class_docstr: Base class to implement an encoder that creates a latent z vector.
  
  Users should override compute_z() to define the actual encoder structure.
  Input_keys from compute_z() instead of call(), output_keys are always ['z'].
docstr: Takes in input tensors and returns a latent tensor z.
docstr_tok: ["Takes","in","input","tensors","and","returns","a","latent","tensor","z","."]
code: def compute_z(self, *inputs):
      """Takes in input tensors and returns a latent tensor z."""
      raise NotImplementedError
  
imports: import ddsp
  from ddsp import spectral_ops
  from ddsp.training import nn
  import gin
  import tensorflow.compat.v2
label_desc: Use image node_id 4 for calling the ZEncoder obj's underlying member method code with example usage: obj.compute_z() without return types