[mlir][sparse] use proper type alias for filename ptr

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

module {
   func @entry() {
     %d0 = constant 0.0 : f64
     %c0 = constant 0 : index
     %c1 = constant 1 : index
 
     // Read the sparse matrix from file, construct sparse storage.
     %fileName = call @getTensorFilename(%c0) : (index) -> (!Filename)
     %a = sparse_tensor.new %fileName
-      : !llvm.ptr<i8> to tensor<?x?xf64, #SparseMatrix>
+      : !Filename to tensor<?x?xf64, #SparseMatrix>
 
     // Initialize all-dense annotated "sparse" matrix to all zeros.
     %fileZero = call @getTensorFilename(%c1) : (index) -> (!Filename)
     %x = sparse_tensor.new %fileZero
-      : !llvm.ptr<i8> to tensor<?x?xf64, #DenseMatrix>
+      : !Filename to tensor<?x?xf64, #DenseMatrix>
 
     // Call the kernel.
     %0 = call @dense_output(%a, %x)
       : (tensor<?x?xf64, #SparseMatrix>,
          tensor<?x?xf64, #DenseMatrix>) -> tensor<?x?xf64, #DenseMatrix>
 
     //
     // Print the linearized 5x5 result for verification.

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

scf.for %i = %c0 to %c7 step %c1 {
       scf.for %j = %c0 to %c3 step %c1 {
         memref.store %d0, %xdata[%i, %j] : memref<7x3xf64>
       }
     }
     %x = memref.tensor_load %xdata : memref<7x3xf64>
 
     // Read the sparse tensor from file, construct sparse storage.
     %fileName = call @getTensorFilename(%c0) : (index) -> (!Filename)
-    %a = sparse_tensor.new %fileName : !llvm.ptr<i8> to tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor>
+    %a = sparse_tensor.new %fileName : !Filename to tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor>
 
     // Call the kernel.
     %0 = call @kernel_flatten(%a, %x)
       : (tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor>, tensor<7x3xf64>) -> tensor<7x3xf64>
 
     // Print the result for verification.
     //
     // CHECK: ( 6.25, 0, 0 )

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

func @entry() {
     %i0 = constant 0 : i32
     %c0 = constant 0 : index
     %c1 = constant 1 : index
     %c4 = constant 4 : index
     %c256 = constant 256 : index
 
     // Read the sparse matrix from file, construct sparse storage.
     %fileName = call @getTensorFilename(%c0) : (index) -> (!Filename)
-    %a = sparse_tensor.new %fileName : !llvm.ptr<i8> to tensor<?x?xi32, #SparseMatrix>
+    %a = sparse_tensor.new %fileName : !Filename to tensor<?x?xi32, #SparseMatrix>
 
     // Initialize dense vectors.
     %bdata = memref.alloc(%c256) : memref<?xi32>
     %xdata = memref.alloc(%c4) : memref<?xi32>
     scf.for %i = %c0 to %c256 step %c1 {
       %k = addi %i, %c1 : index
       %j = index_cast %k : index to i32
       memref.store %j, %bdata[%i] : memref<?xi32>

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

func @entry() {
     %c3 = constant 3 : index
     %c4 = constant 4 : index
     %c5 = constant 5 : index
     %c256 = constant 256 : index
 
     // Read the sparse B input from a file.
     %fileName = call @getTensorFilename(%c0) : (index) -> (!Filename)
     %b = sparse_tensor.new %fileName
-          : !llvm.ptr<i8> to tensor<?x?x?xf64, #SparseMatrix>
+          : !Filename to tensor<?x?x?xf64, #SparseMatrix>
 
     // Initialize dense C and D inputs and dense output A.
     %cdata = memref.alloc(%c3, %c5) : memref<?x?xf64>
     scf.for %i = %c0 to %c3 step %c1 {
       scf.for %j = %c0 to %c5 step %c1 {
         %k0 = muli %i, %c5 : index
         %k1 = addi %k0, %j : index
         %k2 = index_cast %k1 : index to i32

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

module {
   // Main driver that reads matrix from file and calls the sparse kernel.
   //
   func @entry() {
     %d0 = constant 0.0 : f64
     %c0 = constant 0 : index
 
     // Read the sparse matrix from file, construct sparse storage.
     %fileName = call @getTensorFilename(%c0) : (index) -> (!Filename)
-    %x = sparse_tensor.new %fileName : !llvm.ptr<i8> to tensor<?x?xf64, #DCSR>
+    %x = sparse_tensor.new %fileName : !Filename to tensor<?x?xf64, #DCSR>
 
     // Call kernel.
     %0 = call @kernel_eltwise_mult(%x) : (tensor<?x?xf64, #DCSR>) -> tensor<?x?xf64, #DCSR>
 
     // Print the result for verification.
     //
     // CHECK: ( 1, 1.96, 4, 6.25, 9, 16.81, 16, 27.04, 25 )
     //
     %m = sparse_tensor.values %0 : tensor<?x?xf64, #DCSR> to memref<?xf64>
     %v = vector.transfer_read %m[%c0], %d0: memref<?xf64>, vector<9xf64>
     vector.print %v : vector<9xf64>
 
     return
   }
 }

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

scf.for %i = %c0 to %c5 step %c1 {
       }
     }
     %a = memref.tensor_load %adata : memref<?x?xf32>
     %b = memref.tensor_load %bdata : memref<?x?xf32>
     %x = memref.tensor_load %xdata : memref<?x?xf32>
 
     // Read the sparse matrix from file, construct sparse storage.
     %fileName = call @getTensorFilename(%c0) : (index) -> (!Filename)
-    %s = sparse_tensor.new %fileName : !llvm.ptr<i8> to tensor<?x?xf32, #SparseMatrix>
+    %s = sparse_tensor.new %fileName : !Filename to tensor<?x?xf32, #SparseMatrix>
 
     // Call the kernel.
     %0 = call @sampled_dense_dense(%s, %a, %b, %x)
        : (tensor<?x?xf32, #SparseMatrix>,
           tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>) -> tensor<?x?xf32>
 
     // Print the result for verification.
     //

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

func @entry() {
     %i0 = constant 0.0 : f64
     %c0 = constant 0 : index
     %c1 = constant 1 : index
     %c4 = constant 4 : index
     %c256 = constant 256 : index
 
     // Read the sparse matrix from file, construct sparse storage.
     %fileName = call @getTensorFilename(%c0) : (index) -> (!Filename)
-    %a = sparse_tensor.new %fileName : !llvm.ptr<i8> to tensor<?x?xf64, #SparseMatrix>
+    %a = sparse_tensor.new %fileName : !Filename to tensor<?x?xf64, #SparseMatrix>
 
     // Initialize dense vectors.
     %bdata = memref.alloc(%c256, %c4) : memref<?x?xf64>
     %xdata = memref.alloc(%c4, %c4) : memref<?x?xf64>
     scf.for %i = %c0 to %c256 step %c1 {
       scf.for %j = %c0 to %c4 step %c1 {
         %k0 = muli %i, %c4 : index
         %k1 = addi %j, %k0 : index

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

func @entry() {
     // Setup memory for a single reduction scalar,
     // initialized to zero.
     %xdata = memref.alloc() : memref<f64>
     memref.store %d0, %xdata[] : memref<f64>
     %x = memref.tensor_load %xdata : memref<f64>
 
     // Read the sparse matrix from file, construct sparse storage.
     %fileName = call @getTensorFilename(%c0) : (index) -> (!Filename)
-    %a = sparse_tensor.new %fileName : !llvm.ptr<i8> to tensor<?x?xf64, #SparseMatrix>
+    %a = sparse_tensor.new %fileName : !Filename to tensor<?x?xf64, #SparseMatrix>
 
     // Call the kernel.
     %0 = call @kernel_sum_reduce(%a, %x)
       : (tensor<?x?xf64, #SparseMatrix>, tensor<f64>) -> tensor<f64>
 
     // Print the result for verification.
     //
     // CHECK: 28.2