class_docstr: Helper class to manage learnable splines. One could imagine this as a standard
  layer in PyTorch...
code: def _call(self, x):
      y, log_detJ = self.spline_op(x)
      self._cache_log_detJ = log_detJ
      return y
  
imports: from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.distributions import Transform, constraints
  from pyro.nn import DenseNN
  from ..conditional import ConditionalTransformModule
  from ..torch_transform import TransformModule
  from ..util import copy_docs_from
label_desc: Use image node_id 2 for calling the ConditionedSpline obj's underlying member method code with example usage: obj._call(x) and returns: y