code: def forward(self, x):
      # Means, stds
      if not self.transposed:
          x = x.transpose(-1, -2)
  
      self.s, self.m = torch.std_mean(
          x, dim=-1, unbiased=False, keepdim=True
      )
      self.s += 1e-4
  
      x = (x - self.m) / self.s
      # x = self.norm.weight.unsqueeze(-1) * x + self.norm.bias.unsqueeze(-1)
  
      if not self.transposed:
          return x.transpose(-1, -2)
      return x
  
imports: import math
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  from einops import rearrange
  from opt_einsum import contract
label_desc: Use image node_id 2 for calling the ReversibleInstanceNorm1dInput obj's underlying member method code with example usage: obj.forward(x) and returns: x, x