template and use auto

mravishankar abandoned this revision.Dec 26 2020, 1:06 PM

Dont need this anymore. Abondoning.

Revision Contents

PathSize
mlir/
lib/
Dialect/
Linalg/
IR/
17 lines

Diff 312121

mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp

Show First 20 Lines • Show All 61 Lines • ▼ Show 20 Lines
SmallVector<Value, 4> LinalgOp::createFlatListOfOperandDims(OpBuilder &b, SmallVector<Value, 4> LinalgOp::createFlatListOfOperandDims(OpBuilder &b,
Location loc) { Location loc) {
SmallVector<Value, 4> res; SmallVector<Value, 4> res;
for (Value v : getShapedOperands()) { for (Value v : getShapedOperands()) {
ShapedType t = v.getType().template cast<ShapedType>(); ShapedType t = v.getType().template cast<ShapedType>();
for (unsigned i = 0, e = t.getRank(); i < e; ++i) for (unsigned i = 0, e = t.getRank(); i < e; ++i)
res.push_back(b.create<DimOp>(loc, v, i)); res.push_back(b.create<DimOp>(loc, v, i));
} }
if (getNumInitTensors() == 0 && getOperation()->getNumResults() != 0) {
OpBuilder::InsertionGuard guard(b);
b.setInsertionPointAfter(getOperation());
for (Value v : getOperation()->getResults()) {
ShapedType t = v.getType().template cast<ShapedType>();
hanchungUnsubmitted
Not Done
ReplyInline Actions

no need for template and use auto

hanchung: no need for template and use `auto`
for (unsigned i = 0, e = t.getRank(); i < e; ++i)
res.push_back(b.create<DimOp>(loc, v, i));
}
}
return res; return res;
} }
SmallVector<Range, 4> LinalgOp::createLoopRanges(OpBuilder &b, Location loc) { SmallVector<Range, 4> LinalgOp::createLoopRanges(OpBuilder &b, Location loc) {
AffineMap map = getLoopsToShapesMap(); AffineMap map = getLoopsToShapesMap();
unsigned numDims = map.getNumDims(), numRes = map.getNumResults(); unsigned numDims = map.getNumDims(), numRes = map.getNumResults();
auto viewSizes = createFlatListOfOperandDims(b, loc); auto viewSizes = createFlatListOfOperandDims(b, loc);
SmallVector<Range, 4> res(numDims); SmallVector<Range, 4> res(numDims);
▲ Show 20 Lines • Show All 82 Lines • ▼ Show 20 LinesOptional<Value> LinalgOp::inferResultDimFromInputShapes(OpBuilder &b,
} }
llvm::SmallSet<unsigned, 4> outputDims; llvm::SmallSet<unsigned, 4> outputDims;
llvm::for_each(llvm::seq<unsigned>(numInputDims, llvm::for_each(llvm::seq<unsigned>(numInputDims,
operandShapesToResultDimMap.getNumDims()), operandShapesToResultDimMap.getNumDims()),
[&outputDims](unsigned dim) { outputDims.insert(dim); }); [&outputDims](unsigned dim) { outputDims.insert(dim); });
HasAffineDimExprVisitor checkDimExpr(outputDims); HasAffineDimExprVisitor checkDimExpr(outputDims);
if (checkDimExpr.visit(operandShapesToResultDimMap.getResult(0))) if (checkDimExpr.visit(operandShapesToResultDimMap.getResult(0)))
return llvm::None; return llvm::None;
// Since map.compose(createFlatListOfOperands()) only works for the case where
// init tensors exist, drop the dims corresponding to output shapes in the
// map.
if (getNumInitTensors() == 0 && getOperation()->getNumResults() != 0) {
operandShapesToResultDimMap = getProjectedMap(
operandShapesToResultDimMap, llvm::to_vector<4>(outputDims));
}
return applyMapToValues(b, loc, operandShapesToResultDimMap, return applyMapToValues(b, loc, operandShapesToResultDimMap,
createFlatListOfOperandDims(b, loc))[0]; createFlatListOfOperandDims(b, loc))[0];
} }
/// Forward declarations. /// Forward declarations.
template <typename NamedStructuredOpType> template <typename NamedStructuredOpType>
static void buildNamedStructuredOpRegionAndAttributes( static void buildNamedStructuredOpRegionAndAttributes(
OpBuilder &opBuilder, OperationState &result, TypeRange inputTypes, OpBuilder &opBuilder, OperationState &result, TypeRange inputTypes,
▲ Show 20 Lines • Show All 1,793 Lines • Show Last 20 Lines