code: def _create_agent(
      train_step: tf.Variable,
      observation_tensor_spec: types.NestedTensorSpec,
      action_tensor_spec: types.NestedTensorSpec,
      time_step_tensor_spec: ts.TimeStep,
      learning_rate: float,
  ) -> tf_agent.TFAgent:
      """Creates an agent."""
      critic_net = critic_network.CriticNetwork(
          (observation_tensor_spec, action_tensor_spec),
          observation_fc_layer_params=None,
          action_fc_layer_params=None,
          joint_fc_layer_params=(256, 256),
          kernel_initializer="glorot_uniform",
          last_kernel_initializer="glorot_uniform",
      )
  
      actor_net = actor_distribution_network.ActorDistributionNetwork(
          observation_tensor_spec,
          action_tensor_spec,
          fc_layer_params=(256, 256),
          continuous_projection_net=tanh_normal_projection_network.TanhNormalProjectionNetwork,
      )
  
      return sac_agent.SacAgent(
          time_step_tensor_spec,
          action_tensor_spec,
          actor_network=actor_net,
          critic_network=critic_net,
          actor_optimizer=tf.keras.optimizers.Adam(
              learning_rate=learning_rate
          ),
          critic_optimizer=tf.keras.optimizers.Adam(
              learning_rate=learning_rate
          ),
          alpha_optimizer=tf.keras.optimizers.Adam(
              learning_rate=learning_rate
          ),
          target_update_tau=0.005,
          target_update_period=1,
          td_errors_loss_fn=tf.math.squared_difference,
          gamma=0.99,
          reward_scale_factor=0.1,
          gradient_clipping=None,
          train_step_counter=train_step,
      )
  
imports: import os
  from typing import Callable, Text
  from absl import app
  from absl import flags
  from absl import logging
  import gin
  import tensorflow.compat.v2
  from tf_agents.agents import tf_agent
  from tf_agents.agents.ddpg import critic_network
  from tf_agents.agents.sac import sac_agent
  from tf_agents.agents.sac import tanh_normal_projection_network
  from tf_agents.environments import py_environment
  from tf_agents.environments import suite_mujoco
  from tf_agents.experimental.distributed import reverb_variable_container
  from tf_agents.networks import actor_distribution_network
  from tf_agents.replay_buffers import reverb_replay_buffer
  from tf_agents.system import system_multiprocessing
  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.trajectories import time_step
  from tf_agents.typing import types
label_desc: Use image node_id 1 for calling a global function with example usage: _create_agent(train_step, observation_tensor_spec, action_tensor_spec, time_step_tensor_spec, learning_rate) and returns: sac_agent