code: def __init__(self, mode, device, dtype, M, N, K, L):
      super().__init__(mode, device, dtype)
      self.M = M
      self.N = N
      self.K = K
      self.L = L
  
      self.d1 = self.rand(
          [M, N],
          device=device,
          dtype=dtype,
          requires_grad=self.requires_grad,
      )
      self.d2 = self.rand(
          [K, M, 1],
          device=device,
          dtype=dtype,
          requires_grad=self.requires_grad,
      )
      self.d3 = self.rand(
          [L, K, 1, 1],
          device=device,
          dtype=dtype,
          requires_grad=self.requires_grad,
      )
  
      self.inputs = [self.d1, self.d2, self.d3]
  
imports: import itertools
  import operator
  import numpy
  import torch
  from .None import benchmark
label_desc: Use image node_id 1 to create a new BroadcastThreeArgs object from inherited base classes: benchmark with example: obj = BroadcastThreeArgs(mode, device, dtype, M, N, K, L)