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[mlir][vector] Fix illegal vector.transfer + tensor.insert/extract_slice folding 

vector.transfer operations do not have rank-reducing semantics.

Bail on illegal rank-reduction: we need to check that the rank-reduced
dims are exactly the leading dims. I.e. the following is illegal:
```
   %0 = vector.transfer_write %v, %t[0,0], %cst :
     vector<2x4xf32>, tensor<2x4xf32>
   %1 = tensor.insert_slice %0 into %tt[0,0,0][2,1,4][1,1,1] :
     tensor<2x4xf32> into tensor<2x1x4xf32>
```

Cannot fold into:
```
   %0 = vector.transfer_write %v, %t[0,0,0], %cst :
     vector<2x4xf32>, tensor<2x1x4xf32>
```
For this, check the trailing `vectorRank` dims of the insert_slice result
tensor match the trailing dims of the inferred result tensor.

Differential Revision: https://reviews.llvm.org/D116409
This commit is contained in:
Nicolas Vasilache 2021-12-30 12:41:18 +00:00
parent 84b285d6eb
commit 2e69f4f012
2 changed files with 84 additions and 1 deletions
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59
mlir/lib/Dialect/Vector/VectorOps.cpp
View File

@ -24,6 +24,7 @@
#include "mlir/IR/BlockAndValueMapping.h"
#include "mlir/IR/Builders.h"
#include "mlir/IR/BuiltinOps.h"
#include "mlir/IR/BuiltinTypes.h"
#include "mlir/IR/DialectImplementation.h"
#include "mlir/IR/OpImplementation.h"
#include "mlir/IR/PatternMatch.h"
@ -2783,8 +2784,35 @@ public:
if (!extractOp.hasUnitStride())
return failure();
// Bail on illegal rank-reduction: we need to check that the rank-reduced
// dims are exactly the leading dims. I.e. the following is illegal:
// ```
// %0 = tensor.extract_slice %t[0,0,0][2,1,4][1,1,1] :
// tensor<2x1x4xf32> to tensor<2x4xf32>
// %1 = vector.transfer_read %0[0,0], %cst :
// tensor<2x4xf32>, vector<2x4xf32>
// ```
//
// Cannot fold into:
// ```
// %0 = vector.transfer_read %t[0,0,0], %cst :
// tensor<2x1x4xf32>, vector<2x4xf32>
// ```
// For this, check the trailing `vectorRank` dims of the extract_slice
// result tensor match the trailing dims of the inferred result tensor.
int64_t rankReduced =
extractOp.getSourceType().getRank() - extractOp.getType().getRank();
int64_t vectorRank = xferOp.getVectorType().getRank();
RankedTensorType inferredDestTensorType =
tensor::ExtractSliceOp::inferResultType(
extractOp.getSourceType(), extractOp.getMixedOffsets(),
extractOp.getMixedSizes(), extractOp.getMixedStrides());
auto actualDestTensorShape = extractOp.getType().getShape();
if (rankReduced > 0 &&
actualDestTensorShape.take_back(vectorRank) !=
inferredDestTensorType.getShape().take_back(vectorRank))
return failure();
SmallVector<Value> newIndices;
// In case this is a rank-reducing ExtractSliceOp, copy rank-reduced
// indices first.
@ -3168,7 +3196,7 @@ public:
if (xferOp.mask())
return failure();
// Fold only if the TransferWriteOp completely overwrites the `source` with
// a vector. I.e., the result of the TransferWriteOp is a new tensor who's
// a vector. I.e., the result of the TransferWriteOp is a new tensor whose
// content is the data of the vector.
if (!llvm::equal(xferOp.getVectorType().getShape(),
xferOp.getShapedType().getShape()))
@ -3176,6 +3204,35 @@ public:
if (!xferOp.permutation_map().isIdentity())
return failure();
// Bail on illegal rank-reduction: we need to check that the rank-reduced
// dims are exactly the leading dims. I.e. the following is illegal:
// ```
// %0 = vector.transfer_write %v, %t[0,0], %cst :
// vector<2x4xf32>, tensor<2x4xf32>
// %1 = tensor.insert_slice %0 into %tt[0,0,0][2,1,4][1,1,1] :
// tensor<2x4xf32> into tensor<2x1x4xf32>
// ```
//
// Cannot fold into:
// ```
// %0 = vector.transfer_write %v, %t[0,0,0], %cst :
// vector<2x4xf32>, tensor<2x1x4xf32>
// ```
// For this, check the trailing `vectorRank` dims of the insert_slice result
// tensor match the trailing dims of the inferred result tensor.
int64_t rankReduced =
insertOp.getType().getRank() - insertOp.getSourceType().getRank();
int64_t vectorRank = xferOp.getVectorType().getRank();
RankedTensorType inferredSourceTensorType =
tensor::ExtractSliceOp::inferResultType(
insertOp.getType(), insertOp.getMixedOffsets(),
insertOp.getMixedSizes(), insertOp.getMixedStrides());
auto actualSourceTensorShape = insertOp.getSourceType().getShape();
if (rankReduced > 0 &&
actualSourceTensorShape.take_back(vectorRank) !=
inferredSourceTensorType.getShape().take_back(vectorRank))
return failure();
SmallVector<Value> indices = getValueOrCreateConstantIndexOp(
rewriter, insertOp.getLoc(), insertOp.getMixedOffsets());
SmallVector<bool> inBounds(xferOp.getTransferRank(), true);

26
mlir/test/Dialect/Vector/canonicalize.mlir
View File

@ -995,6 +995,20 @@ func @transfer_read_of_extract_slice_rank_reducing(%t : tensor<?x?x?xf32>, %s1 :
// -----
// CHECK-LABEL: func @transfer_read_of_extract_slice_illegal_rank_reducing(
// CHECK: extract_slice
// CHECK: vector.transfer_read
func @transfer_read_of_extract_slice_illegal_rank_reducing(%t : tensor<?x?x?xf32>, %s1 : index, %s2 : index) -> vector<5x6xf32> {
%c3 = arith.constant 3 : index
%c4 = arith.constant 4 : index
%cst = arith.constant 0.0 : f32
%0 = tensor.extract_slice %t[5, %s1, 6] [%s2, 1, 12] [1, 1, 1] : tensor<?x?x?xf32> to tensor<?x12xf32>
%1 = vector.transfer_read %0[%c3, %c4], %cst {in_bounds = [true, true]} : tensor<?x12xf32>, vector<5x6xf32>
return %1 : vector<5x6xf32>
}
// -----
// CHECK-LABEL: func @insert_slice_of_transfer_write(
// CHECK-SAME: %[[t1:.*]]: tensor<?x12xf32>, %[[v:.*]]: vector<5x6xf32>, %[[s:.*]]: index
// CHECK: %[[c3:.*]] = arith.constant 3 : index
@ -1009,6 +1023,18 @@ func @insert_slice_of_transfer_write(%t1 : tensor<?x12xf32>, %v : vector<5x6xf32
// -----
// CHECK-LABEL: func @insert_slice_of_transfer_write_illegal_rank_extending(
// CHECK: vector.transfer_write
// CHECK: insert_slice
func @insert_slice_of_transfer_write_illegal_rank_extending(%t1 : tensor<?x?x12xf32>, %v : vector<5x6xf32>, %s : index, %t2 : tensor<5x6xf32>) -> tensor<?x?x12xf32> {
%c0 = arith.constant 0 : index
%0 = vector.transfer_write %v, %t2[%c0, %c0] {in_bounds = [true, true]} : vector<5x6xf32>, tensor<5x6xf32>
%1 = tensor.insert_slice %0 into %t1[4, 3, %s] [5, 1, 6] [1, 1, 1] : tensor<5x6xf32> into tensor<?x?x12xf32>
return %1 : tensor<?x?x12xf32>
}
// -----
// CHECK-LABEL: func @insert_slice_of_transfer_write_rank_extending(
// CHECK-SAME: %[[t1:.*]]: tensor<?x?x12xf32>, %[[v:.*]]: vector<5x6xf32>, %[[s:.*]]: index
// CHECK-DAG: %[[c3:.*]] = arith.constant 3 : index