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[mlir][tosa] Adds a canonicalization to the transpose op if the perms are a no op

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Reviewed By: rsuderman

Differential Revision: https://reviews.llvm.org/D112037
This commit is contained in:
not-jenni
2021-10-18 16:22:01 -07:00
committed by Rob Suderman
parent 87c016078a
commit 4ada6c2aaf
2 changed files with 40 additions and 1 deletions
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28
mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
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@@ -222,9 +222,37 @@ struct ConstantTransposeOptimization
}
};
struct NoOpOptimization : public OpRewritePattern<tosa::TransposeOp> {
using OpRewritePattern::OpRewritePattern;
LogicalResult matchAndRewrite(tosa::TransposeOp op,
PatternRewriter &rewriter) const override {
auto perm = op.perms();
DenseIntElementsAttr permAttr;
if (!matchPattern(perm, m_Constant(&permAttr))) {
return failure();
}
SmallVector<int64_t> permValues = llvm::to_vector<6>(
llvm::map_range(permAttr.getValues<APInt>(),
[](const APInt &val) { return val.getSExtValue(); }));
for (int i = 0, s = permValues.size(); i < s; i++) {
if (i != permValues[i]) {
return failure();
}
}
rewriter.replaceOp(op, op.input1());
return success();
}
};
void TransposeOp::getCanonicalizationPatterns(OwningRewritePatternList &results,
MLIRContext *context) {
results.insert<ConstantTransposeOptimization>(context);
results.insert<NoOpOptimization>(context);
}
//===----------------------------------------------------------------------===//

13
mlir/test/Dialect/Tosa/canonicalize.mlir
View File

@@ -233,7 +233,7 @@ func @transpose_nofold(%arg0: tensor<3x3xf32>) -> tensor<3x3xf32> {
// CHECK-LABEL: @transpose_nofold_shape
func @transpose_nofold_shape(%arg0: tensor<3x4xf32>) -> tensor<?x?xf32> {
// CHECK: "tosa.transpose"
%0 = arith.constant dense<[0, 1]> : tensor<2xi32>
%0 = arith.constant dense<[1, 0]> : tensor<2xi32>
%1 = "tosa.transpose"(%arg0, %0) { perms = [1, 0] }: (tensor<3x4xf32>, tensor<2xi32>) -> tensor<?x?xf32>
return %1 : tensor<?x?xf32>
}
@@ -325,3 +325,14 @@ func @transpose_nofold_quantized_types() -> tensor<1x1x16x1x!quant.uniform<i8<-1
%0 = "tosa.transpose"(%input, %perms) : (tensor<1x1x1x16xi8>, tensor<4xi32>) -> tensor<1x1x16x1x!quant.uniform<i8<-127:127>:f32:3, {1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,2.100000e+00,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01}>>
return %0: tensor<1x1x16x1x!quant.uniform<i8<-127:127>:f32:3, {1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,2.100000e+00,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01,1.000000e-01}>>
}
// -----
// CHECK-LABEL: @transpose_no_op
func @transpose_no_op(%arg0: tensor<3x4x5x6xf32>) -> tensor<3x4x5x6xf32> {
// CHECK: return %arg0
// CHECK-NOT: tosa.transpose
%perms = "tosa.const"() {value = dense<[0, 1, 2, 3]> : tensor<4xi32>} : () -> tensor<4xi32>
%1 = "tosa.transpose"(%arg0, %perms) : (tensor<3x4x5x6xf32>, tensor<4xi32>) -> tensor<3x4x5x6xf32>
return %1 : tensor<3x4x5x6xf32>
}