code: def make_environment(training: bool = True):
      del training
      env = bsuite.load(experiment_name="deep_sea", kwargs={"size": 10})
      return single_precision.SinglePrecisionWrapper(env)
  
imports: import functools
  import operator
  from typing import Callable
  from acme import core
  from acme import environment_loop
  from acme import specs
  from acme import types
  from acme.agents.jax import actor_core
  from acme.agents.jax import actors
  from acme.agents.jax import bc
  from acme.agents.tf.dqfd import bsuite_demonstrations
  from acme.jax import networks
  from acme.jax import types
  from acme.jax import utils
  from acme.jax import variable_utils
  from acme.jax.deprecated import offline_distributed_layout
  from acme.utils import counting
  from acme.utils import loggers
  from acme.wrappers import single_precision
  import bsuite
  import dm_env
  import haiku
  import jax
  import jax.numpy
  from jax.scipy import special
  import rlax
  import tensorflow
  import tree
label_desc: Use image node_id 3 for calling a global function with example usage: make_environment(training) and returns: single_precision