[mlir][sparse] test pack copy behavior

mlir/test/Dialect/SparseTensor/pack_copy.mlir

+// RUN: mlir-opt %s --sparsification-and-bufferization | FileCheck %s
+
+#CSR = #sparse_tensor.encoding<{
+  lvlTypes = ["dense","compressed"],
+  dimToLvl = affine_map<(i,j) -> (i,j)>,
+  crdWidth = 32,
+  posWidth = 32
+}>
+
+#trait_scale = {
+  indexing_maps = [
+    affine_map<(i,j) -> (i,j)>   // X (out)
+  ],
+  iterator_types = ["parallel", "parallel"],
+  doc = "X(i,j) = X(i,j) * 2"
+}
+
+//
+// Pass in the buffers of the sparse tensor, marked non-writable.
+// This forces a copy for the values and positions.
+//
+// CHECK-LABEL: func.func @foo(
+// CHECK-SAME: %[[VAL:.*]]: memref<3xf64>,
+// CHECK-SAME: %[[CRD:.*]]: memref<3xi32>,
+// CHECK-SAME: %[[POS:.*]]: memref<11xi32>)
+// CHECK:      %[[ALLOC1:.*]] = memref.alloc() {alignment = 64 : i64} : memref<3xf64>
+// CHECK:      memref.copy %[[VAL]], %[[ALLOC1]] : memref<3xf64> to memref<3xf64>
+// CHECK:      %[[ALLOC2:.*]] = memref.alloc() {alignment = 64 : i64} : memref<11xi32>
+// CHECK:      memref.copy %[[POS]], %[[ALLOC2]] : memref<11xi32> to memref<11xi32>
+// CHECK-NOT:  memref.copy
+// CHECK:      return
+//
+func.func @foo(%arg0: tensor<3xf64>  {bufferization.writable = false},
+               %arg1: tensor<3xi32>  {bufferization.writable = false},
+               %arg2: tensor<11xi32> {bufferization.writable = false}) -> (index) {
+    //
+    // Pack the buffers into a sparse tensors.
+    //
+    %pack = sparse_tensor.pack %arg0, %arg2, %arg1
+      : tensor<3xf64>,
+        tensor<11xi32>,
+        tensor<3xi32> to tensor<10x10xf64, #CSR>
+
+    //
+    // Scale the sparse tensor "in-place" (this has no impact on the final
+    // number of entries, but introduces reading the positions buffer
+    // and writing into the value buffer).
+    //
+    %c = arith.constant 2.0 : f64
+    %s = linalg.generic #trait_scale
+      outs(%pack: tensor<10x10xf64, #CSR>) {
+         ^bb(%x: f64):
+          %1 = arith.mulf %x, %c : f64
+          linalg.yield %1 : f64
+    } -> tensor<10x10xf64, #CSR>
+
+    //
+    // Return number of entries in the scaled sparse tensor.
+    //
+    %nse = sparse_tensor.number_of_entries %s : tensor<10x10xf64, #CSR>
+    return %nse : index
+}
+
+//
+// Pass in the buffers of the sparse tensor, marked writable.
+//
+// CHECK-LABEL: func.func @bar(
+// CHECK-SAME: %[[VAL:.*]]: memref<3xf64>,
+// CHECK-SAME: %[[CRD:.*]]: memref<3xi32>,
+// CHECK-SAME: %[[POS:.*]]: memref<11xi32>)
+// CHECK-NOT:  memref.copy
+// CHECK:      return
+//
+func.func @bar(%arg0: tensor<3xf64>  {bufferization.writable = true},
+               %arg1: tensor<3xi32>  {bufferization.writable = true},
+               %arg2: tensor<11xi32> {bufferization.writable = true}) -> (index) {
+    //
+    // Pack the buffers into a sparse tensors.
+    //
+    %pack = sparse_tensor.pack %arg0, %arg2, %arg1
+      : tensor<3xf64>,
+        tensor<11xi32>,
+        tensor<3xi32> to tensor<10x10xf64, #CSR>
+
+    //
+    // Scale the sparse tensor "in-place" (this has no impact on the final
+    // number of entries, but introduces reading the positions buffer
+    // and writing into the value buffer).
+    //
+    %c = arith.constant 2.0 : f64
+    %s = linalg.generic #trait_scale
+      outs(%pack: tensor<10x10xf64, #CSR>) {
+         ^bb(%x: f64):
+          %1 = arith.mulf %x, %c : f64
+          linalg.yield %1 : f64
+    } -> tensor<10x10xf64, #CSR>
+
+    //
+    // Return number of entries in the scaled sparse tensor.
+    //
+    %nse = sparse_tensor.number_of_entries %s : tensor<10x10xf64, #CSR>
+    return %nse : index
+}