[Mlir-commits] [mlir] 30dcbb2 - [mlir][Linalg] Add a test case that consumer has "reduction" loops.

[Hanhan Wang]

Author: Hanhan Wang
Date: 2021-01-05T09:47:07-08:00
New Revision: 30dcbb2a83018da90bac9e52fdbf1b0770e941c2

URL: https://github.com/llvm/llvm-project/commit/30dcbb2a83018da90bac9e52fdbf1b0770e941c2
DIFF: https://github.com/llvm/llvm-project/commit/30dcbb2a83018da90bac9e52fdbf1b0770e941c2.diff

LOG: [mlir][Linalg] Add a test case that consumer has "reduction" loops.

In the past, this was a missing test case and the fusion was not supported. It's
supported after the revisit of init_tensor in Linalg.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D94093

Added: 
    

Modified: 
    mlir/test/Dialect/Linalg/fusion-tensor.mlir

Removed: 
    


################################################################################
diff  --git a/mlir/test/Dialect/Linalg/fusion-tensor.mlir b/mlir/test/Dialect/Linalg/fusion-tensor.mlir
index df7e59d59dde..6a67b5dff10e 100644
--- a/mlir/test/Dialect/Linalg/fusion-tensor.mlir
+++ b/mlir/test/Dialect/Linalg/fusion-tensor.mlir
@@ -536,3 +536,45 @@ func @constant_fusion(%arg0 : tensor<4xf32>) -> (tensor<4xf32>) {
 //      CHECK:     %[[T2:.+]] = addf %[[ARG1]], %[[CST]]
 //      CHECK:     linalg.yield %[[T2]]
 //      CHECK:   return %[[T1]]
+
+// -----
+
+#map0 = affine_map<(d0, d1) -> (d0, d1)>
+#map1 = affine_map<(d0) -> (0, d0)>
+#map2 = affine_map<(d0) -> (0)>
+func @consumer_with_reduction(%arg0: tensor<1x10xf32>,
+                              %arg1: tensor<1x10xf32>,
+                              %arg2: tensor<1xf32>) -> tensor<1xf32> {
+  %init = linalg.init_tensor [1, 10] : tensor<1x10xf32>
+  %0 = linalg.generic
+    {indexing_maps = [#map0, #map0, #map0],
+     iterator_types = ["parallel", "parallel"]}
+    ins(%arg0, %arg1 : tensor<1x10xf32>, tensor<1x10xf32>)
+    outs(%init : tensor<1x10xf32>) {
+  ^bb0(%arg3: f32, %arg4: f32, %arg5: f32):  // no predecessors
+    %2 = addf %arg3, %arg4 : f32
+    linalg.yield %2 : f32
+  } -> tensor<1x10xf32>
+  %1 = linalg.generic
+    {indexing_maps = [#map1, #map2],
+     iterator_types = ["reduction"]}
+    ins(%0 : tensor<1x10xf32>)
+    outs(%arg2 : tensor<1xf32>)  {
+  ^bb0(%arg3: f32, %arg4: f32):  // no predecessors
+    %2 = addf %arg3, %arg4 : f32
+    linalg.yield %2 : f32
+  } -> tensor<1xf32>
+  return %1 : tensor<1xf32>
+}
+//  CHECK-DAG: #[[MAP0:.+]] = affine_map<(d0) -> (0, d0)>
+//  CHECK-DAG: #[[MAP1:.+]] = affine_map<(d0) -> (0)>
+//      CHECK: func @consumer_with_reduction(%[[ARG0:.+]]: tensor<1x10xf32>, %[[ARG1:.+]]: tensor<1x10xf32>, %[[ARG2:.+]]: tensor<1xf32>)
+//      CHECK:   %[[RES:.+]] = linalg.generic
+// CHECK-SAME:     indexing_maps = [#[[MAP0]], #[[MAP0]], #[[MAP1]]]
+// CHECK-SAME:     iterator_types = ["reduction"]
+// CHECK-SAME:     ins(%[[ARG0]], %[[ARG1]] : tensor<1x10xf32>, tensor<1x10xf32>)
+//      CHECK:   ^{{.+}}(%[[T0:.+]]: f32, %[[T1:.+]]: f32, %[[T2:.+]]: f32)
+//      CHECK:     %[[T3:.+]] = addf %[[T0]], %[[T1]] : f32
+//      CHECK:     %[[T4:.+]] = addf %[[T3]], %[[T2]] : f32
+//      CHECK:     linalg.yield %[[T4]]
+//      CHECK:   return %[[RES]]