[Mlir-commits] [mlir] [mlir][vector] Add mask elimination transform (PR #99314)

[Benjamin Maxwell]

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@@ -0,0 +1,138 @@
+// RUN: mlir-opt %s -split-input-file -test-eliminate-vector-masks  | FileCheck %s
+
+// This tests a general pattern the vectorizer tends to emit.
+
+// CHECK-LABEL: @eliminate_redundant_masks_through_insert_and_extracts
+// CHECK: %[[ALL_TRUE_MASK:.*]] = arith.constant dense<true> : vector<[4]xi1>
+// CHECK: vector.transfer_read {{.*}} %[[ALL_TRUE_MASK]]
+// CHECK: vector.transfer_write {{.*}} %[[ALL_TRUE_MASK]]
+func.func @eliminate_redundant_masks_through_insert_and_extracts(%tensor: tensor<1x1000xf32>) {
+  %c0 = arith.constant 0 : index
+  %c4 = arith.constant 4 : index
+  %c1000 = arith.constant 1000 : index
+  %c0_f32 = arith.constant 0.0 : f32
+  %vscale = vector.vscale
+  %c4_vscale = arith.muli %vscale, %c4 : index
+  %extracted_slice_0 = tensor.extract_slice %tensor[0, 0] [1, %c4_vscale] [1, 1] : tensor<1x1000xf32> to tensor<1x?xf32>
+  %output_tensor = scf.for %i = %c0 to %c1000 step %c4_vscale iter_args(%arg = %extracted_slice_0) -> tensor<1x?xf32> {
+    // 1. Extract a slice.
+    %extracted_slice_1 = tensor.extract_slice %arg[0, 0] [1, %c4_vscale] [1, 1] : tensor<1x?xf32> to tensor<?xf32>
+
+    // 2. Create a mask for the slice.
+    %dim_1 = tensor.dim %extracted_slice_1, %c0 : tensor<?xf32>
+    %mask = vector.create_mask %dim_1 : vector<[4]xi1>
+
+    // 3. Read the slice and do some computation.
+    %vec = vector.transfer_read %extracted_slice_1[%c0], %c0_f32, %mask {in_bounds = [true]} : tensor<?xf32>, vector<[4]xf32>
+    %new_vec = "test.some_computation"(%vec) : (vector<[4]xf32>) -> (vector<[4]xf32>)
+
+    // 4. Write the new value.
+    %write = vector.transfer_write %new_vec, %extracted_slice_1[%c0], %mask {in_bounds = [true]} : vector<[4]xf32>, tensor<?xf32>
+
+    // 5. Insert and yield the new tensor value.
+    %result = tensor.insert_slice %write into %arg[0, 0] [1, %c4_vscale] [1, 1] : tensor<?xf32> into tensor<1x?xf32>
+    scf.yield %result : tensor<1x?xf32>
+  }
+  "test.some_use"(%output_tensor) : (tensor<1x?xf32>) -> ()
+  return
+}
+
+// -----
+
+// CHECK-LABEL: @negative_extract_slice_size_shrink
+// CHECK-NOT: arith.constant dense<true> : vector<[4]xi1>
+// CHECK: %[[MASK:.*]] = vector.create_mask
+// CHECK: "test.some_use"(%[[MASK]]) : (vector<[4]xi1>) -> ()
+func.func @negative_extract_slice_size_shrink(%tensor: tensor<1000xf32>) {
+  %c0 = arith.constant 0 : index
+  %c4 = arith.constant 4 : index
+  %c1000 = arith.constant 1000 : index
+  %vscale = vector.vscale
+  %c4_vscale = arith.muli %vscale, %c4 : index
+  %extracted_slice = tensor.extract_slice %tensor[0] [%c4_vscale] [1] : tensor<1000xf32> to tensor<?xf32>
+  %slice = scf.for %i = %c0 to %c1000 step %c4_vscale iter_args(%arg = %extracted_slice) -> tensor<?xf32> {
+    // This mask cannot be eliminated even though looking at the above operations
+    // it appears `tensor.dim` will always be c4_vscale (so the mask all-true).
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MacDue wrote:

The key part is "looking at the above operations" (to point out how simple pattern matching of the IR could lead to incorrect results).

https://github.com/llvm/llvm-project/pull/99314