code: def sample_qrdqn_params(trial: optuna.Trial) -> dict[str, Any]:
      """
      Sampler for QR-DQN hyperparams.
  
      :param trial:
      :return:
      """
      # TQC is DQN + Distributional RL
      hyperparams = sample_dqn_params(trial)
  
      n_quantiles = trial.suggest_int("n_quantiles", 5, 200)
      hyperparams["policy_kwargs"].update({"n_quantiles": n_quantiles})
  
      return hyperparams
  
file_path: FinRL/finrl/agents/stablebaselines3/hyperparams_opt.py
imports: from __future__ import annotations
  from typing import Any
  from typing import Dict
  import numpy
  import optuna
  from stable_baselines3.common.noise import NormalActionNoise
  from stable_baselines3.common.noise import OrnsteinUhlenbeckActionNoise
  from torch import nn
  from utils import linear_schedule
label_desc: Use image node_id 10 for calling a global function with example usage: sample_qrdqn_params(trial) and returns: hyperparams