func.return %0 : tensor<?xf32>
}

// -----

// CHECK-LABEL: testGatherNdI16Indices
func.func @testGatherNdI16Indices(%arg0 : tensor<?xf32>, %arg1 : tensor<?xi16>) -> tensor<?xf32> {
  %0 = "tfl.gather_nd"(%arg0, %arg1) {axis = 1 : i32}: (tensor<?xf32>,tensor<?xi16>) -> tensor<?xf32>
  func.return %0 : tensor<?xf32>
}

// -----

// CHECK-LABEL: testAbs
func.func @testAbs(tensor<? x f32>) -> tensor<? x f32> {

      ConversionPatternRewriter& rewriter) const final {
    RankedTensorType type =
        mlir::dyn_cast_or_null<RankedTensorType>(iota_op.getType());
    // TF::RangeOp doesn't support UI16.
    if (!type || type.getElementType().isUnsignedInteger(16)) return failure();

    const uint64_t dimension = iota_op.getIotaDimension();
    Type element_type = type.getElementType();

  %14 = "tf.Sub"(%12, %13) {device = ""} : (tensor<2xi64>, tensor<2xi64>) -> tensor<2xi64>
  %15 = "tf.LessEqual"(%4, %14) {device = ""} : (tensor<i64>, tensor<2xi64>) -> tensor<2xi1>
  %16 = "tf.All"(%15, %7) {device = "", keep_dims = false} : (tensor<2xi1>, tensor<1xi32>) -> tensor<i1>