[mlir][Linalg] Drop spurious error message

Drop usage of `emitRemark` and use `notifyMatchFailure` instead to
avoid unnecessary spew during compilation.

Differential Revision: https://reviews.llvm.org/D99485

Author: MaheshRavishankar

mlir/lib/Dialect/Linalg/Transforms/FusionOnTensors.cpp

@@ -880,8 +880,10 @@ struct FoldProducerReshapeOpByLinearization
 
       // Further check that the resulting index maps can be fused and
       // inverted. Without this the resultant op is not legal.
-      if (!inversePermutation(concatAffineMaps(fusedIndexMaps)))
-        return op.emitRemark("fused op loop bound computation failed");
+      if (!inversePermutation(concatAffineMaps(fusedIndexMaps))) {
+        return rewriter.notifyMatchFailure(
+            op, "fused op loop bound computation failed");
+      }
 
       rewriter.startRootUpdate(op);
       op->setOperands(fusedOperands);
@@ -973,15 +975,19 @@ struct FoldConsumerReshapeOpByLinearization
         linearizeCollapsedDims(invMap, reshapeOp.getSrcType().getShape(),
                                reshapeOp.getReassociationMaps());
     for (AffineExpr expr : modifiedMap.getResults()) {
-      if (!expr.isPureAffine())
-        return producer.emitRemark("fused op indexing map is not affine");
+      if (!expr.isPureAffine()) {
+        return rewriter.notifyMatchFailure(
+            producer, "fused op indexing map is not affine");
+      }
     }
     fusedIndexMaps.back() = modifiedMap;
 
     // Further check that the resulting index maps can be fused and
     // inverted. Without this the resultant op is not legal.
-    if (!inversePermutation(concatAffineMaps(fusedIndexMaps)))
-      return reshapeOp.emitRemark("fused op loop bound computation failed");
+    if (!inversePermutation(concatAffineMaps(fusedIndexMaps))) {
+      return rewriter.notifyMatchFailure(
+          producer, "fused op loop bound computation failed");
+    }
 
     Location loc = producer.getLoc();
     Value output = rewriter.create<TensorReshapeOp>(

mlir/test/Dialect/Linalg/reshape_linearization_fusion.mlir

@@ -1,4 +1,4 @@
-// RUN: mlir-opt -split-input-file -linalg-fold-reshape-ops-by-linearization -verify-diagnostics %s | FileCheck %s
+// RUN: mlir-opt -split-input-file -linalg-fold-reshape-ops-by-linearization %s | FileCheck %s
 
 #map0 = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>
 func @generic_op_reshape_producer_fusion(%arg0 : tensor<?x?x?xf32>,
@@ -257,7 +257,6 @@ func @generic_op_reshape_consumer_nofusion(%arg0 : tensor<?x?x?x5xf32>,
                                            %arg1 : tensor<?x?x?x5xf32>) ->
                                            tensor<?x?xf32>
 {
-  // expected-remark @+1 {{fused op indexing map is not affine}}
   %0 = linalg.generic {
      indexing_maps = [#map0, #map0, #map0],
      iterator_types = ["parallel", "parallel", "parallel", "parallel"]}
@@ -272,3 +271,10 @@ func @generic_op_reshape_consumer_nofusion(%arg0 : tensor<?x?x?x5xf32>,
     tensor<?x?x?x5xf32> into tensor<?x?xf32>
   return %1 : tensor<?x?xf32>
 }
+// CHECK-LABEL: func @generic_op_reshape_consumer_nofusion
+//  CHECK-SAME:   %[[ARG0:[a-zA-Z0-9_]+]]: tensor<?x?x?x5xf32>
+//  CHECK-SAME:   %[[ARG1:[a-zA-Z0-9_]+]]: tensor<?x?x?x5xf32>
+//       CHECK:   %[[NOFUSE:.+]] = linalg.generic
+//  CHECK-SAME:     ins(%[[ARG0]], %[[ARG1]]
+//       CHECK:   %[[RESULT:.+]] = linalg.tensor_reshape %[[NOFUSE]]
+//       CHECK:   return %[[RESULT]]