class_docstr: Base class for stochastic encoders in TensorFlow.
class_docstr_tok: ["Base","class","for","stochastic","encoders","in","TensorFlow","."]
docstr: Build encoder.
  
  After buil, self.distribution is a Gaussian distribution conitioned
  on embedding_input.
  
  Args:
    embedding_input (tf.Tensor) : Embedding input.
    name (str): Name of the model, which is also the name scope.
docstr_tok: ["Build","encoder",".","After","buil",",","self.distribution","is","a","Gaussian","distribution","conitioned","on","embedding_input",".","Args",":","embedding_input","(","tf.Tensor",")",":","Embedding","input",".","name","(","str",")",":","Name","of","the","model",",","which","is","also","the","name","scope","."]
code: def build(self, embedding_input, name=None):
      """Build encoder.
  
      After buil, self.distribution is a Gaussian distribution conitioned
      on embedding_input.
  
      Args:
        embedding_input (tf.Tensor) : Embedding input.
        name (str): Name of the model, which is also the name scope.
  
      """
  
file_path: garage/src/garage/tf/embeddings/encoder.py
imports: from garage.np.embeddings import Encoder
  from garage.np.embeddings import StochasticEncoder
  from garage.tf.models import Module, StochasticModule
label_desc: Use image node_id 1 for calling the StochasticEncoder obj's underlying member method code with example usage: obj.build(embedding_input, name) without return types