code: def forward(
      self, q_input_a, q_input_b, out_variant: bool, other_scalar: bool
  ):
      if out_variant:
          if other_scalar:
              return self.qop(
                  q_input_a,
                  42,
                  out=torch.tensor(True, dtype=torch.bool),
              )
          else:
              return self.qop(
                  q_input_a,
                  q_input_b,
                  out=torch.tensor(True, dtype=torch.bool),
              )
      else:
          if other_scalar:
              return self.qop(q_input_a, 42)
          else:
              return self.qop(q_input_a, q_input_b)
  
imports: import torch
  import operator_benchmark
label_desc: Use image node_id 2 for calling the QComparatorBenchmark obj's underlying member method code with example usage: obj.forward(q_input_a, q_input_b, out_variant, other_scalar) and returns: self, self, self, self