code: def custom_call(self, inputs):
      output = original_call(self, inputs)
      self.last_activation = output
      return output
  
imports: import functools
  import os
  from absl import app
  from absl import flags
  from absl import logging
  import gin
  import numpy
  import reverb
  from rigl.rl.tfagents import sparse_tanh_normal_projection_network
  import tensorflow
  from tf_agents.agents import tf_agent
  from tf_agents.agents.sac import sac_agent
  from tf_agents.environments import suite_mujoco
  from tf_agents.keras_layers import inner_reshape
  from tf_agents.metrics import py_metrics
  from tf_agents.networks import nest_map
  from tf_agents.networks import sequential
  from tf_agents.policies import greedy_policy
  from tf_agents.policies import py_tf_eager_policy
  from tf_agents.policies import random_py_policy
  from tf_agents.replay_buffers import reverb_replay_buffer
  from tf_agents.replay_buffers import reverb_utils
  from tf_agents.train import actor
  from tf_agents.train import learner
  from tf_agents.train import triggers
  from tf_agents.train.utils import spec_utils
  from tf_agents.train.utils import strategy_utils
  from tf_agents.train.utils import train_utils
  from tf_agents.utils import common
  from tf_agents.utils import object_identity
label_desc: Use image node_id 1 for calling a global function with example usage: custom_call(inputs) and returns: output