code: def run_hpo():
      # Specify the database where the experiments are stored. We use a local PickleDB here.
      storage = {
          "type": "legacy",
          "database": {
              "type": "pickleddb",
              "host": "./db.pkl",
          },
      }
  
      # Load the data for the specified experiment
      experiment = build_experiment(
          "hyperband-cifar10",
          space={
              "epochs": "fidelity(1, 120, base=4)",
              "learning_rate": "loguniform(1e-5, 0.1)",
              "momentum": "uniform(0, 0.9)",
              "weight_decay": "loguniform(1e-10, 1e-2)",
              "gamma": "loguniform(0.97, 1)",
          },
          algorithm={
              "hyperband": {
                  "seed": 1,
                  "repetitions": 5,
              },
          },
          storage=storage,
      )
  
      trials = 1
      while not experiment.is_done:
          print("trial", trials)
          trial = experiment.suggest()
          if trial is None and experiment.is_done:
              break
          valid_error_rate = main(
              **trial.params,
              checkpoint=f"{experiment.working_dir}/{trial.hash_params}",
          )
          experiment.observe(
              trial, valid_error_rate, name="valid_error_rate"
          )
          trials += 1
  
file_path: orion/examples/tutorials/code_2_hyperband_checkpoint.py
imports: import os
  import numpy
  import torch
  import torch.nn
  import torch.optim
  import torchvision
  import torchvision.models
  import torchvision.transforms
  from torch.utils.data import SubsetRandomSampler
  from orion.client import build_experiment
label_desc: Use image node_id 7 for calling a global function with example usage: run_hpo() without return types