class_docstr: Common superclass for SAC runners, implementing the main training controls.
docstr: Adjusts initial values where necessary.
docstr_tok: ["Adjusts","initial","values","where","necessary","."]
code: def __post_init__(self):
      """
      Adjusts initial values where necessary.
      """
  
      if self.eval_concurrency <= 0:
          self.eval_concurrency = query_cpu()
  
imports: import copy
  from abc import abstractmethod
  from dataclasses import dataclass
  from typing import Callable, List, Union
  from omegaconf import DictConfig
  from torch.utils.data import Dataset
  from maze.core.agent.policy import Policy
  from maze.core.agent.torch_actor_critic import TorchActorCritic
  from maze.core.agent.torch_policy import TorchPolicy
  from maze.core.agent.torch_state_action_critic import TorchStateActionCritic
  from maze.core.annotations import override
  from maze.core.env.maze_env import MazeEnv
  from maze.core.log_stats.log_stats import LogStatsAggregator, LogStatsLevel, get_stats_logger
  from maze.core.rollout.rollout_generator import RolloutGenerator
  from maze.core.trajectory_recording.datasets.in_memory_dataset import InMemoryDataset
  from maze.core.trajectory_recording.records.trajectory_record import SpacesTrajectoryRecord
  from maze.core.utils.config_utils import SwitchWorkingDirectoryToInput
  from maze.core.utils.factory import Factory
  from maze.train.parallelization.distributed_actors.base_distributed_workers_with_buffer import BaseDistributedWorkersWithBuffer
  from maze.train.parallelization.distributed_actors.dummy_distributed_workers_with_buffer import DummyDistributedWorkersWithBuffer
  from maze.train.parallelization.vector_env.sequential_vector_env import SequentialVectorEnv
  from maze.train.parallelization.vector_env.structured_vector_env import StructuredVectorEnv
  from maze.train.trainers.common.evaluators.rollout_evaluator import RolloutEvaluator
  from maze.train.trainers.common.model_selection.best_model_selection import BestModelSelection
  from maze.train.trainers.common.replay_buffer.replay_buffer import BaseReplayBuffer
  from maze.train.trainers.common.replay_buffer.uniform_replay_buffer import UniformReplayBuffer
  from maze.train.trainers.common.training_runner import TrainingRunner
  from maze.train.trainers.sac.sac_trainer import SAC
  from maze.utils.process import query_cpu
label_desc: Use image node_id 1 for calling the SACRunner obj's underlying member method code with example usage: obj.__post_init__() without return types