Fix tests

Author: Groverkss

mlir/test/Dialect/Linalg/rank-reduce-contraction-ops.mlir

@@ -43,7 +43,8 @@ func.func @singleton_batch_matvec(%arg0 : tensor<1x128x512xf32>, %arg1 : tensor<
   //  CHECK-NEXT:   %[[COLLAPSED_LHS:.*]] = tensor.collapse_shape %[[LHS]] {{\[}}[0, 1], [2]]
   //  CHECK-NEXT:   %[[COLLAPSED_RHS:.*]] = tensor.collapse_shape %[[RHS]] {{\[}}[0, 1]]
   //  CHECK-NEXT:   %[[COLLAPSED_INIT:.*]] = tensor.collapse_shape %[[INIT]] {{\[}}[0, 1]]
-  //  CHECK-NEXT:   %[[MATMUL:.+]] = linalg.matvec ins(%[[COLLAPSED_LHS]], %[[COLLAPSED_RHS]] : tensor<128x512xf32>, tensor<512xf32>) outs(%[[COLLAPSED_INIT]] : tensor<128xf32>)
+  //  CHECK-NEXT:   %[[MATMUL:.+]] = linalg.matvec
+  //  CHECK-SAME:   ins(%[[COLLAPSED_LHS]], %[[COLLAPSED_RHS]] : tensor<128x512xf32>, tensor<512xf32>) outs(%[[COLLAPSED_INIT]] : tensor<128xf32>)
   //  CHECK-NEXT:   %[[RES:.*]] = tensor.expand_shape %[[MATMUL]] {{\[}}[0, 1]] output_shape [1, 128]
   //  CHECK-NEXT:   return %[[RES]]
   %1 = linalg.batch_matvec ins(%arg0, %arg1 : tensor<1x128x512xf32>, tensor<1x512xf32>)
@@ -62,7 +63,8 @@ func.func @singleton_batch_vecmat(%arg0 : tensor<1x?xf32>, %arg1 : tensor<1x?x?x
   //  CHECK-NEXT:   %[[COLLAPSED_LHS:.*]] = tensor.collapse_shape %[[LHS]] {{\[}}[0, 1]]
   //  CHECK-NEXT:   %[[COLLAPSED_RHS:.*]] = tensor.collapse_shape %[[RHS]] {{\[}}[0, 1], [2]]
   //  CHECK-NEXT:   %[[COLLAPSED_INIT:.*]] = tensor.collapse_shape %[[INIT]] {{\[}}[0, 1]]
-  //  CHECK-NEXT:   %[[MATMUL:.+]] = linalg.vecmat ins(%[[COLLAPSED_LHS]], %[[COLLAPSED_RHS]] : tensor<?xf32>, tensor<?x?xf32>) outs(%[[COLLAPSED_INIT]] : tensor<?xf32>)
+  //  CHECK-NEXT:   %[[MATMUL:.+]] = linalg.vecmat 
+  //  CHECK-SAME:   ins(%[[COLLAPSED_LHS]], %[[COLLAPSED_RHS]] : tensor<?xf32>, tensor<?x?xf32>) outs(%[[COLLAPSED_INIT]] : tensor<?xf32>)
   //  CHECK-NEXT:   %[[DIM1:.*]] = tensor.dim %[[INIT]], %[[C1]]
   //  CHECK-NEXT:   %[[RES:.*]] = tensor.expand_shape %[[MATMUL]] {{\[}}[0, 1]] output_shape [1, %[[DIM1]]]
   //  CHECK-NEXT:   return %[[RES]]
@@ -113,7 +115,8 @@ func.func @matmul_to_matvec_tensor(%arg0: tensor<?x?xf32>, %arg1: tensor<?x1xf32
   //  CHECK-DAG:    %[[C0:.*]] = arith.constant 0
   //  CHECK-NEXT:   %[[COLLAPSED_RHS:.*]] = tensor.collapse_shape %[[RHS]] {{\[}}[0, 1]]
   //  CHECK-NEXT:   %[[COLLAPSED_INIT:.*]] = tensor.collapse_shape %[[INIT]] {{\[}}[0, 1]]
-  //  CHECK-NEXT:   %[[MATMUL:.+]] = linalg.matvec ins(%[[LHS]], %[[COLLAPSED_RHS]] : tensor<?x?xf32>, tensor<?xf32>) outs(%[[COLLAPSED_INIT]] : tensor<?xf32>)
+  //  CHECK-NEXT:   %[[MATMUL:.+]] = linalg.matvec 
+  //  CHECK-SAME:   ins(%[[LHS]], %[[COLLAPSED_RHS]] : tensor<?x?xf32>, tensor<?xf32>) outs(%[[COLLAPSED_INIT]] : tensor<?xf32>)
   //  CHECK-NEXT:   %[[DIM0:.*]] = tensor.dim %[[INIT]], %[[C0]]
   //  CHECK-NEXT:   %[[RES:.*]] = tensor.expand_shape %[[MATMUL]] {{\[}}[0, 1]] output_shape [%[[DIM0]], 1]
   //  CHECK-NEXT:   return %[[RES]]
@@ -140,7 +143,8 @@ func.func @matmul_to_vecmat_tensor(%arg0: tensor<1x?xf32>, %arg1: tensor<?x?xf32
   //  CHECK-DAG:    %[[C1:.*]] = arith.constant 1
   //  CHECK-NEXT:   %[[COLLAPSED_LHS:.*]] = tensor.collapse_shape %[[LHS]] {{\[}}[0, 1]]
   //  CHECK-NEXT:   %[[COLLAPSED_INIT:.*]] = tensor.collapse_shape %[[INIT]] {{\[}}[0, 1]]
-  //  CHECK-NEXT:   %[[RESULT:.*]] = linalg.vecmat ins(%[[COLLAPSED_LHS]], %[[RHS]] : tensor<?xf32>, tensor<?x?xf32>) outs(%[[COLLAPSED_INIT]] : tensor<?xf32>)
+  //  CHECK-NEXT:   %[[RESULT:.*]] = linalg.vecmat 
+  //  CHECK-SAME:   ins(%[[COLLAPSED_LHS]], %[[RHS]] : tensor<?xf32>, tensor<?x?xf32>) outs(%[[COLLAPSED_INIT]] : tensor<?xf32>)
   //  CHECK-NEXT:   %[[DIM1:.*]] = tensor.dim %[[INIT]], %[[C1]]
   //  CHECK-NEXT:   %[[RES:.*]] = tensor.expand_shape %[[RESULT]] {{\[}}[0, 1]] output_shape [1, %[[DIM1]]]
   //  CHECK-NEXT:   return %[[RES]]