code: def __init__(self, mode, device, dtype, B, M, N, K):
      super().__init__(mode, device, dtype)
      self.B = B
      self.M = M
      self.N = N
      self.K = K
      self.d1 = self.rand(
          [B, M, N],
          device=device,
          dtype=dtype,
          requires_grad=self.requires_grad,
      )
      self.d2 = self.rand(
          [B, N, K],
          device=device,
          dtype=dtype,
          requires_grad=self.requires_grad,
      )
      self.inputs = [self.d1, self.d2]
  
file_path: pytorch/benchmarks/tensorexpr/matmul.py
imports: import numpy
  from .None import benchmark
label_desc: Use image node_id 1 to create a new MatMulBench object from inherited base classes: benchmark with example: obj = MatMulBench(mode, device, dtype, B, M, N, K)