code: def init(self, M, N, K, device, dtype):
      self._init(M, N, K, device)
      x_scale = 0.1
      x_zero_point = 0
      self.inputs = {
          "q_input_one": torch.quantize_per_tensor(
              self.input_one,
              scale=x_scale,
              zero_point=x_zero_point,
              dtype=dtype,
          ),
          "mean": torch.rand(N),
          "var": torch.rand(N),
          "weight": torch.rand(N),
          "bias": torch.rand(N),
          "eps": 1e-5,
          "Y_scale": 0.1,
          "Y_zero_point": 0,
      }
  
file_path: pytorch/benchmarks/operator_benchmark/pt/qbatchnorm_test.py
imports: import torch
  import operator_benchmark
label_desc: Use image node_id 1 for calling the QBatchNormBenchmark obj's underlying member method code with example usage: obj.init(M, N, K, device, dtype) without return types