[Mlir-commits] [mlir] f98e1c4 - [mlir][sparse] add one extra index test on f32 matrix
Aart Bik
llvmlistbot at llvm.org
Tue Mar 15 17:43:38 PDT 2022
Author: Aart Bik
Date: 2022-03-15T17:43:30-07:00
New Revision: f98e1c40ca9f3e74f85d6361a24f63ce184e737f
URL: https://github.com/llvm/llvm-project/commit/f98e1c40ca9f3e74f85d6361a24f63ce184e737f
DIFF: https://github.com/llvm/llvm-project/commit/f98e1c40ca9f3e74f85d6361a24f63ce184e737f.diff
LOG: [mlir][sparse] add one extra index test on f32 matrix
Reviewed By: bixia
Differential Revision: https://reviews.llvm.org/D121743
Added:
Modified:
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index.mlir
Removed:
################################################################################
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index.mlir
index cd5a5aee75d2c..765dedb02346f 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index.mlir
@@ -119,12 +119,31 @@ module {
return %r : tensor<3x4xi64, #SparseMatrix>
}
+ func @add_outer_2d(%arg0: tensor<2x3xf32, #SparseMatrix>)
+ -> tensor<2x3xf32, #SparseMatrix> {
+ %c2 = arith.constant 2 : index
+ %c3 = arith.constant 3 : index
+ %0 = sparse_tensor.init[%c2, %c3] : tensor<2x3xf32, #SparseMatrix>
+ %1 = linalg.generic #trait_2d
+ ins(%arg0 : tensor<2x3xf32, #SparseMatrix>)
+ outs(%0 : tensor<2x3xf32, #SparseMatrix>) {
+ ^bb0(%arg1: f32, %arg2: f32):
+ %2 = linalg.index 0 : index
+ %3 = arith.index_cast %2 : index to i64
+ %4 = arith.uitofp %3 : i64 to f32
+ %5 = arith.addf %arg1, %4 : f32
+ linalg.yield %5 : f32
+ } -> tensor<2x3xf32, #SparseMatrix>
+ return %1 : tensor<2x3xf32, #SparseMatrix>
+ }
+
//
// Main driver.
//
func @entry() {
%c0 = arith.constant 0 : index
%du = arith.constant -1 : i64
+ %df = arith.constant -1.0 : f32
// Setup input sparse vector.
%v1 = arith.constant sparse<[[2], [4]], [ 10, 20]> : tensor<8xi64>
@@ -144,6 +163,10 @@ module {
[ 1, 1, 3, 4 ] ]> : tensor<3x4xi64>
%dm = sparse_tensor.convert %m2 : tensor<3x4xi64> to tensor<3x4xi64, #SparseMatrix>
+ // Setup input sparse f32 matrix.
+ %mf32 = arith.constant sparse<[[0,1], [1,2]], [10.0, 41.0]> : tensor<2x3xf32>
+ %sf32 = sparse_tensor.convert %mf32 : tensor<2x3xf32> to tensor<2x3xf32, #SparseMatrix>
+
// Call the kernels.
%0 = call @sparse_index_1d_conj(%sv) : (tensor<8xi64, #SparseVector>)
-> tensor<8xi64, #SparseVector>
@@ -213,6 +236,19 @@ module {
sparse_tensor.release %6 : tensor<3x4xi64, #SparseMatrix>
sparse_tensor.release %7 : tensor<3x4xi64, #SparseMatrix>
+ //
+ // Call the f32 kernel, verify the result, release the resources.
+ //
+ // CHECK-NEXT: ( 0, 10, 0, 1, 1, 42 )
+ //
+ %100 = call @add_outer_2d(%sf32) : (tensor<2x3xf32, #SparseMatrix>)
+ -> tensor<2x3xf32, #SparseMatrix>
+ %101 = sparse_tensor.values %100 : tensor<2x3xf32, #SparseMatrix> to memref<?xf32>
+ %102 = vector.transfer_read %101[%c0], %df: memref<?xf32>, vector<6xf32>
+ vector.print %102 : vector<6xf32>
+ sparse_tensor.release %sf32 : tensor<2x3xf32, #SparseMatrix>
+ sparse_tensor.release %100 : tensor<2x3xf32, #SparseMatrix>
+
return
}
}
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