code: def __init__(self, d, transposed=False):
      super().__init__()
      # BLD if transpoed is False, otherwise BDL
      self.transposed = transposed
      self.norm = nn.InstanceNorm1d(
          d, affine=True, track_running_stats=False
      )
  
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 1 to create a new ReversibleInstanceNorm1dInput object from inherited base classes: nn with example: obj = ReversibleInstanceNorm1dInput(d, transposed)