[mlir][sparse] fix bug when packing tensor with 32 bit pointer width.

mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorCodegen.cpp

foreachFieldAndTypeInSparseTensor(
             // memory management.
             auto tensorType = RankedTensorType::get({2}, enc.getPointerType());
             auto memrefType = MemRefType::get(tensorType.getShape(),
                                               tensorType.getElementType());
             auto cstPtr = rewriter.create<arith::ConstantOp>(
                 loc, tensorType,
                 DenseElementsAttr::get(
                     tensorType,
-                    {APInt(64, 0),
-                     APInt(64, op.getData().getType().getShape()[0])}));
+                    ArrayRef<Attribute>{
+                        IntegerAttr::get(enc.getPointerType(), 0),
+                        IntegerAttr::get(
+                            enc.getPointerType(),
+                            op.getData().getType().getShape()[0])}));
             field = rewriter.create<bufferization::ToMemrefOp>(loc, memrefType,
                                                                cstPtr);
             break;
           }
           case SparseTensorFieldKind::IdxMemRef: {
             auto tensorType = op.getIndices().getType();
             auto memrefType = MemRefType::get(tensorType.getShape(),
                                               tensorType.getElementType());

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_pack.mlir

 // DEFINE: %{option} = enable-runtime-library=false
 // DEFINE: %{command} = mlir-opt %s --sparse-compiler=%{option} | \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
 // DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{command}
 //
 
 // TODO: Pack only support CodeGen Path
 
 #SortedCOO = #sparse_tensor.encoding<{
   dimLevelType = [ "compressed-nu", "singleton" ]
 }>
 
+#SortedCOOI32 = #sparse_tensor.encoding<{
+  dimLevelType = [ "compressed-nu", "singleton" ],
+  pointerBitWidth = 32,
+  indexBitWidth = 32
+}>
+
 module {
   //
   // Main driver.
   //
   func.func @entry() {
     //
     // Initialize a 3-dim dense tensor.
     //
     %data = arith.constant dense<
        [  1.0,  2.0,  3.0]
     > : tensor<3xf64>
 
     %index = arith.constant dense<
        [[  1,  2],
         [  5,  6],
         [  7,  8]]
     > : tensor<3x2xindex>
 
+    %index32 = arith.constant dense<
+       [[  1,  2],
+        [  5,  6],
+        [  7,  8]]
+    > : tensor<3x2xi32>
+
     %s4 = sparse_tensor.pack %data, %index : tensor<3xf64>, tensor<3x2xindex>
                                           to tensor<10x10xf64, #SortedCOO>
     // CHECK:1
     // CHECK-NEXT:2
     // CHECK-NEXT:1
     //
     // CHECK-NEXT:5
     // CHECK-NEXT:6
     // CHECK-NEXT:2
     //
     // CHECK-NEXT:7
     // CHECK-NEXT:8
     // CHECK-NEXT:3
     sparse_tensor.foreach in %s4 : tensor<10x10xf64, #SortedCOO> do {
       ^bb0(%1: index, %2: index, %v: f64) :
         vector.print %1: index
         vector.print %2: index
         vector.print %v: f64
      }
+
+    %s5= sparse_tensor.pack %data, %index32 : tensor<3xf64>, tensor<3x2xi32>
+                                          to tensor<10x10xf64, #SortedCOOI32>
+    // CHECK-NEXT:1
+    // CHECK-NEXT:2
+    // CHECK-NEXT:1
+    //
+    // CHECK-NEXT:5
+    // CHECK-NEXT:6
+    // CHECK-NEXT:2
+    //
+    // CHECK-NEXT:7
+    // CHECK-NEXT:8
+    // CHECK-NEXT:3
+    sparse_tensor.foreach in %s5 : tensor<10x10xf64, #SortedCOOI32> do {
+      ^bb0(%1: index, %2: index, %v: f64) :
+        vector.print %1: index
+        vector.print %2: index
+        vector.print %v: f64
+     }
+
     return
   }
 }