more IR tests

Author: rengolin

mlir/test/Dialect/SCF/canonicalize.mlir

@@ -1811,7 +1811,7 @@ module {
       %4 = affine.min #map2(%arg3)[%dim, %arg0]
       %extracted_slice0 = tensor.extract_slice %arg4[%3] [%4] [1] : tensor<?xf32> to tensor<?xf32>
       %extracted_slice1 = tensor.extract_slice %arg5[%3] [%4] [1] : tensor<?xf32> to tensor<?xf32>
-      %5 = linalg.elemwise_unary ins(%extracted_slice0 : tensor<?xf32>) outs(%extracted_slice1 : tensor<?xf32>) -> tensor<?xf32>
+      %5 = linalg.exp ins(%extracted_slice0 : tensor<?xf32>) outs(%extracted_slice1 : tensor<?xf32>) -> tensor<?xf32>
       scf.forall.in_parallel {
         tensor.parallel_insert_slice %5 into %arg5[%3] [%4] [1] : tensor<?xf32> into tensor<?xf32>
       }
@@ -1825,7 +1825,7 @@ module {
 //  CHECK-SAME:                       shared_outs(%[[ITER_ARG_5:.*]] = %[[ARG2]]) -> (tensor<?xf32>) {
 //       CHECK:      %[[OPERAND0:.*]] = tensor.extract_slice %[[ARG1]]
 //       CHECK:      %[[OPERAND1:.*]] = tensor.extract_slice %[[ITER_ARG_5]]
-//       CHECK:      %[[ELEM:.*]] = linalg.elemwise_unary ins(%[[OPERAND0]] : tensor<?xf32>) outs(%[[OPERAND1]] : tensor<?xf32>) -> tensor<?xf32>
+//       CHECK:      %[[ELEM:.*]] = linalg.exp ins(%[[OPERAND0]] : tensor<?xf32>) outs(%[[OPERAND1]] : tensor<?xf32>) -> tensor<?xf32>
 //       CHECK:      scf.forall.in_parallel {
 //  CHECK-NEXT:         tensor.parallel_insert_slice %[[ELEM]] into %[[ITER_ARG_5]]
 //  CHECK-NEXT:      }
@@ -1851,7 +1851,7 @@ module {
       %extracted_slice_0 = tensor.extract_slice %arg6[%3] [%4] [1] : tensor<?xf32> to tensor<?xf32>
       %extracted_slice_1 = tensor.extract_slice %arg7[%3] [%4] [1] : tensor<?xf32> to tensor<?xf32>
       %extracted_slice_2 = tensor.extract_slice %0[%3] [%4] [1] : tensor<?xf32> to tensor<?xf32>
-      %5 = linalg.elemwise_unary ins(%extracted_slice : tensor<?xf32>) outs(%extracted_slice_1 : tensor<?xf32>) -> tensor<?xf32>
+      %5 = linalg.exp ins(%extracted_slice : tensor<?xf32>) outs(%extracted_slice_1 : tensor<?xf32>) -> tensor<?xf32>
       scf.forall.in_parallel {
         tensor.parallel_insert_slice %5 into %arg6[%3] [%4] [1] : tensor<?xf32> into tensor<?xf32>
         tensor.parallel_insert_slice %extracted_slice into %arg5[%3] [%4] [1] : tensor<?xf32> into tensor<?xf32>
@@ -1868,7 +1868,7 @@ module {
 //  CHECK-SAME:                       shared_outs(%[[ITER_ARG_6:.*]] = %[[ARG2]]) -> (tensor<?xf32>) {
 //       CHECK:      %[[OPERAND0:.*]] = tensor.extract_slice %[[ARG1]]
 //       CHECK:      %[[OPERAND1:.*]] = tensor.extract_slice %[[ARG3]]
-//       CHECK:      %[[ELEM:.*]] = linalg.elemwise_unary ins(%[[OPERAND0]] : tensor<?xf32>) outs(%[[OPERAND1]] : tensor<?xf32>) -> tensor<?xf32>
+//       CHECK:      %[[ELEM:.*]] = linalg.exp ins(%[[OPERAND0]] : tensor<?xf32>) outs(%[[OPERAND1]] : tensor<?xf32>) -> tensor<?xf32>
 //       CHECK:      scf.forall.in_parallel {
 //  CHECK-NEXT:         tensor.parallel_insert_slice %[[ELEM]] into %[[ITER_ARG_6]]
 //  CHECK-NEXT:      }

mlir/test/Integration/Dialect/Transform/match_matmul.mlir

@@ -69,7 +69,7 @@ func.func @matmul_with_extra_ops_in_func(%lhs: tensor<10x20xf32>, %rhs: tensor<2
   // expected-remark @below {{fill}}
   %fill = linalg.fill ins(%cst : f64) outs(%empty : tensor<10x15xf32>) -> tensor<10x15xf32>
 
-  %real_lhs = linalg.elemwise_binary { fun = #linalg.binary_fn<mul> } 
+  %real_lhs = linalg.mul
     ins(%lhs, %lhs : tensor<10x20xf32>, tensor<10x20xf32>) outs(%lhs : tensor<10x20xf32>) -> tensor<10x20xf32>
 
   // expected-remark @below {{matmul}}

mlir/test/Interfaces/TilingInterface/tile-and-fuse-consumer.mlir

@@ -19,7 +19,7 @@ module {
     }
     %in_operand_2 = tensor.empty() : tensor<64xf32>
     %out_operand_3 = tensor.empty() : tensor<64xf32>
-    %2 = linalg.elemwise_binary {fun = #linalg.binary_fn<add>} ins(%1#1, %in_operand_2 : tensor<64xf32>, tensor<64xf32>) outs(%out_operand_3 : tensor<64xf32>) -> tensor<64xf32>
+    %2 = linalg.add ins(%1#1, %in_operand_2 : tensor<64xf32>, tensor<64xf32>) outs(%out_operand_3 : tensor<64xf32>) -> tensor<64xf32>
     return %2 : tensor<64xf32>
   }
 }
@@ -50,7 +50,7 @@ module attributes {transform.with_named_sequence} {
 //      CHECK:      %[[INSERT_MAT:.*]] = tensor.insert_slice %[[MAT_OUT]] into %[[FIRST_OUT_ARG]][%[[IV]]] [32] [1]
 //      CHECK:      %[[SLICE_OPERAND2:.*]] = tensor.extract_slice %0[%[[IV]]] [32] [1]
 //      CHECK:      %[[SLICE_OUT:.*]] = tensor.extract_slice %[[ELEM_OUT_ARG]][%[[IV]]] [32] [1]
-//      CHECK:      %[[ELEM_OUT:.*]] = linalg.elemwise_binary {fun = #linalg.binary_fn<add>}
+//      CHECK:      %[[ELEM_OUT:.*]] = linalg.add
 // CHECK-SAME:              ins(%[[MAT_OUT]], %[[SLICE_OPERAND2]] :
 // CHECK-SAME:              outs(%[[SLICE_OUT]] :
 //      CHECK:      %[[INSERT_ELEM:.*]] = tensor.insert_slice %[[ELEM_OUT]] into %[[ELEM_OUT_ARG]][%[[IV]]] [32] [1]
@@ -76,7 +76,7 @@ module {
     }
     %in_operand_2 = tensor.empty() : tensor<64x64xf32>
     %out_operand_3 = tensor.empty() : tensor<64x64xf32>
-    %2 = linalg.elemwise_binary {fun = #linalg.binary_fn<add>} ins(%1#1, %in_operand_2 : tensor<64x64xf32>, tensor<64x64xf32>) outs(%out_operand_3 : tensor<64x64xf32>) -> tensor<64x64xf32>
+    %2 = linalg.add ins(%1#1, %in_operand_2 : tensor<64x64xf32>, tensor<64x64xf32>) outs(%out_operand_3 : tensor<64x64xf32>) -> tensor<64x64xf32>
     return %2 : tensor<64x64xf32>
   }
 }
@@ -109,7 +109,7 @@ module attributes {transform.with_named_sequence} {
 // CHECK-SAME:              outs(%[[MAT_OUT_SLICE]] :
 //      CHECK:      %[[SLICE_OPERAND2:.*]] = tensor.extract_slice %[[OUT_INIT]][%[[IV1]], %[[IV2]]] [32, 32] [1, 1]
 //      CHECK:      %[[SLICE_OUT:.*]] = tensor.extract_slice %[[ELEM_OUT_ARG]][%[[IV1]], %[[IV2]]] [32, 32] [1, 1]
-//      CHECK:      %[[ELEM_OUT:.*]] = linalg.elemwise_binary {fun = #linalg.binary_fn<add>}
+//      CHECK:      %[[ELEM_OUT:.*]] = linalg.add
 // CHECK-SAME:              ins(%[[MAT_OUT]], %[[SLICE_OPERAND2]] :
 // CHECK-SAME:              outs(%[[SLICE_OUT]] :
 //      CHECK:      scf.forall.in_parallel {