class_docstr: Coupling Block following the GLOW design. The only difference to the RealNVP coupling blocks, is the fact that it
  uses a single subnetwork to jointly predict [s_i, t_i], instead of two separate subnetworks. This reduces
  computational cost and speeds up learning. clamp: Soft clamping for the multiplicative component. The amplification
  or attenuation of each input dimension can be at most ±exp(clamp).
code: def output_dims(self, input_dims):
      return input_dims
  
imports: import math
  import torch
  from torch import nn
  from transformers.activations import get_activation
  from ..configuration import AdapterFusionConfig, BnConfig
  from ..context import ForwardContext
label_desc: Use image node_id 6 for calling the GLOWCouplingBlock obj's underlying member method code with example usage: obj.output_dims(input_dims) and returns: input_dims