code: def __init__(self, mode, device, dtype, M, N):
      super().__init__(mode, device, dtype)
      self.M = M
      self.N = N
      self.dtype = dtype
      self.inputs = [
          self.randn(
              [M, N],
              device=device,
              dtype=dtype,
              requires_grad=self.requires_grad,
          )
      ]
  
file_path: pytorch/benchmarks/tensorexpr/softmax.py
imports: import scipy.special
  from .None import benchmark
label_desc: Use image node_id 1 to create a new SoftmaxBench object from inherited base classes: benchmark with example: obj = SoftmaxBench(mode, device, dtype, M, N)