// CHECK: %[[BROADCAST_ARGS_1:.*]] = "tfl.broadcast_args"(%[[BROADCAST_ARGS_0]], %[[SHAPE_2]]) : (tensor<8xi64>, tensor<8xi64>) -> tensor<8xi64>
  // CHECK: %[[BROADCAST_TO_2:.*]] = "tfl.broadcast_to"(%[[LESS]], %[[BROADCAST_ARGS_1]]) : (tensor<8x7x6x5x?x3x2x1xi1>, tensor<8xi64>) -> tensor<8x7x6x5x?x3x2x1xi1>

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

// -----

func.func @broadcast_args(%arg0: tensor<5xi32>, %arg1: tensor<2xi32>) -> tensor<5xi32> {
  // CHECK: "tfl.broadcast_args"(%arg0, %arg1)
  %0 = "tfl.broadcast_args"(%arg0, %arg1) {} : (tensor<5xi32>, tensor<2xi32>) -> tensor<5xi32>
  func.return %0 : tensor<5xi32>
}

// -----

  let arguments = (ins
    TFL_ResourceTensor:$hash_table
  );

  let results = (outs
    TFL_I64Tensor:$out
  );
}

def TFL_BroadcastArgsOp : TFL_Op<"broadcast_args",[
    OperandsSameElementTypeConstraintBase<"BroadcastArgs op">,
    PredOpTrait<"input and output must have same element type",
      TFL_TCresVTEtIsSameAsOp<0, 0>>,
    TFL_OperandHasRank<0, 1>,
    TFL_OperandHasRank<1, 1>,

  // maximum rank.
  if (max_rank <= max_bcast_rank) {
    return true;
  }

  // Checks if all operands are broadcasted by BroadcastTo ops with the shape
  // is calculated from the same BroadcastArgs op. In such case, all operands
  // will have the same shape.
  Operation* broadcast_args_pivot = nullptr;
  for (unsigned index : indices) {
    Operation* parent_broadcast_args =