original_docstring: Runtime batch shape of models represented by this component.
  
      Returns:
        batch_shape: `int` `Tensor` giving the broadcast batch shape of
          all model parameters. This should match the batch shape of
          derived state space models, i.e.,
          `self.make_state_space_model(...).batch_shape_tensor()`.
      
docstring: Runtime batch shape of models represented by this component.
docstring_tokens: Runtime batch shape of models represented by this component .
code: def batch_shape_tensor(self):
      """Runtime batch shape of models represented by this component.
  
      Returns:
        batch_shape: `int` `Tensor` giving the broadcast batch shape of
          all model parameters. This should match the batch shape of
          derived state space models, i.e.,
          `self.make_state_space_model(...).batch_shape_tensor()`.
      """
      batch_shape = tf.constant([], dtype=tf.int32)
      for param in self.parameters:
        batch_shape = tf.broadcast_dynamic_shape(
            batch_shape, param.prior.batch_shape_tensor())
      return batch_shape
code_tokens: def batch_shape_tensor ( self ) : batch_shape = tf . constant ( [ ] , dtype = tf . int32 ) for param in self . parameters : batch_shape = tf . broadcast_dynamic_shape ( batch_shape , param . prior . batch_shape_tensor ( ) ) return batch_shape
short_docstring: Runtime batch shape of models represented by this component.
short_docstring_tokens: Runtime batch shape of models represented by this component .
comment: """Runtime batch shape of models represented by this component.
  
      Returns:
        batch_shape: `int` `Tensor` giving the broadcast batch shape of
          all model parameters. This should match the batch shape of
          derived state space models, i.e.,
          `self.make_state_space_model(...).batch_shape_tensor()`.
      """