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Sep 15, 2023
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[mlir][sparse][tensor] replace bufferization with empty tensor #66450

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ea656a5
[mlir][sparse][tensor] replace bufferization with empty tensor
aartbik Sep 15, 2023
4241557
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aartbik Sep 15, 2023
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2 changes: 1 addition & 1 deletion mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output.mlir
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Expand Up @@ -71,7 +71,7 @@ module {
%c2 = arith.constant 2.0 : f64
%d0 = tensor.dim %arga, %c0 : tensor<?x?xf64, #SparseMatrix>
%d1 = tensor.dim %arga, %c1 : tensor<?x?xf64, #SparseMatrix>
%init = bufferization.alloc_tensor(%d0, %d1) : tensor<?x?xf64, #DenseMatrix>
%init = tensor.empty(%d0, %d1) : tensor<?x?xf64, #DenseMatrix>
%0 = linalg.generic #trait_assign
ins(%arga: tensor<?x?xf64, #SparseMatrix>)
outs(%init: tensor<?x?xf64, #DenseMatrix>) {
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_bf16.mlir
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Expand Up @@ -48,7 +48,7 @@ module {
%argb: tensor<?xbf16, #SparseVector>) -> tensor<?xbf16, #DenseVector> {
%c = arith.constant 0 : index
%d = tensor.dim %arga, %c : tensor<?xbf16, #SparseVector>
%xv = bufferization.alloc_tensor (%d) : tensor<?xbf16, #DenseVector>
%xv = tensor.empty (%d) : tensor<?xbf16, #DenseVector>
%0 = linalg.generic #trait_vec_op
ins(%arga, %argb: tensor<?xbf16, #SparseVector>, tensor<?xbf16, #SparseVector>)
outs(%xv: tensor<?xbf16, #DenseVector>) {
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir
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Expand Up @@ -49,7 +49,7 @@ module {
%argb: tensor<?xf16, #SparseVector>) -> tensor<?xf16, #DenseVector> {
%c = arith.constant 0 : index
%d = tensor.dim %arga, %c : tensor<?xf16, #SparseVector>
%xv = bufferization.alloc_tensor (%d) : tensor<?xf16, #DenseVector>
%xv = tensor.empty (%d) : tensor<?xf16, #DenseVector>
%0 = linalg.generic #trait_vec_op
ins(%arga, %argb: tensor<?xf16, #SparseVector>, tensor<?xf16, #SparseVector>)
outs(%xv: tensor<?xf16, #DenseVector>) {
Expand Down
8 changes: 4 additions & 4 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/dual_sparse_conv_2d.mlir
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Expand Up @@ -51,7 +51,7 @@ module {

func.func @conv2d_all_sparse_DCSR(%input: tensor<8x8xi32, #DCSR>,
%filter: tensor<3x3xi32, #DCSR>) -> tensor<6x6xi32, #DCSR> {
%s = bufferization.alloc_tensor() : tensor<6x6xi32, #DCSR>
%s = tensor.empty() : tensor<6x6xi32, #DCSR>
%0 = linalg.conv_2d
ins (%input, %filter: tensor<8x8xi32, #DCSR>, tensor<3x3xi32, #DCSR>)
outs (%s: tensor<6x6xi32, #DCSR>) -> tensor<6x6xi32, #DCSR>
Expand All @@ -60,7 +60,7 @@ module {

func.func @conv2d_all_sparse_CSR(%input: tensor<8x8xi32, #CSR>,
%filter: tensor<3x3xi32, #CSR>) -> tensor<6x6xi32, #CSR> {
%s = bufferization.alloc_tensor() : tensor<6x6xi32, #CSR>
%s = tensor.empty() : tensor<6x6xi32, #CSR>
%0 = linalg.conv_2d
ins (%input, %filter: tensor<8x8xi32, #CSR>, tensor<3x3xi32, #CSR>)
outs (%s: tensor<6x6xi32, #CSR>) -> tensor<6x6xi32, #CSR>
Expand All @@ -69,7 +69,7 @@ module {

func.func @conv2d_all_sparse_CD(%input: tensor<8x8xi32, #CDR>,
%filter: tensor<3x3xi32, #CDR>) -> tensor<6x6xi32, #CDR> {
%s = bufferization.alloc_tensor() : tensor<6x6xi32, #CDR>
%s = tensor.empty() : tensor<6x6xi32, #CDR>
%0 = linalg.conv_2d
ins (%input, %filter: tensor<8x8xi32, #CDR>, tensor<3x3xi32, #CDR>)
outs (%s: tensor<6x6xi32, #CDR>) -> tensor<6x6xi32, #CDR>
Expand All @@ -78,7 +78,7 @@ module {

func.func @conv2d_all_sparse_CSC(%input: tensor<8x8xi32, #CSC>,
%filter: tensor<3x3xi32, #CSC>) -> tensor<6x6xi32, #CSC> {
%s = bufferization.alloc_tensor() : tensor<6x6xi32, #CSC>
%s = tensor.empty() : tensor<6x6xi32, #CSC>
%0 = linalg.conv_2d
ins (%input, %filter: tensor<8x8xi32, #CSC>, tensor<3x3xi32, #CSC>)
outs (%s: tensor<6x6xi32, #CSC>) -> tensor<6x6xi32, #CSC>
Expand Down
4 changes: 2 additions & 2 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_abs.mlir
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Expand Up @@ -46,7 +46,7 @@ module {
-> tensor<?xf64, #SparseVector> {
%c0 = arith.constant 0 : index
%d = tensor.dim %arg0, %c0 : tensor<?xf64, #SparseVector>
%xin = bufferization.alloc_tensor(%d) : tensor<?xf64, #SparseVector>
%xin = tensor.empty(%d) : tensor<?xf64, #SparseVector>
%0 = linalg.generic #trait_op
ins(%arg0: tensor<?xf64, #SparseVector>)
outs(%xin: tensor<?xf64, #SparseVector>) {
Expand All @@ -61,7 +61,7 @@ module {
-> tensor<?xi32, #SparseVector> {
%c0 = arith.constant 0 : index
%d = tensor.dim %arg0, %c0 : tensor<?xi32, #SparseVector>
%xin = bufferization.alloc_tensor(%d) : tensor<?xi32, #SparseVector>
%xin = tensor.empty(%d) : tensor<?xi32, #SparseVector>
%0 = linalg.generic #trait_op
ins(%arg0: tensor<?xi32, #SparseVector>)
outs(%xin: tensor<?xi32, #SparseVector>) {
Expand Down
22 changes: 11 additions & 11 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_binary.mlir
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Expand Up @@ -73,7 +73,7 @@ module {
%argb: tensor<?xi32, #SparseVector>) -> tensor<?xi32, #SparseVector> {
%c = arith.constant 0 : index
%d = tensor.dim %arga, %c : tensor<?xi32, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xi32, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xi32, #SparseVector>
%0 = linalg.generic #trait_vec_op
ins(%arga, %argb: tensor<?xi32, #SparseVector>, tensor<?xi32, #SparseVector>)
outs(%xv: tensor<?xi32, #SparseVector>) {
Expand All @@ -97,7 +97,7 @@ module {
%argb: tensor<?xf64>) -> tensor<?xf64, #SparseVector> {
%c = arith.constant 0 : index
%d = tensor.dim %arga, %c : tensor<?xf64, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xf64, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xf64, #SparseVector>
%0 = linalg.generic #trait_vec_op
ins(%arga, %argb: tensor<?xf64, #SparseVector>, tensor<?xf64>)
outs(%xv: tensor<?xf64, #SparseVector>) {
Expand All @@ -121,7 +121,7 @@ module {
%argb: tensor<?xf64, #SparseVector>) -> tensor<?xf64, #SparseVector> {
%c = arith.constant 0 : index
%d = tensor.dim %arga, %c : tensor<?xf64, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xf64, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xf64, #SparseVector>
%0 = linalg.generic #trait_vec_op
ins(%arga, %argb: tensor<?xf64, #SparseVector>, tensor<?xf64, #SparseVector>)
outs(%xv: tensor<?xf64, #SparseVector>) {
Expand All @@ -139,7 +139,7 @@ module {
func.func @vector_index(%arga: tensor<?xf64, #SparseVector>) -> tensor<?xi32, #SparseVector> {
%c = arith.constant 0 : index
%d = tensor.dim %arga, %c : tensor<?xf64, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xi32, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xi32, #SparseVector>
%0 = linalg.generic #trait_vec_scale
ins(%arga: tensor<?xf64, #SparseVector>)
outs(%xv: tensor<?xi32, #SparseVector>) {
Expand All @@ -166,7 +166,7 @@ module {
%c1 = arith.constant 1 : index
%d0 = tensor.dim %arga, %c0 : tensor<?x?xf64, #DCSR>
%d1 = tensor.dim %arga, %c1 : tensor<?x?xf64, #DCSR>
%xv = bufferization.alloc_tensor(%d0, %d1) : tensor<?x?xf64, #DCSR>
%xv = tensor.empty(%d0, %d1) : tensor<?x?xf64, #DCSR>
%0 = linalg.generic #trait_mat_op
ins(%arga, %argb: tensor<?x?xf64, #DCSR>, tensor<?x?xf64, #DCSR>)
outs(%xv: tensor<?x?xf64, #DCSR>) {
Expand All @@ -191,7 +191,7 @@ module {
// Tensor addition (use semi-ring binary operation).
func.func @add_tensor_1(%A: tensor<4x4xf64, #DCSR>,
%B: tensor<4x4xf64, #DCSR>) -> tensor<4x4xf64, #DCSR> {
%C = bufferization.alloc_tensor() : tensor<4x4xf64, #DCSR>
%C = tensor.empty() : tensor<4x4xf64, #DCSR>
%0 = linalg.generic #trait_mat_op
ins(%A, %B: tensor<4x4xf64, #DCSR>,
tensor<4x4xf64, #DCSR>)
Expand All @@ -213,7 +213,7 @@ module {
// Same as @add_tensor_1, but use sparse_tensor.yield instead of identity to yield value.
func.func @add_tensor_2(%A: tensor<4x4xf64, #DCSR>,
%B: tensor<4x4xf64, #DCSR>) -> tensor<4x4xf64, #DCSR> {
%C = bufferization.alloc_tensor() : tensor<4x4xf64, #DCSR>
%C = tensor.empty() : tensor<4x4xf64, #DCSR>
%0 = linalg.generic #trait_mat_op
ins(%A, %B: tensor<4x4xf64, #DCSR>,
tensor<4x4xf64, #DCSR>)
Expand Down Expand Up @@ -241,7 +241,7 @@ module {
// Performs triangular add/sub operation (using semi-ring binary op).
func.func @triangular(%A: tensor<4x4xf64, #DCSR>,
%B: tensor<4x4xf64, #DCSR>) -> tensor<4x4xf64, #DCSR> {
%C = bufferization.alloc_tensor() : tensor<4x4xf64, #DCSR>
%C = tensor.empty() : tensor<4x4xf64, #DCSR>
%0 = linalg.generic #trait_mat_op
ins(%A, %B: tensor<4x4xf64, #DCSR>,
tensor<4x4xf64, #DCSR>)
Expand Down Expand Up @@ -274,7 +274,7 @@ module {
// Perform sub operation (using semi-ring binary op) with a constant threshold.
func.func @sub_with_thres(%A: tensor<4x4xf64, #DCSR>,
%B: tensor<4x4xf64, #DCSR>) -> tensor<4x4xf64, #DCSR> {
%C = bufferization.alloc_tensor() : tensor<4x4xf64, #DCSR>
%C = tensor.empty() : tensor<4x4xf64, #DCSR>
// Defines out-block constant bounds.
%thres_out_up = arith.constant 2.0 : f64
%thres_out_lo = arith.constant -2.0 : f64
Expand Down Expand Up @@ -323,7 +323,7 @@ module {
// Performs isEqual only on intersecting elements.
func.func @intersect_equal(%A: tensor<4x4xf64, #DCSR>,
%B: tensor<4x4xf64, #DCSR>) -> tensor<4x4xi8, #DCSR> {
%C = bufferization.alloc_tensor() : tensor<4x4xi8, #DCSR>
%C = tensor.empty() : tensor<4x4xi8, #DCSR>
%0 = linalg.generic #trait_mat_op
ins(%A, %B: tensor<4x4xf64, #DCSR>,
tensor<4x4xf64, #DCSR>)
Expand All @@ -346,7 +346,7 @@ module {
// Keeps values on left, negate value on right, ignore value when overlapping.
func.func @only_left_right(%A: tensor<4x4xf64, #DCSR>,
%B: tensor<4x4xf64, #DCSR>) -> tensor<4x4xf64, #DCSR> {
%C = bufferization.alloc_tensor() : tensor<4x4xf64, #DCSR>
%C = tensor.empty() : tensor<4x4xf64, #DCSR>
%0 = linalg.generic #trait_mat_op
ins(%A, %B: tensor<4x4xf64, #DCSR>,
tensor<4x4xf64, #DCSR>)
Expand Down
4 changes: 2 additions & 2 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_cmp.mlir
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Expand Up @@ -66,7 +66,7 @@ module {

func.func @cmp_lhs_sparse(%arga: tensor<4x4xf64, #DCSR>,
%argb: tensor<4x4xf64>) -> tensor<4x4xi8, #DCSR> {
%argx = bufferization.alloc_tensor() : tensor<4x4xi8, #DCSR>
%argx = tensor.empty() : tensor<4x4xi8, #DCSR>
%0 = linalg.generic #trait
ins(%arga, %argb: tensor<4x4xf64, #DCSR>, tensor<4x4xf64>)
outs(%argx: tensor<4x4xi8, #DCSR>) {
Expand All @@ -80,7 +80,7 @@ module {

func.func @cmp_all_sparse(%arga: tensor<4x4xf64, #DCSR>,
%argb: tensor<4x4xf64, #DCSR>) -> tensor<4x4xi8, #DCSR> {
%argx = bufferization.alloc_tensor() : tensor<4x4xi8, #DCSR>
%argx = tensor.empty() : tensor<4x4xi8, #DCSR>
%0 = linalg.generic #trait
ins(%arga, %argb: tensor<4x4xf64, #DCSR>, tensor<4x4xf64, #DCSR>)
outs(%argx: tensor<4x4xi8, #DCSR>) {
Expand Down
4 changes: 2 additions & 2 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_codegen_dim.mlir
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Expand Up @@ -43,8 +43,8 @@ module {
%c1 = arith.constant 1 : index
%c2 = arith.constant 2 : index
%c3 = arith.constant 3 : index
%t1 = bufferization.alloc_tensor() : tensor<4x5xf64, #DCSR>
%t2 = bufferization.alloc_tensor(%c2, %c3) : tensor<?x?xf64, #DCSR>
%t1 = tensor.empty() : tensor<4x5xf64, #DCSR>
%t2 = tensor.empty(%c2, %c3) : tensor<?x?xf64, #DCSR>

%d1_0 = tensor.dim %t1, %c0 : tensor<4x5xf64, #DCSR>
%d2_0 = tensor.dim %t2, %c0 : tensor<?x?xf64, #DCSR>
Expand Down
4 changes: 2 additions & 2 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_complex32.mlir
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Expand Up @@ -48,7 +48,7 @@ module {
-> tensor<?xcomplex<f32>, #SparseVector> {
%c = arith.constant 0 : index
%d = tensor.dim %arga, %c : tensor<?xcomplex<f32>, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xcomplex<f32>, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xcomplex<f32>, #SparseVector>
%0 = linalg.generic #trait_op
ins(%arga, %argb: tensor<?xcomplex<f32>, #SparseVector>,
tensor<?xcomplex<f32>, #SparseVector>)
Expand All @@ -65,7 +65,7 @@ module {
-> tensor<?xcomplex<f32>, #SparseVector> {
%c = arith.constant 0 : index
%d = tensor.dim %arga, %c : tensor<?xcomplex<f32>, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xcomplex<f32>, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xcomplex<f32>, #SparseVector>
%0 = linalg.generic #trait_op
ins(%arga, %argb: tensor<?xcomplex<f32>, #SparseVector>,
tensor<?xcomplex<f32>, #SparseVector>)
Expand Down
4 changes: 2 additions & 2 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_complex64.mlir
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Expand Up @@ -45,7 +45,7 @@ module {
-> tensor<?xcomplex<f64>, #SparseVector> {
%c = arith.constant 0 : index
%d = tensor.dim %arga, %c : tensor<?xcomplex<f64>, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xcomplex<f64>, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xcomplex<f64>, #SparseVector>
%0 = linalg.generic #trait_op
ins(%arga, %argb: tensor<?xcomplex<f64>, #SparseVector>,
tensor<?xcomplex<f64>, #SparseVector>)
Expand All @@ -62,7 +62,7 @@ module {
-> tensor<?xcomplex<f64>, #SparseVector> {
%c = arith.constant 0 : index
%d = tensor.dim %arga, %c : tensor<?xcomplex<f64>, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xcomplex<f64>, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xcomplex<f64>, #SparseVector>
%0 = linalg.generic #trait_op
ins(%arga, %argb: tensor<?xcomplex<f64>, #SparseVector>,
tensor<?xcomplex<f64>, #SparseVector>)
Expand Down
14 changes: 7 additions & 7 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_complex_ops.mlir
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Expand Up @@ -57,7 +57,7 @@ module {
-> tensor<?xcomplex<f64>, #SparseVector> {
%c0 = arith.constant 0 : index
%d = tensor.dim %arga, %c0 : tensor<?xcomplex<f64>, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xcomplex<f64>, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xcomplex<f64>, #SparseVector>
%0 = linalg.generic #trait_op2
ins(%arga, %argb: tensor<?xcomplex<f64>, #SparseVector>,
tensor<?xcomplex<f64>, #SparseVector>)
Expand All @@ -74,7 +74,7 @@ module {
-> tensor<?xcomplex<f64>, #SparseVector> {
%c0 = arith.constant 0 : index
%d = tensor.dim %arga, %c0 : tensor<?xcomplex<f64>, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xcomplex<f64>, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xcomplex<f64>, #SparseVector>
%0 = linalg.generic #trait_op1
ins(%arga: tensor<?xcomplex<f64>, #SparseVector>)
outs(%xv: tensor<?xcomplex<f64>, #SparseVector>) {
Expand All @@ -89,7 +89,7 @@ module {
-> tensor<?xcomplex<f64>, #SparseVector> {
%c0 = arith.constant 0 : index
%d = tensor.dim %arga, %c0 : tensor<?xcomplex<f64>, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xcomplex<f64>, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xcomplex<f64>, #SparseVector>
%0 = linalg.generic #trait_op1
ins(%arga: tensor<?xcomplex<f64>, #SparseVector>)
outs(%xv: tensor<?xcomplex<f64>, #SparseVector>) {
Expand All @@ -104,7 +104,7 @@ module {
-> tensor<?xcomplex<f64>, #SparseVector> {
%c0 = arith.constant 0 : index
%d = tensor.dim %arga, %c0 : tensor<?xcomplex<f64>, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xcomplex<f64>, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xcomplex<f64>, #SparseVector>
%0 = linalg.generic #trait_op1
ins(%arga: tensor<?xcomplex<f64>, #SparseVector>)
outs(%xv: tensor<?xcomplex<f64>, #SparseVector>) {
Expand All @@ -119,7 +119,7 @@ module {
-> tensor<?xcomplex<f64>, #SparseVector> {
%c0 = arith.constant 0 : index
%d = tensor.dim %arga, %c0 : tensor<?xcomplex<f64>, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xcomplex<f64>, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xcomplex<f64>, #SparseVector>
%0 = linalg.generic #trait_op1
ins(%arga: tensor<?xcomplex<f64>, #SparseVector>)
outs(%xv: tensor<?xcomplex<f64>, #SparseVector>) {
Expand All @@ -135,7 +135,7 @@ module {
-> tensor<?xcomplex<f64>, #SparseVector> {
%c0 = arith.constant 0 : index
%d = tensor.dim %arga, %c0 : tensor<?xcomplex<f64>, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xcomplex<f64>, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xcomplex<f64>, #SparseVector>
%c = complex.constant [2.0 : f64, 0.0 : f64] : complex<f64>
%0 = linalg.generic #trait_op1
ins(%arga: tensor<?xcomplex<f64>, #SparseVector>)
Expand All @@ -151,7 +151,7 @@ module {
-> tensor<?xf64, #SparseVector> {
%c0 = arith.constant 0 : index
%d = tensor.dim %arga, %c0 : tensor<?xcomplex<f64>, #SparseVector>
%xv = bufferization.alloc_tensor(%d) : tensor<?xf64, #SparseVector>
%xv = tensor.empty(%d) : tensor<?xf64, #SparseVector>
%0 = linalg.generic #trait_op1
ins(%arga: tensor<?xcomplex<f64>, #SparseVector>)
outs(%xv: tensor<?xf64, #SparseVector>) {
Expand Down
6 changes: 3 additions & 3 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conv_1d_nwc_wcf.mlir
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Expand Up @@ -41,7 +41,7 @@

// Creates and returns 3-D buffer of size (%s1, %s2, %s3) filled with the value %f
func.func @alloc_3d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %f : f32) -> tensor<?x?x?xf32> {
%buf = bufferization.alloc_tensor(%s1, %s2, %s3) : tensor<?x?x?xf32>
%buf = tensor.empty(%s1, %s2, %s3) : tensor<?x?x?xf32>
%ret = linalg.fill ins(%f : f32) outs(%buf : tensor<?x?x?xf32>) -> tensor<?x?x?xf32>
return %ret : tensor<?x?x?xf32>
}
Expand All @@ -58,7 +58,7 @@ func.func @conv_1d_nwc_wcf_CCC(%arg0: tensor<?x?x?xf32, #CCC>, %arg1: tensor<?x?
%c1 = arith.constant 1 : index
%c3 = arith.constant 3 : index
%c6 = arith.constant 6 : index
%s = bufferization.alloc_tensor(%c3, %c6, %c1) : tensor<?x?x?xf32, #CCC>
%s = tensor.empty(%c3, %c6, %c1) : tensor<?x?x?xf32, #CCC>
%ret = linalg.conv_1d_nwc_wcf {dilations = dense<1> : tensor<1xi64>,
strides = dense<1> : tensor<1xi64>}
ins (%arg0, %arg1: tensor<?x?x?xf32, #CCC>, tensor<?x?x?xf32>)
Expand All @@ -70,7 +70,7 @@ func.func @conv_1d_nwc_wcf_CDC(%arg0: tensor<?x?x?xf32, #CDC>, %arg1: tensor<?x?
%c1 = arith.constant 1 : index
%c3 = arith.constant 3 : index
%c6 = arith.constant 6 : index
%s = bufferization.alloc_tensor(%c3, %c6, %c1) : tensor<?x?x?xf32, #CDC>
%s = tensor.empty(%c3, %c6, %c1) : tensor<?x?x?xf32, #CDC>
%ret = linalg.conv_1d_nwc_wcf {dilations = dense<1> : tensor<1xi64>,
strides = dense<1> : tensor<1xi64>}
ins (%arg0, %arg1: tensor<?x?x?xf32, #CDC>, tensor<?x?x?xf32>)
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10 changes: 5 additions & 5 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conv_2d.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -51,7 +51,7 @@ module {

func.func @conv2d_sparse_out(%input: tensor<8x8xi32>,
%filter: tensor<3x3xi32>) -> tensor<6x6xi32, #DCSR> {
%s = bufferization.alloc_tensor() : tensor<6x6xi32, #DCSR>
%s = tensor.empty() : tensor<6x6xi32, #DCSR>
%0 = linalg.conv_2d
ins (%input, %filter: tensor<8x8xi32>, tensor<3x3xi32>)
outs (%s: tensor<6x6xi32, #DCSR>) -> tensor<6x6xi32, #DCSR>
Expand All @@ -60,7 +60,7 @@ module {

func.func @conv2d_all_sparse_DCSR(%input: tensor<8x8xi32, #DCSR>,
%filter: tensor<3x3xi32>) -> tensor<6x6xi32, #DCSR> {
%s = bufferization.alloc_tensor() : tensor<6x6xi32, #DCSR>
%s = tensor.empty() : tensor<6x6xi32, #DCSR>
%0 = linalg.conv_2d
ins (%input, %filter: tensor<8x8xi32, #DCSR>, tensor<3x3xi32>)
outs (%s: tensor<6x6xi32, #DCSR>) -> tensor<6x6xi32, #DCSR>
Expand All @@ -69,7 +69,7 @@ module {

func.func @conv2d_all_sparse_CSR(%input: tensor<8x8xi32, #CSR>,
%filter: tensor<3x3xi32>) -> tensor<6x6xi32, #CSR> {
%s = bufferization.alloc_tensor() : tensor<6x6xi32, #CSR>
%s = tensor.empty() : tensor<6x6xi32, #CSR>
%0 = linalg.conv_2d
ins (%input, %filter: tensor<8x8xi32, #CSR>, tensor<3x3xi32>)
outs (%s: tensor<6x6xi32, #CSR>) -> tensor<6x6xi32, #CSR>
Expand All @@ -78,7 +78,7 @@ module {

func.func @conv2d_all_sparse_CD(%input: tensor<8x8xi32, #CDR>,
%filter: tensor<3x3xi32>) -> tensor<6x6xi32, #CDR> {
%s = bufferization.alloc_tensor() : tensor<6x6xi32, #CDR>
%s = tensor.empty() : tensor<6x6xi32, #CDR>
%0 = linalg.conv_2d
ins (%input, %filter: tensor<8x8xi32, #CDR>, tensor<3x3xi32>)
outs (%s: tensor<6x6xi32, #CDR>) -> tensor<6x6xi32, #CDR>
Expand All @@ -87,7 +87,7 @@ module {

func.func @conv2d_all_sparse_CSC(%input: tensor<8x8xi32, #CSC>,
%filter: tensor<3x3xi32>) -> tensor<6x6xi32, #CSC> {
%s = bufferization.alloc_tensor() : tensor<6x6xi32, #CSC>
%s = tensor.empty() : tensor<6x6xi32, #CSC>
%0 = linalg.conv_2d
ins (%input, %filter: tensor<8x8xi32, #CSC>, tensor<3x3xi32>)
outs (%s: tensor<6x6xi32, #CSC>) -> tensor<6x6xi32, #CSC>
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