[mlir][sparse] performs a tab cleanup (NFC)
authorAart Bik <ajcbik@google.com>
Thu, 15 Dec 2022 19:38:55 +0000 (11:38 -0800)
committerAart Bik <ajcbik@google.com>
Thu, 15 Dec 2022 20:12:06 +0000 (12:12 -0800)
Reviewed By: Peiming

Differential Revision: https://reviews.llvm.org/D140142

mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_abs.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_flatten.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matvec.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_mttkrp.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_out_reduction.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_quantized_matmul.mlir

index 31d5eb5..30f864f 100644 (file)
@@ -451,7 +451,7 @@ def SparseTensor_CompressOp : SparseTensor_Op<"compress",
                    StridedMemRefRankOf<[Index],[1]>:$added,
                    Index:$count,
                    AnySparseTensor:$tensor,
-                  Variadic<Index>:$indices)>,
+                   Variadic<Index>:$indices)>,
     Results<(outs AnySparseTensor:$result)> {
   string summary = "Compressed an access pattern for insertion";
   string description = [{
@@ -477,8 +477,8 @@ def SparseTensor_CompressOp : SparseTensor_Op<"compress",
   }];
   let assemblyFormat = "$values `,` $filled `,` $added `,` $count"
                        " `into` $tensor `[` $indices `]` attr-dict"
-                      " `:` type($values) `,` type($filled) `,` type($added)"
-                      " `,` type($tensor)";
+                       " `:` type($values) `,` type($filled) `,` type($added)"
+                       " `,` type($tensor)";
   let hasVerifier = 1;
 }
 
index e12e9bf..79d1e35 100644 (file)
@@ -83,8 +83,8 @@ module {
     %v2 = arith.constant sparse<
        [ [0], [3], [5], [11], [13], [17], [18], [21], [31] ],
          [ -2147483648, -2147483647, -1000, -1, 0,
-          1, 1000, 2147483646, 2147483647
-        ]
+           1, 1000, 2147483646, 2147483647
+         ]
     > : tensor<32xi32>
     %sv1 = sparse_tensor.convert %v1
          : tensor<32xf64> to tensor<?xf64, #SparseVector>
index 41b5410..6917274 100644 (file)
@@ -48,7 +48,7 @@ module {
   //
   func.func @kernel_flatten(%arga: tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor>,
                             %argx: tensor<7x3xf64>)
-                      -> tensor<7x3xf64> {
+                                -> tensor<7x3xf64> {
     %0 = linalg.generic #trait_flatten
       ins(%arga: tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor>)
       outs(%argx: tensor<7x3xf64>) {
index 9430070..2c18c2b 100644 (file)
@@ -55,7 +55,7 @@ module {
   func.func @kernel_matvec(%arga: tensor<?x?xi32, #SparseMatrix>,
                            %argb: tensor<?xi32>,
                            %argx: tensor<?xi32>)
-                     -> tensor<?xi32> {
+                               -> tensor<?xi32> {
     %0 = linalg.generic #matvec
       ins(%arga, %argb: tensor<?x?xi32, #SparseMatrix>, tensor<?xi32>)
       outs(%argx: tensor<?xi32>) {
index 0933e82..375db9a 100644 (file)
@@ -49,7 +49,7 @@ module {
                            %argc: tensor<?x?xf64>,
                            %argd: tensor<?x?xf64>,
                            %arga: tensor<?x?xf64>)
-                     -> tensor<?x?xf64> {
+                               -> tensor<?x?xf64> {
     %0 = linalg.generic #mttkrp
       ins(%argb, %argc, %argd:
             tensor<?x?x?xf64, #SparseTensor>, tensor<?x?xf64>, tensor<?x?xf64>)
index 36c09a0..4978434 100644 (file)
@@ -36,7 +36,7 @@
 module {
   func.func @redsum(%arga: tensor<?x?x?xi32, #SparseTensor>,
                %argb: tensor<?x?x?xi32, #SparseTensor>)
-                  -> tensor<?x?xi32, #SparseMatrix> {
+                   -> tensor<?x?xi32, #SparseMatrix> {
     %c0 = arith.constant 0 : index
     %c1 = arith.constant 1 : index
     %d0 = tensor.dim %arga, %c0 : tensor<?x?x?xi32, #SparseTensor>
index 7b982f7..2c1200a 100644 (file)
@@ -59,7 +59,7 @@ module {
     %0 = call @quantized_matmul(%input1, %sparse_input2, %output)
        : (tensor<5x3xi8>,
           tensor<3x6xi8, #DCSR>,
-         tensor<5x6xi32>) -> tensor<5x6xi32>
+          tensor<5x6xi32>) -> tensor<5x6xi32>
 
     //
     // Verify the output.