class_docstr: Interface for defining the components of an offline RL agent.
  
  Implementations of this interface contain a complete specification of a
  concrete offline RL agent. An instance of this class can be used to build an
  offline RL agent that operates either locally or in a distributed setup.
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docstr: Creates an instance of the learner.
  
  Args:
    random_key: A key for random number generation.
    networks: struct describing the networks needed by the learner; this is
      specific to the learner in question.
    dataset: iterator over demonstration samples.
    logger_fn: factory providing loggers used for logging progress.
    environment_spec: A container for all relevant environment specs.
    counter: a Counter which allows for recording of counts (learner steps,
      evaluator steps, etc.) distributed throughout the agent.
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code: def make_learner(
      self,
      random_key: networks_lib.PRNGKey,
      networks: Networks,
      dataset: Iterator[Sample],
      logger_fn: loggers.LoggerFactory,
      environment_spec: specs.EnvironmentSpec,
      *,
      counter: Optional[counting.Counter] = None,
  ) -> core.Learner:
      """Creates an instance of the learner.
  
      Args:
        random_key: A key for random number generation.
        networks: struct describing the networks needed by the learner; this is
          specific to the learner in question.
        dataset: iterator over demonstration samples.
        logger_fn: factory providing loggers used for logging progress.
        environment_spec: A container for all relevant environment specs.
        counter: a Counter which allows for recording of counts (learner steps,
          evaluator steps, etc.) distributed throughout the agent.
      """
  
imports: import abc
  import dataclasses
  from typing import Generic, Iterator, List, Optional
  from acme import adders
  from acme import core
  from acme import specs
  from acme.jax import networks
  from acme.jax import types
  from acme.utils import counting
  from acme.utils import loggers
  import reverb
label_desc: Use image node_id 1 for calling the OfflineBuilder obj's underlying member method code with example usage: obj.make_learner(random_key, networks, dataset, logger_fn, environment_spec) without return types