Change CHECK-MULTI to CHECK-ALWAYS and add comments

Author: mgehre-amd

mlir/test/Dialect/Tosa/constant-reshape-fold.mlir

@@ -1,5 +1,6 @@
-// RUN: mlir-opt --split-input-file --tosa-layerwise-constant-fold %s | FileCheck %s
-// RUN: mlir-opt --split-input-file --tosa-layerwise-constant-fold="fold-splat-or-single-use-only=0" %s | FileCheck %s --check-prefix CHECK-MULTI
+// RUN: mlir-opt --tosa-layerwise-constant-fold %s | FileCheck %s
+// RUN: mlir-opt --tosa-layerwise-constant-fold="fold-splat-or-single-use-only=0" %s \
+// RUN:   | FileCheck %s --check-prefix CHECK-ALWAYS
 
 // CHECK-LABEL: @reshape_single_user
 func.func @reshape_single_user() -> tensor<1x2xf32> {
@@ -10,6 +11,7 @@ func.func @reshape_single_user() -> tensor<1x2xf32> {
   return %1 : tensor<1x2xf32>
 }
 
+// Splat constants are always folded, even when they have multiple users.
 // CHECK-LABEL: @reshape_multi_user_splat
 func.func @reshape_multi_user_splat() -> (tensor<1x2xf32>, tensor<2xf32>) {
   // CHECK-DAG: %[[RES:.*]] = "tosa.const"{{.*}}-> tensor<2xf32>
@@ -20,14 +22,16 @@ func.func @reshape_multi_user_splat() -> (tensor<1x2xf32>, tensor<2xf32>) {
   return %1, %0 : tensor<1x2xf32>, tensor<2xf32>
 }
 
+// Non-splat constants with multiple users are only folded when
+// fold-splat-or-single-use-only=0 is set.
 // CHECK-LABEL: @reshape_multi_user_non_splat
 func.func @reshape_multi_user_non_splat() -> (tensor<1x2xf32>, tensor<2xf32>) {
   // CHECK: %[[CONST:.*]] = "tosa.const"{{.*}}-> tensor<2xf32>
   // CHECK: %[[RES:.*]] = tosa.reshape
   // CHECK: return %[[RES]], %[[CONST]]
-  // CHECK-MULTI-DAG: %[[RES:.*]] = "tosa.const"{{.*}}-> tensor<2xf32>
-  // CHECK-MULTI-DAG: %[[RESHAPED:.*]] = "tosa.const"{{.*}}-> tensor<1x2xf32>
-  // CHECK-MULTI: return %[[RESHAPED]], %[[RES]]
+  // CHECK-ALWAYS-DAG: %[[RES:.*]] = "tosa.const"{{.*}}-> tensor<2xf32>
+  // CHECK-ALWAYS-DAG: %[[RESHAPED:.*]] = "tosa.const"{{.*}}-> tensor<1x2xf32>
+  // CHECK-ALWAYS: return %[[RESHAPED]], %[[RES]]
   %0 = "tosa.const"() {value = dense<[4.0, 3.0]> : tensor<2xf32>} : () -> tensor<2xf32>
   %1 = tosa.reshape %0 {new_shape = array<i64: 1, 2>}: (tensor<2xf32>) -> tensor<1x2xf32>
   return %1, %0 : tensor<1x2xf32>, tensor<2xf32>