class_docstr: Abstract encoder class. All encoders should inherit from this.
  
  Args:
    params: A dictionary of hyperparameters for the encoder.
    name: A variable scope for the encoder graph.
class_docstr_tok: ["Abstract","encoder","class",".","All","encoders","should","inherit","from","this",".","Args",":","params",":","A","dictionary","of","hyperparameters","for","the","encoder",".","name",":","A","variable","scope","for","the","encoder","graph","."]
docstr: Encodes an input sequence.
  
  Args:
    inputs: The inputs to encode. A float32 tensor of shape [B, T, ...].
    sequence_length: The length of each input. An int32 tensor of shape [T].
  
  Returns:
    An `EncoderOutput` tuple containing the outputs and final state.
docstr_tok: ["Encodes","an","input","sequence",".","Args",":","inputs",":","The","inputs","to","encode",".","A","float32","tensor","of","shape","[","B",",","T",",","...","]",".","sequence_length",":","The","length","of","each","input",".","An","int32","tensor","of","shape","[","T","]",".","Returns",":","An","`","EncoderOutput","`","tuple","containing","the","outputs","and","final","state","."]
code: def encode(self, *args, **kwargs):
      """
      Encodes an input sequence.
  
      Args:
        inputs: The inputs to encode. A float32 tensor of shape [B, T, ...].
        sequence_length: The length of each input. An int32 tensor of shape [T].
  
      Returns:
        An `EncoderOutput` tuple containing the outputs and final state.
      """
      raise NotImplementedError
  
file_path: seq2seq/seq2seq/encoders/encoder.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  from collections import namedtuple
  import six
  from seq2seq.configurable import Configurable
  from seq2seq.graph_module import GraphModule
label_desc: Use image node_id 3 for calling the Encoder obj's underlying member method code with example usage: obj.encode() without return types