docstr: Append an observation to the memory
  
  # Argument
      observation (dict): Observation returned by environment
      action (int): Action taken to obtain this observation
      reward (float): Reward obtained by taking this action
      terminal (boolean): Is the state terminal
docstr_tok: ["Append","an","observation","to","the","memory","#","Argument","observation","(","dict",")",":","Observation","returned","by","environment","action","(","int",")",":","Action","taken","to","obtain","this","observation","reward","(","float",")",":","Reward","obtained","by","taking","this","action","terminal","(","boolean",")",":","Is","the","state","terminal"]
code: def append(
      self, observation, action, reward, terminal, training=True
  ):
      """Append an observation to the memory
  
      # Argument
          observation (dict): Observation returned by environment
          action (int): Action taken to obtain this observation
          reward (float): Reward obtained by taking this action
          terminal (boolean): Is the state terminal
      """
      super(SequentialMemory, self).append(
          observation, action, reward, terminal, training=training
      )
  
      # This needs to be understood as follows: in `observation`, take `action`, obtain `reward`
      # and weather the next state is `terminal` or not.
      if training:
          self.observations.append(observation)
          self.actions.append(action)
          self.rewards.append(reward)
          self.terminals.append(terminal)
  
imports: from __future__ import absolute_import
  from collections import deque, namedtuple
  import warnings
  import random
  import numpy
label_desc: Use image node_id 3 for calling the SequentialMemory obj's underlying member method code with example usage: obj.append(observation, action, reward, terminal, training) without return types