mirror of https://github.com/llvm/torch-mlir
Fix for 0-size dim inferred incorrectly.
The issue was in the canonicalizer for torch.aten.ge.int -- in cases where the operands were swapped, it would miscompile. This issue is fixed and folding support generalized to `torch.aten.size.int < 0` as well. Fixes #716pull/643/head
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8250f50c81
commit
c17c0a6ba2
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@ -826,8 +826,9 @@ static OpFoldResult intComparatorFoldHelper(OpTy op,
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};
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comparator = newComparator;
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}
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// Fold comparisons of negative values with the result of AtenSizeIntOp, which
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// is known to always be non-negative.
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// Fold comparisons of AtenSizeIntOp against negative values.
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// AtenSizeIntOp is known to always be non-negative.
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if (rhsIsConstant && rhs < 0) {
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// We can return `comparator(0, -1)` here because of the property:
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// If x >= 0 && y < 0, then:
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@ -837,10 +838,20 @@ static OpFoldResult intComparatorFoldHelper(OpTy op,
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if (auto size = lhsValue.getDefiningOp<AtenSizeIntOp>())
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return getI1IntegerAttr(op->getContext(), comparator(0, -1));
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}
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// A special case of importance: size.int >= 0 ==> True.
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if (rhsIsConstant && rhs == 0 && isa<AtenGeIntOp>(op)) {
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if (auto size = lhsValue.getDefiningOp<AtenSizeIntOp>())
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// Fold comparisons of AtenSizeIntOp against 0:
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// - torch.aten.size.int >= 0 ==> True.
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// - torch.aten.size.int < 0 ==> False.
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// (and the operand-swapped versions of the above)
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if (rhsIsConstant && rhs == 0) {
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if (auto size = lhsValue.getDefiningOp<AtenSizeIntOp>()) {
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// >= 0 comparison.
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if (comparator(0, 0) && comparator(1, 0))
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return getI1IntegerAttr(op->getContext(), true);
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// < 0 comparison.
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if (!comparator(0, 0) && comparator(-1, 0) && !comparator(1, 0))
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return getI1IntegerAttr(op->getContext(), false);
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}
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}
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return nullptr;
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@ -318,7 +318,9 @@ def slice(self: List[int], dim: int, start: Optional[int], end: Optional[int], s
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end_val += self[dim]
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if start_val < 0:
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start_val = 0
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elif start_val >= self[dim]:
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# TODO: Remove this comment after https://github.com/pytorch/pytorch/pull/74980
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# is merged to incorporate our local edit here.
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elif start_val > self[dim]:
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start_val = self[dim]
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if end_val < start_val:
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end_val = start_val
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@ -375,17 +375,39 @@ func @torch.aten.gt.float$evaluate_to_false() -> !torch.bool {
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}
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// CHECK-LABEL: func @torch.aten.ge.int$of_size.int(
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// CHECK-SAME: %[[ARG:.*]]: !torch.tensor) -> !torch.bool {
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// CHECK: %[[TRUE:.*]] = torch.constant.bool true
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// CHECK: return %[[TRUE]] : !torch.bool
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func @torch.aten.ge.int$of_size.int(%arg0: !torch.tensor) -> !torch.bool {
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// CHECK-LABEL: func @comparison_with_torch.aten.size.int(
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// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[?,2],unk>) -> (!torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool) {
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// CHECK: %[[SIZE:.*]] = torch.aten.size.int %[[ARG0]], %int0 : !torch.vtensor<[?,2],unk>, !torch.int -> !torch.int
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// CHECK: %[[GE_0_LHS:.*]] = torch.aten.ge.int %int0, %[[SIZE]] : !torch.int, !torch.int -> !torch.bool
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// CHECK: %[[LT_0_LHS:.*]] = torch.aten.lt.int %int0, %[[SIZE]] : !torch.int, !torch.int -> !torch.bool
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// CHECK: %[[EQ_0_LHS:.*]] = torch.aten.eq.int %int0, %[[SIZE]] : !torch.int, !torch.int -> !torch.bool
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// CHECK: %[[NE_0_LHS:.*]] = torch.aten.ne.int %int0, %[[SIZE]] : !torch.int, !torch.int -> !torch.bool
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// CHECK: %[[GT_0_RHS:.*]] = torch.aten.gt.int %[[SIZE]], %int0 : !torch.int, !torch.int -> !torch.bool
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// CHECK: %[[LE_0_RHS:.*]] = torch.aten.le.int %[[SIZE]], %int0 : !torch.int, !torch.int -> !torch.bool
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// CHECK: %[[EQ_0_RHS:.*]] = torch.aten.eq.int %[[SIZE]], %int0 : !torch.int, !torch.int -> !torch.bool
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// CHECK: %[[NE_0_RHS:.*]] = torch.aten.ne.int %[[SIZE]], %int0 : !torch.int, !torch.int -> !torch.bool
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// CHECK: return %true, %true, %false, %false, %[[GE_0_LHS]], %[[LT_0_LHS]], %[[EQ_0_LHS]], %[[NE_0_LHS]], %[[GT_0_RHS]], %[[LE_0_RHS]], %[[EQ_0_RHS]], %[[NE_0_RHS]] : !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool
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func @comparison_with_torch.aten.size.int(%arg0: !torch.vtensor<[?,2],unk>) -> (!torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool) {
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%int0 = torch.constant.int 0
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%0 = torch.aten.size.int %arg0, %int0 : !torch.tensor, !torch.int -> !torch.int
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%1 = torch.aten.ge.int %0, %int0 : !torch.int, !torch.int -> !torch.bool
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return %1 : !torch.bool
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%0 = torch.aten.size.int %arg0, %int0 : !torch.vtensor<[?,2],unk>, !torch.int -> !torch.int
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// Cases we can fold.
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%1 = torch.aten.le.int %int0, %0 : !torch.int, !torch.int -> !torch.bool
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%2 = torch.aten.ge.int %0, %int0 : !torch.int, !torch.int -> !torch.bool
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%3 = torch.aten.lt.int %0, %int0 : !torch.int, !torch.int -> !torch.bool
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%4 = torch.aten.gt.int %int0, %0 : !torch.int, !torch.int -> !torch.bool
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// Cases we cannot fold.
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%5 = torch.aten.ge.int %int0, %0 : !torch.int, !torch.int -> !torch.bool
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%6 = torch.aten.lt.int %int0, %0 : !torch.int, !torch.int -> !torch.bool
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%7 = torch.aten.eq.int %int0, %0 : !torch.int, !torch.int -> !torch.bool
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%8 = torch.aten.ne.int %int0, %0 : !torch.int, !torch.int -> !torch.bool
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%9 = torch.aten.gt.int %0, %int0 : !torch.int, !torch.int -> !torch.bool
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%10 = torch.aten.le.int %0, %int0 : !torch.int, !torch.int -> !torch.bool
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%11 = torch.aten.eq.int %0, %int0 : !torch.int, !torch.int -> !torch.bool
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%12 = torch.aten.ne.int %0, %int0 : !torch.int, !torch.int -> !torch.bool
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return %1, %2, %3, %4, %5, %6, %7, %8, %9, %10, %11, %12 : !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool, !torch.bool
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}
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// CHECK-LABEL: func @torch.aten.eq.float$different_value() -> !torch.bool {
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// CHECK: %[[FALSE:.*]] = torch.constant.bool false
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// CHECK: return %[[FALSE]] : !torch.bool
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