return failure();
      }

      auto inserted_window_dims =
          scatter_dimension_numbers.getInsertedWindowDims();
      auto scatter_dims_to_operand_dims =
          scatter_dimension_numbers.getScatterDimsToOperandDims();

      if (IsIotaAttr(inserted_window_dims, indices_type.getShape().back()) &&
          IsIotaAttr(scatter_dims_to_operand_dims,

            op->update_window_dims, builder)));
    attributes.emplace_back(builder.getNamedAttr(
        "inserted_window_dims",
        BuildVhloTensorV1Attr(
            {static_cast<int64_t>(op->inserted_window_dims.size())},
            op->inserted_window_dims, builder)));
    attributes.emplace_back(builder.getNamedAttr(
        "scatter_dims_to_operand_dims",
        BuildVhloTensorV1Attr(

      tensor<200x100x300xf32> {
  %0 = "vhlo.scatter_v1" (%input_tensor, %scatter_indices, %updates) <{
    update_window_dims = #vhlo.tensor_v1<dense<1> : tensor<1xi64>>,
    inserted_window_dims = #vhlo.tensor_v1<dense<[0, 1]> : tensor<2xi64>>,
    scatter_dims_to_operand_dims = #vhlo.tensor_v1<dense<[0, 1]> : tensor<2xi64>>,
    index_vector_dim = #vhlo.integer_v1<1 : i64>,

  batch_group_count : long;
  precision_config : [StablehloPrecisionConfig];
}

table StablehloScatterOptions {
  indices_are_sorted: bool;
  update_window_dims: [long];
  inserted_window_dims: [long];
  scatter_dims_to_operand_dims: [long];
  index_vector_dim: long;
  unique_indices: bool;
  update_computation_subgraph_index: int;
}

enum RngAlgorithm : byte {

  // CHECK:      %[[RESULT:.*]] = "mhlo.scatter"(%[[DEFAULT]], %[[ARG0]], %[[ARG1]])
  // CHECK-SAME: indices_are_sorted = false
  // CHECK-SAME: scatter_dimension_numbers
  // CHECK-SAME:   inserted_window_dims = [0, 1]
  // CHECK-SAME:   scatter_dims_to_operand_dims = [0, 1]
  // CHECK-SAME:   index_vector_dim = 1
  // CHECK-SAME: unique_indices = false