code: def init(self, B, M, N, K, device, op):
      self.inputs = {
          "batch1": torch.rand(
              (B, M, K), device=device, requires_grad=self.auto_set()
          ),
          "batch2": torch.rand(
              (
                  B,
                  K,
                  N,
              ),
              device=device,
              requires_grad=self.auto_set(),
          ),
      }
      self.set_module_name(f"bmm (actual op={op}")
      self.op = torch.bmm if op == "bmm" else torch.matmul
  
imports: import torch
  import operator_benchmark
label_desc: Use image node_id 1 for calling the BmmBenchmark obj's underlying member method code with example usage: obj.init(B, M, N, K, device, op) without return types