class_docstr: Sequential Model.
  
  Args:
      name (str): Model name, also the variable scope.
      models (list[garage.tf.models.Model]): The models to be connected
          in sequential order.
class_docstr_tok: ["Sequential","Model",".","Args",":","name","(","str",")",":","Model","name",",","also","the","variable","scope",".","models","(","list","[","garage.tf.models.Model","]",")",":","The","models","to","be","connected","in","sequential","order","."]
docstr: Build model given input placeholder(s).
  
  Args:
      input_var (tf.Tensor): Tensor input.
      name (str): Inner model name, also the variable scope of the
          inner model.
  
  Return:
      tf.Tensor: Tensor output of the model.
docstr_tok: ["Build","model","given","input","placeholder","(","s",")",".","Args",":","input_var","(","tf.Tensor",")",":","Tensor","input",".","name","(","str",")",":","Inner","model","name",",","also","the","variable","scope","of","the","inner","model",".","Return",":","tf.Tensor",":","Tensor","output","of","the","model","."]
code: def _build(self, input_var, name=None):
      """Build model given input placeholder(s).
  
      Args:
          input_var (tf.Tensor): Tensor input.
          name (str): Inner model name, also the variable scope of the
              inner model.
  
      Return:
          tf.Tensor: Tensor output of the model.
  
      """
      out = input_var
      for model in self._models:
          self._last_network = model.build(out, name=name)
          if self._first_network is None:
              self._first_network = self._last_network
          out = self._last_network.outputs
  
      return out
  
file_path: garage/src/garage/tf/models/sequential.py
imports: from garage.tf.models.model import Model
label_desc: Use image node_id 2 for calling the Sequential obj's underlying member method code with example usage: obj._build(input_var, name) and returns: out