class_docstr: Abstract encoder class.
  
  Implementations must define the following abstract methods:
   -`build`
   -`encode`
class_docstr_tok: ["Abstract","encoder","class",".","Implementations","must","define","the","following","abstract","methods",":","-","`","build","`","-","`","encode","`"]
docstr: Encodes input sequences into a precursors for latent code `z`.
  
  Args:
     sequence: Batch of sequences to encode.
     sequence_length: Length of sequences in input batch.
  
  Returns:
     outputs: Raw outputs to parameterize the prior distribution in
        MusicVae.encode, sized `[batch_size, N]`.
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code: def encode(self, sequence, sequence_length):
      """Encodes input sequences into a precursors for latent code `z`.
  
      Args:
         sequence: Batch of sequences to encode.
         sequence_length: Length of sequences in input batch.
  
      Returns:
         outputs: Raw outputs to parameterize the prior distribution in
            MusicVae.encode, sized `[batch_size, N]`.
      """
      pass
  
imports: import abc
  from magenta.contrib import training
  import tensorflow.compat.v1
  import tensorflow_probability
  import tf_slim
label_desc: Use image node_id 3 for calling the BaseEncoder obj's underlying member method code with example usage: obj.encode(sequence, sequence_length) without return types