code: def forward(
      self,
      qX,
      weight,
      bias,
      eps: float,
      Y_scale: float,
      Y_zero_point: int,
  ):
      return torch.ops.quantized.layer_norm(
          qX,
          qX.size()[1:],
          weight=weight,
          bias=bias,
          eps=eps,
          output_scale=Y_scale,
          output_zero_point=Y_zero_point,
      )
  
imports: import torch
  import operator_benchmark
label_desc: Use image node_id 2 for calling the QLayerNormBenchmark obj's underlying member method code with example usage: obj.forward(qX, weight, bias, eps, Y_scale, Y_zero_point) and returns: torch